This is the accessible text file for GAO report number GAO-09-549 
entitled 'Mineral Revenues: MMS Could Do More to Improve the Accuracy 
of Key Data Used to Collect and Verify Oil and Gas Royalties' which was 
released on September 15, 2009. 

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Report to Congressional Requesters: 

United States Government Accountability Office: 
GAO: 

July 2009: 

Mineral Revenues: 

MMS Could Do More to Improve the Accuracy of Key Data Used to Collect 
and Verify Oil and Gas Royalties: 

GAO-09-549: 

GAO Highlights: 

Highlights of GAO-09-549, a report to congressional requesters. 

Why GAO Did This Study: 

In fiscal year 2008, the Department of Interior’s Minerals Management 
Service (MMS) collected over $12 billion in royalties from oil and gas 
production from federal lands and waters. Companies that produce this 
oil and gas self-report to MMS data on the amount of oil and gas they 
produced and sold, the value of this production, and the amount of 
royalties owed. Since 2004, GAO has noted systemic problems with these 
data and recommended improvements. GAO is providing: (1) a descriptive 
update on MMS’s key efforts to improve the accuracy of oil and gas 
royalty data; (2) our assessment of the completeness and reasonableness 
of fiscal years 2006 and 2007 oil and gas royalty data—the latest data 
available; and (3) factors identified by oil and gas companies that 
affect their ability to accurately report royalties owed to the federal 
government. 

What GAO Found: 

MMS has several key efforts underway to improve the accuracy of the 
payor-reported data used to collect and verify royalties, but it is too 
soon to evaluate their effectiveness. MMS is in the process of 
implementing (1) GAO’s past recommendations to help identify missing 
royalty reports and monitor payors’ changes to royalty data; (2) 
recommendations from the Royalty Policy Committee––a group empaneled by 
the Secretary of the Interior to provide advice on managing federal and 
Indian leases and revenues––to improve edit checks, monitor the quality 
of natural gas, revise gas valuation regulations, and improve 
coordination with BLM; and (3) other efforts on adding specific edits 
for sales prices and identifying discrepancies in volumes between 
operators and payors. 

While much of the royalty data we examined from fiscal years 2006 and 
2007 are reasonable, we found significant instances where data were 
missing or appeared erroneous. For example, we examined gas leases in 
the Gulf of Mexico and found that, about 5.5 percent of the time, lease 
operators reported production, but royalty payors did not submit the 
corresponding royalty reports, potentially resulting in $117 million in 
uncollected royalties. We also found that a small percentage of royalty 
payors reported negative royalty values, which cannot happen, 
potentially costing $41 million in uncollected royalties. In addition, 
payors claimed processing allowances 2.3 percent of the time for 
unprocessed gas, potentially resulting in $2 million in uncollected 
royalties. Furthermore, we found significant instances where payor-
provided data on royalties paid and the volume and/or the value of the 
oil and gas produced appeared erroneous because they were outside of 
expected ranges. 

Oil and gas company representatives reported that several factors 
affect their ability to accurately report royalties, including complex 
land ownership, administratively combining leases into units, ambiguity 
in federal regulations that establish gas prices, short time frames for 
filing royalty reports, and inaccuracies in MMS’s internal databases. 

Figure: Production Facilities on a Federal Lease in Colorado: 

[REfer to PDF for image: photograph] 

Source: GAO. 

[End of figure] 

What GAO Recommends: 

To prevent erroneous data from being entered into MMS databases and to 
check the quality of data already entered, GAO recommends that MMS 
design (1) an edit check to prevent payors from submitting a claim for 
processing allowances on gas that is not processed and (2) new edit 
checks to examine the net effect of adjustments to certain key royalty 
variables. To simplify auditing, GAO recommends that MMS royalty payors 
submit data on unit agreements and reasons for changes to original data 
submissions. In commenting on a draft of this report, Interior 
generally agreed with our findings and recommendations. 

View [hyperlink, http://www.gao.gov/products/GAO-09-549] or key 
components. For more information, contact Frank Rusco, (202) 512-3841, 
ruscof@gao.gov. 

[End of section] 

Contents: 

Letter: 

Background: 

MMS Has Ongoing Efforts to Improve the Accuracy of Payor-Reported 
Royalty Data, but It Is Too Early to Assess the Effectiveness of These 
Efforts: 

In Several Instances, Data Used to Collect and Verify Royalties Are 
Either Missing or Appear to Be Erroneous: 

Multiple Factors Affect Oil and Gas Companies' Abilities to Accurately 
Report Royalties Owed to the Federal Government: 

Conclusions: 

Recommendations for Executive Action: 

Agency Comments and Our Evaluation: 

Appendix I: Scope and Methodology: 

Appendix II: Comments from the Department of the Interior: 

Appendix III: GAO Contact and Staff Acknowledgments: 

Tables: 

Table 1: GAO Analysis of Key Royalty Variables, MMS's Oil and Gas 
Royalty Data Exclusive of Royalty-in-Kind Transactions, Fiscal Years 
2006 and 2007: 

Table 2: Royalty Rate Calculations Outside of Expected Ranges for 
Federal Oil and Gas Leases, Fiscal Years 2006 and 2007: 

Figures: 

Figure 1: MMS's Processes for Submitting, Checking, and Accepting 
Royalty Data: 

Figure 2: Percentage of Gas Production Reports without Corresponding 
Royalty Reports in the Offshore Gulf of Mexico for Fiscal Years 2006 
and 2007: 

Figure 3: Range of Reasonable Oil Prices in the Offshore Gulf of Mexico 
Based on Highest and Lowest Daily Spot Prices for Each Month: 

Figure 4: Sales Prices for Oil from Federal Leases in the Offshore Gulf 
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007: 

Figure 5: Range of Reasonable Gas Prices in the Gulf of Mexico Based on 
Highest and Lowest Daily Spot Prices for Each Month and the First of 
the Month Price at the Henry Hub: 

Figure 6: Sales Prices for Gas from Federal Leases in the Offshore Gulf 
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007: 

Figure 7: Block Diagram Illustrating the Hypothetical Creation of a 
Federal Unit: 

Figure 8: Block Diagram Illustrating a Hypothetical Complex 
Relationship between Unit Agreements and Potential Impacts on 
Oversight: 

Figure 9: Numbers of Oil and Gas Royalty Records and Leases Reported 
per Month for Fiscal Years 2006 and 2007: 

Abbreviations: 

API: American Petroleum Institute: 

BLM: Bureau of Land Management: 

Btu: British Thermal Unit: 

CPT: Compliance Program Tool: 

EDI: Electronic Data Interchange: 

FERC: Federal Energy Regulatory Commission: 

IG: Inspector General: 

IPAMS: Independent Petroleum Association of Mountain States: 

IRS: Internal Revenue Service: 

LLS: Light Louisiana Sweet: 

MMBtu: millions of British Thermal Units: 

MMS: Minerals Management Service: 

OGOR: Oil and Gas Operations Report: 

PCC: Production Coordination Committee: 

RIK: Royalty In Kind: 

RPC: Royalty Policy Committee: 

TIMS: Technical Information Management System: 

[End of section] 

United States Government Accountability Office: 
Washington, DC 20548: 

July 15, 2009: 

The Honorable Jeff Bingaman:
Chairman:
Committee on Energy and Natural Resources:
United States Senate: 

The Honorable Nick J. Rahall, II:
Chairman:
Committee on Natural Resources:
House of Representatives: 

The Honorable Darrell Issa:
Ranking Member:
Committee on Oversight and Government Reform:
House of Representatives: 

The Honorable Carolyn Maloney:
House of Representatives: 

Royalties for oil and natural gas produced from federal lands and 
waters are one of the country's largest non-tax sources of revenue, 
accounting for over $12 billion in collections during fiscal year 2008. 
The Department of the Interior's Minerals Management Service (MMS) is 
responsible for collecting royalties from companies that produce oil 
and gas from almost 29,000 federal and Indian leases. Each month, these 
oil and gas companies self-report to MMS data on the amount of oil and 
gas they produced and sold, the value of this production, and the 
amount of royalties owed the federal government. Over the past 5 years, 
GAO has found problems with these data. These problems include missing 
data, errors in the self-reported amounts of oil and gas produced, self-
reported oil and gas sales value data that, given the reported volumes 
of oil and gas sold, appear at odds with prevailing market prices for 
oil and gas, and a lack of controls over changes to the data that 
companies report. Although data accuracy was not the focus of our 
previous work, we recommended that MMS correct some of these data. 

Building on our prior work examining MMS's royalty data, we are 
providing (1) a descriptive update of MMS's ongoing efforts to improve 
the accuracy of oil and gas royalty data, (2) our assessment of the 
completeness and reasonableness of fiscal years 2006 and 2007 oil and 
gas royalty data, and (3) factors identified by oil and gas companies 
that affect the ability of these oil and gas companies to accurately 
report royalties owed to the federal government. We are addressing only 
cash royalty payments; we have a separate engagement underway 
addressing issues related to MMS's Royalty-in-Kind Program--an option 
whereby MMS takes a share of oil and gas produced on federal lands and 
waters in lieu of cash royalty payments. 

To describe MMS's efforts to improve the accuracy of royalty data, we 
reviewed and discussed with MMS officials their action plans to 
implement recommendations made by GAO and Interior's Royalty Policy 
Committee, reviewed a demonstration of MMS's Compliance Program Tool 
(CPT)--an automated system that analyzes royalty payments--and 
discussed with MMS officials their implementation of the CPT to 
systemically identify misreported volumes and missing royalty reports. 
We made no attempt to evaluate the effectiveness of MMS's ongoing 
efforts to improve the accuracy of royalty data because these efforts 
are not fully implemented. 

To assess the completeness and reasonableness of fiscal years 2006 and 
2007 oil and gas royalty data, we first analyzed MMS's existing edit 
checks and plans for modifying or adding new edit checks. In our 
subsequent analyses, we replicated several of MMS's edit checks but 
used a different method. While MMS evaluates each royalty record 
individually, we combined all royalty records submitted by a given 
payor for each month, product type, and lease, thereby examining the 
cumulative effect of changes to original royalty data. We then used our 
methodology to evaluate 4.1 million royalty records for fiscal years 
2006 and 2007 based on extensive data reliability work conducted on two 
previous assignments. In doing so, we developed a risk-based approach 
to identify and review key aspects of data collection, processing, and 
reporting, and reviewed the extent to which MMS's royalty collection 
system fills those needs. We also reviewed reports and testimonies on 
oil and gas royalties to understand the historical problems associated 
with the royalty collection process, and we interviewed key MMS staff 
and state and tribal auditors that work on federal oil and gas leases 
to identify any continuing concerns with MMS's royalty reporting 
process. 

To examine factors that oil and gas companies identified as limiting 
their ability to accurately report royalties owed to the federal 
government, we interviewed a non-random sample of oil and gas company 
representatives from the 15 companies that report to MMS the highest 
amount of royalty data and from the two largest national oil and gas 
industry associations. The 10 companies that responded to our request 
for information represent the major companies, large independent 
companies, mid-size independent companies, and small independent 
companies. We chose to interview a non-random sample because we lack 
the authority to compel private companies to participate in such 
interviews and because we deemed the cost of trying to convince a large 
enough sample to participate to make the results statistically relevant 
to be greater than the benefits of being able to make inferences from 
the sample interviews. As a result, our results for this objective 
should not be viewed as a comprehensive list of reporting difficulties 
or an evaluative assessment of the validity of all the elements of the 
list. A detailed description of our scope and methodology appears in 
appendix I. 

We conducted this work from July 2008 to April 2009 in accordance with 
generally accepted government auditing standards. Those standards 
require that we plan and perform the audit to obtain sufficient, 
appropriate evidence to provide a reasonable basis for our findings and 
conclusions based on our audit objectives. We believe that the evidence 
obtained provides a reasonable basis for our findings and conclusions 
based on our audit objectives. 

Background: 

Companies that develop and produce oil and gas resources do so under 
leases obtained from and administered by the Department of the 
Interior. Interior's Bureau of Land Management (BLM) manages onshore 
leases, and Interior's MMS manages offshore leases. MMS is responsible 
for collecting the royalties on all federal and many Indian oil and gas 
leases. Royalties on producing leases are a percentage of the value of 
the production sold less deductions known as allowances.[Footnote 1] 
Together, BLM and MMS are responsible for ensuring that oil and gas 
companies comply with applicable laws, regulations, and policies for 
more than 29,000 producing federal and Indian leases, which account for 
about 23 percent of domestically produced gas and 26 percent of 
domestically produced oil. 

In some cases, several companies form partnerships to explore and 
develop oil and gas leases, thereby sharing the risk, the costs, and 
the benefits. These companies often elect from among themselves a 
single company, called the operator, to manage the physical drilling of 
wells and the installation of production equipment. Operators report 
monthly to MMS on the Oil and Gas Operations Report (OGOR) the amount 
of oil and gas produced from each well on each lease. In addition, all 
the companies that share the proceeds from the sale of oil and gas from 
federal lands and waters are required each month to report to MMS on 
the Form MMS-2014 data about the oil and gas they sold. MMS refers to 
these companies, including the operator, as royalty payors. The data on 
each Form MMS-2014 are then stored in MMS's system as a number of 
records, each of which consists of many variables, such as the name of 
the payor, the lease number, the amount of oil and gas sold (sales 
volume), the value of this oil and gas (sales value), allowable 
deductions for transportation and processing, and the amount of 
royalties owed (royalty value). Payors can legally adjust these data 
they report for up to 6 years if, for example, they learn that the data 
they submitted were incorrect.[Footnote 2] Almost all payors submit 
these data electronically. 

Within its 5-year business plan for fiscal years 2008 to 2012, MMS has 
set an objective of ensuring timely and more accurate mineral revenue 
reporting and payment.[Footnote 3] According to Interior's 2009 Budget 
Justification, MMS set goals in fiscal years 2008 and 2009 of ensuring 
that companies report 98 percent of their data accurately the first 
time, up from actual percentages of 97.4 in fiscal year 2006 and 97.3 
in fiscal year 2007, and compared to an actual percentage of 98.3 as 
reported by MMS for fiscal year 2008. While we could not find a 
business entity that performed identical services to those of MMS for 
comparing its accuracy of electronic transactions, we chose the 
Internal Revenue Service (IRS) for comparison because of the potential 
difficulty in interpreting complex tax regulations, determining 
allowable deductions, and calculating taxes owed. To this end, IRS 
reported in January 2008 that its electronic tax filers have a 99 
percent accuracy rate--only slightly higher than the rates reported by 
MMS. To help improve data accuracy, MMS subjects payor-reported royalty 
data to over 140 edit checks. Specifically, MMS has incorporated 
certain up-front edit-checks in its data acceptance tools that help 
detect and reject erroneous payor-reported royalty data before MMS's 
data systems will accept them. MMS also incorporates a second level of 
edit checks that review payor-reported data for additional errors after 
data are accepted. Edit checks must comply with GAO standards for 
internal controls in the federal government as required by 31 U.S.C. § 
3512(c) and (d), commonly referred to as the Federal Managers' 
Financial Integrity Act of 1982. These standards identify and address 
major performance challenges and areas at greatest risk for fraud, 
waste, abuse, and mismanagement. Furthermore, the standards state that 
automated edits and checks should help control the accuracy and 
completion of transaction processing. 

Given the large amount of royalty revenues at stake and problems with 
royalty management identified by past GAO, Interior Inspector General, 
and other reports, MMS's processes for ensuring the accurate collection 
of royalties have been the subject of continuing scrutiny. For example, 
in 2003 while examining MMS's Royalty-in-Kind program, we found that 
from 1.9 percent to 3.3 percent of the data that we examined for oil 
leases in Wyoming and the Gulf of Mexico were erroneous or missing, and 
that 6 percent of the data that we examined for gas leases in the Gulf 
of Mexico were anomalous, meaning that data values fell outside of 
expected ranges.[Footnote 4] Similarly in 2004, we found that 40 
percent of the royalty data that we examined for 10 geothermal projects 
was either missing or erroneous.[Footnote 5] In 2006, we examined the 
relationship between the increases in oil and gas prices from 2000 to 
2005 and the amount of royalties collected during that time and found 
that 8.5 percent of the data appeared anomalous.[Footnote 6] In 2008, 
we reported that MMS's royalty management system lacked several 
capabilities that would provide greater assurance that royalties are 
collected accurately.[Footnote 7] These capabilities include readily 
identifying changes that companies make to previously entered data, 
detecting the absence of royalty reports, and implementing a process 
for collecting the proper amount of royalties when MMS identifies that 
oil and gas volumes have been incorrectly reported. Among other things, 
we recommended MMS identify when royalty reports have not been filed as 
required and when companies make changes to data provided to MMS after 
the statutory limitation on such changes. We also reported that MMS was 
taking steps to address these deficiencies. 

In addition to GAO's work, Interior's Inspector General (IG) analyzed 
MMS's auditing and compliance process and made several recommendations 
in 2007 to improve these functions and the systems that track them. 
Also, the Royalty Policy Committee (RPC)--a group empaneled by the 
Secretary of the Interior and charged with providing advice on managing 
federal and Indian leases and revenues--has identified numerous 
deficiencies. In December 2007, the RPC issued a report that included 
more than 100 recommendations to strengthen Interior's royalty 
collections by improving BLM's and MMS's verification of production 
volumes, improving many areas of MMS's audit and compliance efforts by 
establishing a compliance strategy counsel, improving coordination 
between MMS and BLM, and improving MMS's computer system. 

MMS Has Ongoing Efforts to Improve the Accuracy of Payor-Reported 
Royalty Data, but It Is Too Early to Assess the Effectiveness of These 
Efforts: 

MMS has three major efforts underway to improve the accuracy of payor- 
reported royalty data used to collect and verify royalties, but it is 
too early to evaluate the effectiveness of these efforts. First, MMS is 
beginning to address GAO's recommendations concerning the 
identification of missing royalty reports and the monitoring of 
adjustments that companies make to their royalty data.[Footnote 8] 
Second, MMS is implementing RPC recommendations concerning edit checks, 
valuation regulations for natural gas, and coordination with BLM. 
Third, MMS is continuing to develop processes to increase the accuracy 
of royalty reporting data by improving edit checks on oil and gas sales 
prices and using the CPT to identify errors in the amount of oil and 
gas reportedly sold by payors. 

MMS Is Beginning to Address GAO's Recommendations, but It Is Too Early 
to Assess the Effectiveness of These Actions: 

To address a past GAO recommendation, MMS is developing a process to 
automatically detect within 6 months those cases in which a company has 
not filed a royalty report when it has filed a production report. MMS 
officials explained that 6 months is a reasonable timeframe, and that 
companies make most corrections to missing or incorrect royalty data 
within this time frame. Under the current royalty reporting system, 
cases in which a company has not filed a royalty report may not be 
detected until more than 2 years after the initial reporting date, when 
MMS personnel in their compliance group begin to target leases for a 
review or audit. According to MMS officials, personnel in the financial 
management group are beginning to identify missing royalty reports by 
identifying instances in which the royalty report--the Form MMS-2014-- 
is absent when a production report--the OGOR--was filed by the 
operator. With few exceptions, MMS should receive corresponding royalty 
reports for each production report it receives. MMS has additional 
checks in place through its CPT for determining when both the OGOR and 
the Form MMS-2014 are missing. 

Also in response to a GAO recommendation, MMS is developing an 
automated process to identify changes that royalty payors make to their 
previously entered royalty data that exceed the 6-year statutory limit 
on such adjustments or that occur after compliance work, including 
audits, has been completed. Although these adjustments may change 
payors' royalty payments, prior to this effort MMS's royalty reporting 
system could not monitor them and payors could continue to adjust their 
previously reported royalty data without prior MMS approval or review. 
In addition, companies could change royalty data after an audit has 
been completed, and MMS needs to be able to identify when this occurs, 
as we have suggested in our previous work. While adjustments may occur 
for legitimate reasons, and identifying them will not prevent them from 
occurring, it could facilitate later scrutiny and follow up with 
company officials. However, it is too early to evaluate the 
effectiveness of these actions. 

MMS Has Developed Plans to Address RPC Recommendations, but More 
Progress Is Needed before Results Can Be Evaluated: 

MMS is implementing action plans to address royalty reporting issues 
raised by the 2007 RPC Report. The following actions directly relate to 
four recommendations for improving the accuracy of the royalty 
reporting process out of over 100 recommendations identified by the 
RPC. First, MMS is in the process of using its existing edit checks and 
adding additional edit checks to examine more data before the data are 
entered into its database, instead of examining data that have already 
been accepted and stored. Specifically, this change will affect royalty 
data that payors submit through the electronic reporting interface--a 
Web site-based portal through which MMS accepts almost 30 percent of 
its data. According to MMS officials, the other 70 percent of royalty 
records are accepted through the Electronic Data Interchange (EDI)--a 
standardized method of transferring data electronically between 
computer systems, such as a payor's system and MMS's system. Currently, 
there are some edit checks built into the EDI software, but MMS's goal, 
as outlined in its strategic business plan for 2008-2012, is to require 
EDI reporters to implement most edits on their individual computer 
systems before they submit the data through EDI. If they do not, then 
payors must use MMS's other system for submitting data--the electronic 
reporting interface--which accepts fewer royalty records at a time, but 
already has these up-front edit checks built into its system. As GAO 
has noted in prior reports, edit checks that prevent potentially 
erroneous data from entering the databases offer advantages over 
efforts to continually clean up erroneous data allowed into the system. 
However, it is too early to tell how useful these specific efforts will 
be. MMS's processes for checking data are outlined in figure 1. 

Figure 1: MMS's Processes for Submitting, Checking, and Accepting 
Royalty Data: 

[Refer to PDF for image: illustration] 

Data submission: 

* MMS specified edit checks integrated into company information 
systems. 
* Company information systems: feeds Electronic data interchange. 

* Electronic reporting interface. 

Data acceptance: 

* Electronic data interchange continues. 

* MMS edit checks: 
- If data pass, data allowed into MMS database; 
- If data fail key edit checks, data are rejected. 

Data used for operations: 

* MMS information systems – royalty database. 

* Additional MMS edit checks on database and research to correct 
errors. 

Source: GAO. 

Note: Not all data are submitted electronically. Less than 1 percent is 
submitted in paper format and are keypunched and loaded into the 
database, where they are subjected to edit checks. All data submitted 
through the electronic reporting interface that fail edit checks are 
not rejected. Some data with errors that MMS considers less important 
are accepted by the database. 

[End of figure] 

Second, MMS is working on a problem identified by the RPC concerning 
the accuracy of reporting natural gas royalties. The RPC recommended 
that MMS add a data field on the Form MMS-2014 that identifies the heat 
content per cubic foot of natural gas, which is important in 
determining the amount of royalties owed. State and tribal royalty 
auditors with whom we spoke also identified the need to check on the 
heat content of natural gas. In response to the RPC recommendation, MMS 
officials said that they developed and recently implemented an 
alternate plan for evaluating the information identified by the RPC 
using data already collected on the Form MMS-2014 and maintained in its 
databases. In particular, payors report to MMS the quantity of natural 
gas sold (in thousands of cubic feet) as well as the total heating 
value of all the gas sold (in millions of Btus, an industry standard 
for selling natural gas). MMS officials told us they plan to calculate 
the heating value per cubic foot from these existing data fields, by 
dividing the total heating value by the quantity sold, and implement an 
edit check on the reasonableness of the results of this calculation. 
[Footnote 9] Moreover, MMS officials said that it was too costly to 
change the structure of its database to accommodate a new data field 
and modify how data are collected. We believe that MMS's alternative is 
a reasonable approach and that it is likely to identify errors in 
reported gas volumes. 

Third, MMS is planning to publish proposed revisions to its gas 
valuation regulations and guidelines that they believe will address 
several problems. For example, MMS regulations provide a series of 
benchmarks for companies to use in establishing the price of natural 
gas when they sell it to their affiliates. However, according to the 
RPC and state auditors, these benchmarks are difficult to apply and do 
not reflect how gas is currently sold so they recommend that MMS should 
replace these benchmarks with widely published market indexes. Another 
problem that MMS intends to address with its new gas valuation 
regulations relates to how companies can take deductions from gas 
revenues. According to MMS regulations, the costs for transportation 
and processing must be properly allocated among the individual products 
that result from the processing of gas. However, gas purchasers can 
"bundle" all of these charges together, making it difficult for the 
payor to determine how to allocate these deductions and then to 
calculate what is actually owed in royalties. While MMS has plans to 
address these and other issues with its new regulations, they were 
unable to give us sufficient details about how this would be done for 
us to evaluate the effectiveness of the new regulations. MMS has a 
target date for completion of the new proposed regulations of December 
2009. 

Fourth, in response to RPC recommendations that MMS improve its 
interagency coordination with BLM, MMS has taken a first step to 
improve coordination. Specifically, the RPC recommended that the 
Department of the Interior establish a Production Coordination 
Committee (PCC) that is charged with, among others things, defining and 
coordinating common processes, defining common data standards, and 
addressing technical issues for information sharing between the two 
agencies. To begin this process, MMS, BLM, and the Bureau of Indian 
Affairs held a 3-day PCC meeting in September 2008, during which a 
number of key issues regarding the accuracy of royalty data were 
discussed, including (1) placing more responsibility on industry to 
provide clean data to MMS; (2) resolving invalid lease numbers; (3) 
sharing information on rents, agreements, and Indian leases in a more 
timely manner; and (4) providing notices to MMS when wells first start 
to produce. This meeting was a first step in improving inter-agency 
coordination, but it is too early to judge the effectiveness of the 
committee. MMS officials said that additional meetings are planned on a 
recurring basis. 

MMS Has Other Efforts Underway to Improve the Quality of Payor-Reported 
Royalty Data, but Their Preliminary Nature Precludes Assessing Their 
Effectiveness: 

MMS officials told us they are evaluating a process to incorporate more 
detailed market prices into its system to compare sales prices that MMS 
calculates from payor-reported royalty data to relevant market prices. 
MMS does not require payors to report their sales prices but can 
calculate an implicit sales price by dividing the total value of the 
oil or gas that payors report (sales value) by the volume that payors 
report as having sold (sales volume). Currently, MMS uses for 
comparison a few oil and gas prices with a wide range of values for all 
leases regardless of where the lease is located or the quality of oil 
that is produced. MMS officials told us that they intend to incorporate 
a more detailed price table into its royalty reporting system by 2010 
that will include more specific sales prices related to geographic 
areas and specific sales months. We believe that this could be a 
significant improvement, but it remains too early to assess MMS's 
efforts. 

In addition, during the course of our work, MMS officials told us they 
plan to expand the implementation of two edit checks. First, MMS plans 
to expand the use of an edit check that will calculate the royalty rate 
from payor-reported data and compare this with the royalty rate 
specified in each lease. As with sales prices, MMS does not require 
payors to report royalty rates but can calculate implicit royalty rates 
from payor-reported data. MMS can calculate implicit royalty rates by 
dividing the amount of royalties that payors report (royalty value) by 
the total value of the oil or gas that payors report (sales value). 
While MMS has checked royalty rates on Indian leases and prevented 
erroneous data on these leases from entering its system since prior to 
2001, MMS's checking of royalty rates has not prevented erroneous data 
on federal leases from entering its system. However, MMS plans to 
resolve this issue on federal leases by the end of fiscal year 2009. 
Second, MMS recently began using an edit check that ensures payors take 
processing allowances only on gas that is processed. MMS reported that 
in April 2009 it implemented such an edit check in its electronic 
reporting interface. This action will affect about 30 percent of data 
entering MMS's system, but will not impact potentially erroneous data 
that companies submit through the EDI. We believe that expanding the 
use of both of these edit checks can improve MMS's ability to evaluate 
self-reported royalty data, but we will be unable to evaluate the 
effectiveness of these new processes until they are fully implemented. 

In 2008, MMS auditors in its compliance group began to use the CPT to 
identify discrepancies--based on certain thresholds--between the 
volumes of oil and gas produced that lease operators reported on the 
OGOR and the total volumes sold that payors reported on the Form MMS- 
2014.[Footnote 10] When conducting this process, MMS also is able to 
identify instances when a royalty payor fails to submit the required 
Form MMS-2014. However until recently, these comparisons are not done 
until over 2 years after royalty data have been submitted when MMS 
begins to select leases for audit. While this volumetric comparison had 
been done much sooner and routinely for all leases in the past, the 
process was dropped when MMS implemented its current information system 
in 2001 because the new module that was to perform this function was 
not yet ready for implementation and because MMS wanted to expand the 
comparison to include an examination of the amount of royalties paid 
and the value of the oil and gas sold. MMS officials explained that 
under the old system, potential mismatches between OGOR and 2014 
volumes often involved errors in the royalties paid and/or the value of 
the oil and gas sold, and it was important to look at all three of 
these components at once. They further explained that the new module 
was never implemented but instead was replaced with an expanded use of 
the CPT, albeit at a much later date than initially anticipated. MMS 
reported that in January 2009, it began using the CPT to compare 
volumes and examine the amount of royalties paid and the value of the 
oil and gas sold within 6 to 9 months after payors submit data. 
Moreover, in 1992 when we last examined the comparison of volumes on 
the OGOR with volumes on the Form MMS-2014, we determined that it was 
cost effective to follow up on at least the largest of the 
discrepancies and support MMS doing this within an earlier time frame, 
such as 6 months after receiving royalty data. 

In Several Instances, Data Used to Collect and Verify Royalties Are 
Either Missing or Appear to Be Erroneous: 

While much of the royalty data we examined from fiscal years 2006 and 
2007 appears reasonable, we found several instances where key data were 
missing or appear to be erroneous. For example, our close examination 
of producing gas leases in the Gulf of Mexico indicated that up to 5.5 
percent of the time, royalty reports were missing for these leases. We 
also found that from about 2 to 7.4 percent of the time, depending on 
the group of leases we examined, either the amount of royalties that 
payors report due (royalty value) and/or the total value of the oil and 
gas that payors report (sales value) appeared erroneous. In addition, 
3.9 percent of sales values and/or the volume that payors report as 
having sold (sales volume) from offshore oil leases in the Gulf of 
Mexico appeared erroneous while about 6.6 percent of one or both of 
these data elements appeared erroneous for offshore gas leases in the 
Gulf of Mexico. 

Checks for Completeness of Payor-Reported Royalty Data Indicate That 
Certain Data Are Missing: 

Our detailed examination of producing gas leases in the Gulf of Mexico 
indicated that 5.5 percent of royalty reports were missing. Using 
production reports filed by lease operators, we identified all leases 
producing gas in the Gulf from January 2006 through September 
2007.[Footnote 11] For each month in which operators reported gas 
production, we checked MMS's monthly royalty reports to ensure that 
payors reported sales of gas.[Footnote 12] We found that about 5.5 
percent of the time that operators reported monthly gas production from 
leases, payors did not submit the corresponding monthly royalty report. 
The missing royalty reports for this production represent potentially 
about $117 million in royalties that may not have been collected. 
[Footnote 13] However, it is possible that instead of reporting 
royalties on the appropriate reports, payors may have misreported these 
royalties on reports for other leases, and as such, additional 
royalties would not be due. We also observed instances in which the 
total gas production on the royalty reports was substantially less than 
that on the production reports, possibly indicating that one of 
multiple payors on that lease may not have submitted a royalty report 
for that month. While a significant number of the almost 1,500 leases 
in our sample had royalty reports but no production reports, missing 
production reports were more prevalent for the last 3 months of fiscal 
year 2007, possibly indicating that these reports had not yet been 
received or accepted by MMS's system. Missing royalty reports are 
illustrated in figure 2. 

Figure 2: Percentage of Gas Production Reports without Corresponding 
Royalty Reports in the Offshore Gulf of Mexico for Fiscal Years 2006 
and 2007: 

[Refer to PDF for image: vertical bar graph] 

Date: January 2006; 
Percentage of reports: 4.77%. 

Date: February 2006; 
Percentage of reports: 4.67%. 

Date: March 2006; 
Percentage of reports: 6.02%. 

Date: April 2006; 
Percentage of reports: 6.14%. 

Date: May 2006; 
Percentage of reports: 6.60%. 

Date: June 2006; 
Percentage of reports: 6.42%. 

Date: July 2006; 
Percentage of reports: 4.13%. 

Date: August 2006; 
Percentage of reports: 5.45%. 

Date: September 2006; 
Percentage of reports: 5.26%. 

Date: October 2006; 
Percentage of reports: 5.28%. 

Date: November 2006; 
Percentage of reports: 4.72%. 

Date: December 2006; 
Percentage of reports: 4.57%. 

Date: January 2007; 
Percentage of reports: 5.29%. 

Date: February 2007; 
Percentage of reports: 5.70%. 

Date: March 2007; 
Percentage of reports: 6.07%. 

Date: April 2007; 
Percentage of reports: 6.01%. 

Date: May 2007; 
Percentage of reports: 6.02%. 

Date: June 2007; 
Percentage of reports: 6.07%. 

Date: July 2007; 
Percentage of reports: 6.69%. 

Date: August 2007; 
Percentage of reports: 4.94%. 

Date: September 2007; 
Percentage of reports: 5.43%. 

Source: GAO analysis of MMS data. 

[End of figure] 

Checks for Reasonableness of Payor-Reported Royalty Data Indicate 
Errors in Transportation and Processing Allowances: 

We evaluated all royalty data for fiscal years 2006 and 2007--excluding 
royalty-in-kind leases--for obvious errors in key reported royalty 
variables, including volumes of oil and gas sold, the value of this oil 
and gas, and royalties paid, and found that the error rate for these 
variables ranged from 0 percent to about 2.3 percent, with the highest 
levels of errors being found in transportation and processing 
allowances. This analysis is summarized in table 1, along with 
subsequent analyses discussed below. We used a different method than 
MMS's edit checks to evaluate the reasonableness of royalty data. For 
example, MMS's edit checks generally evaluate each royalty record 
individually, and a royalty payor may submit multiple records for a 
given lease each month, including the original royalty report and often 
times multiple corrections to the volumes sold or the royalties paid. 
However, we combined all royalty records associated with a given payor 
for each month, product type, and lease. Unlike MMS's edit checks of 
individual royalty records, our methodology is able to detect if 
adjustments exceed the amount of the original entries. For example, in 
checking the sum of the sales values, sum of sales volumes, and sum of 
royalty values that payors submitted for a given month, product type, 
and lease, we found that over 99.8 percent of the time these sums were 
positive, as one would expect when payors owe royalties.[Footnote 14] 
However, payors submit one payment per month for all their federal 
leases; therefore a negative royalty value for an individual lease may 
go undetected if it is small in comparison to the sum of the royalty 
values for all their other leases. Although the 0.2 percent of royalty 
values that we found to be negative is a small percentage, collectively 
this represented about $41 million in royalties that may not be 
collected if these instances are not detected in future compliance work 
or audits. Further, a check for positive royalty values is not a 
precise measure of accuracy. Rather, it is a gross check of 
reasonableness and some positive royalty rates, which we did not 
evaluate, could have been lower than they were supposed to be. 

We found that transportation allowances and processing allowances, 
which should always be negative values in the database, were positive 
1.73 percent and 0.77 percent of the time, respectively. We also found 
that about 2.3 percent of claimed processing allowances were incorrect. 
These processing allowances were associated with either unprocessed 
gas, which by definition is not entitled to a processing allowance, or 
coalbed methane, which is never processed, and therefore should not 
receive an allowance. Claiming processing allowances for gas that was 
not processed could result in MMS collecting about $2 million less in 
royalties than are due for the fiscal year 2006 and 2007 leases that we 
examined. However, the gas reported as unprocessed gas could be 
processed gas that was improperly reported as unprocessed gas by the 
payors, and hence, no additional royalties would be due. Either way, 
there are reporting errors that raise questions about the accuracy of 
royalty collections. In addition, we checked that transportation and 
processing allowances did not exceed regulatory limits and found that 
they were within limits nearly 100 percent of the time. Lastly, we 
checked and verified that payors did not report sales volumes when 
reporting transportation and processing allowances separately from 
royalty amounts. This is not permitted because the reporting of sales 
volumes in this situation would lead to reporting the volumes sold 
twice. Table 1 summarizes the types of errors for which we checked and 
the percent of times they occurred. 

Table 1: GAO Analysis of Key Royalty Variables, MMS's Oil and Gas 
Royalty Data Exclusive of Royalty-in-Kind Transactions, Fiscal Years 
2006 and 2007: 

Definition of possible error associated with key royalty variables: 
Reporting sales volume when reporting allowances separately from 
royalties due; 
Percent error rate found: 0. 

Definition of possible error associated with key royalty variables: 
Exceeding the regulatory limit for processing allowances[A]; 
Percent error rate found: 0.02. 

Definition of possible error associated with key royalty variables: 
Exceeding the regulatory limit for transportation allowances[A]; 
Percent error rate found: 0.06. 

Definition of possible error associated with key royalty variables: 
Reporting negative sales volume; 
Percent error rate found: 0.12. 

Definition of possible error associated with key royalty variables: 
Reporting negative sales values; 
Percent error rate found: 0.20. 

Definition of possible error associated with key royalty variables: 
Reporting negative royalty values; 
Percent error rate found: 0.20. 

Definition of possible error associated with key royalty variables: 
Reporting positive processing allowances; 
Percent error rate found: 0.77. 

Definition of possible error associated with key royalty variables: 
Reporting positive transportation allowances; 
Percent error rate found: 1.73. 

Definition of possible error associated with key royalty variables: 
Claiming processing allowance for unprocessed gas or coalbed methane; 
Percent error rate found: 2.29. 

Source: GAO analysis of MMS data. 

[A] Payors can exceed the regulatory limit with prior approval from 
MMS. 

[End of table] 

Significant Amounts of Payor-Reported Data Appear Erroneous as 
Indicated by Implicit Royalty Rates: 

We found that, of the key royalty variables self-reported by royalty 
payors, either the royalties owed, the value of the oil or gas sold, or 
both, appeared erroneous from 2 to 7.4 percent of the time, depending 
on the group of leases that we examined. MMS's royalty system does not 
require payors to report royalty rates but rather the amount of their 
royalty payment--royalty value--and the total amount they received for 
the sale of oil or gas from each federal lease--sales value. We 
calculated an implicit royalty rate by dividing royalty value by sales 
value and compared this number to royalty rates generally specified in 
federal leases. Because payors are not required to report the royalty 
rate that applies to each individual lease and data were not readily 
available to us, it was time prohibitive to individually compare each 
calculation to the royalty rate specified in the lease. Instead, we 
compared the calculated rates to general lease terms, allowing for 
significant but common departures from these terms. 

We found that either royalty values or sales values, or both, were 
erroneous about 2.2 percent of the time for offshore oil leases and 
about 2 percent of the time for offshore gas leases when we calculated 
implicit royalty rates with fiscal year 2006 and 2007 data. We compared 
our implicit royalty rates with standard offshore lease terms of either 
12.5 percent or 16.67 percent, allowing for some rounding error in 
these rates. Our analysis did not identify as erroneous those instances 
when the calculated royalty rate was 12.5 percent, but the lease 
royalty rate was actually 16.67 percent, or vice versa. We also 
compared leases for which the calculated implicit royalty rates were 
other than 12.5 or 16.67 percent to actual royalty rates as specified 
in the federal lease and adjusted our analysis for those few times when 
these calculated, but apparently erroneous royalty rates, were 
legitimate. As such, a royalty rate that is different from general 
lease terms means that either the payor-reported royalty value or the 
sales value is erroneous. MMS acknowledged that erroneous royalty rates 
could result from payors misreporting the sales value or the royalty 
value owed to the federal government. 

We found that either royalty values, sales values, or both, appeared 
erroneous about 7.4 percent of the time for onshore oil leases and 
about 4.8 percent of the time for onshore gas leases when we calculated 
implicit royalty rates with fiscal year 2006 and 2007 data.[Footnote 
15] We compared our implicit royalty rates with standard onshore oil 
and gas lease terms of either 12.5 percent or a variable royalty rate 
schedule that depended on production volumes for certain leases issued 
before 1988. These variable rates ranged from 12.5 percent to 25 
percent for oil production and were either 12.5 percent or 16.67 
percent for gas production. We also assumed royalty rates of 5 and 10 
percent as being correct because MMS indicated that these were common 
royalty rates on certain older leases, and we verified this by 
examining a sample of leases. We excluded all oil leases prior to 
February 2006 because royalty rates below 12.5 percent were in effect 
during that time for low volume or heavy oil production. Our analysis 
did not identify as erroneous those instances when the implicit royalty 
rate matched standard royalty rates but was nevertheless incorrect. In 
addition to misreporting royalty values or sales values, MMS said that 
the higher percentage of apparently erroneous royalty data for onshore 
oil leases may be due to royalty payors continuing to incorrectly pay 
royalties under expired provisions for low volume or heavy oil. 
Erroneous royalty rates are summarized in table 2. 

Table 2: Royalty Rate Calculations Outside of Expected Ranges for 
Federal Oil and Gas Leases, Fiscal Years 2006 and 2007: 

Type of lease: Offshore oil; 
Apparent error rate: 2.2%. 

Type of lease: Offshore gas; 
Apparent error rate: 2.0%. 

Type of lease: Onshore oil; 
Apparent error rate: 7.4%. 

Type of lease: Onshore gas; 
Apparent error rate: 4.8%. 

Source: GAO analysis of MMS data. 

[End of table] 

Significant Amounts of Payor-Reported Data Appear Erroneous as 
Indicated by Implicit Sales Prices in the Gulf of Mexico: 

We found that either sales values or sales volumes appeared erroneous 
about 3.9 to 6.6 percent of the time we used fiscal year 2006 and 2007 
royalty data to calculate implicit sales prices in the offshore Gulf of 
Mexico.[Footnote 16] MMS does not require payors to report oil and gas 
sales prices (prices per unit sold) but instead requires payors to 
report the total amount they received for the sale of oil or gas from a 
federal lease--sales value--and the total volume of oil or gas that 
they sold--sales volume. We calculated an implicit sales price per unit 
by dividing sales value by sales volume and compared this number to 
prevailing market prices at the time.[Footnote 17] 

For offshore oil in the Gulf of Mexico, we found that our implicit 
sales prices fell outside of a wide range of prevailing market prices 
3.9 percent of the time during fiscal years 2006 and 2007. We used a 
range of market prices each month for comparison, the low price being 
the lowest daily spot price that month for Mars oil--a low quality, low 
value oil produced in the offshore Gulf--and the high price being the 
highest daily spot price for light Louisiana sweet (LLS)--a high 
quality, high value oil. The average difference between these prices 
was about $16 per barrel of oil during the October 2005 through 
September 2007 period we evaluated. We believe that this is a 
conservative approach because the two prices are among the lowest and 
highest prices that we found in the Gulf of Mexico. Therefore, while 
there may be cases in which prices fall outside of this range for 
legitimate reasons, we would expect this to be a rare occurrence. 
Conversely, prices that fall within this range are reasonable but not 
necessarily correct. This price range is illustrated in figure 3. 

Figure 3: Range of Reasonable Oil Prices in the Offshore Gulf of Mexico 
Based on Highest and Lowest Daily Spot Prices for Each Month: 

[Refer to PDF for image: multiple line graph] 

Date: October 2005; 
LLS spot price per barrel: $68; 
Mars spot price per barrel: $53. 

Date: November 2005; 
LLS spot price per barrel: $63; 
Mars spot price per barrel: $48. 

Date: December 2005; 
LLS spot price per barrel: $62; 
Mars spot price per barrel: $49. 

Date: January 2006; 
LLS spot price per barrel: $69; 
Mars spot price per barrel: $56. 

Date: February 2006; 
LLS spot price per barrel: $68; 
Mars spot price per barrel: $49. 

Date: March 2006; 
LLS spot price per barrel: $69; 
Mars spot price per barrel: $52. 

Date: April 2006; 
LLS spot price per barrel: $76; 
Mars spot price per barrel: $59. 

Date: May 2006; 
LLS spot price per barrel: $77; 
Mars spot price per barrel: $61. 

Date: June 2006; 
LLS spot price per barrel: $76; 
Mars spot price per barrel: $61. 

Date: July 2006; 
LLS spot price per barrel: $80; 
Mars spot price per barrel: $66. 

Date: August 2006; 
LLS spot price per barrel: $81; 
Mars spot price per barrel: $61. 

Date: September 2006; 
LLS spot price per barrel: $71; 
Mars spot price per barrel: $51. 

Date: October 2006; 
LLS spot price per barrel: $62; 
Mars spot price per barrel: $49. 

Date: November 2006; 
LLS spot price per barrel: $67; 
Mars spot price per barrel: $50. 

Date: December 2006; 
LLS spot price per barrel: $68; 
Mars spot price per barrel: $52. 

Date: January 2007; 
LLS spot price per barrel: $61; 
Mars spot price per barrel: $44. 

Date: February 2007; 
LLS spot price per barrel: $65; 
Mars spot price per barrel: $51. 

Date: March 2007; 
LLS spot price per barrel: $73; 
Mars spot price per barrel: $53. 

Date: April 2007; 
LLS spot price per barrel: $74; 
Mars spot price per barrel: $59. 

Date: May 2007; 
LLS spot price per barrel: $73; 
Mars spot price per barrel: $57. 

Date: June 2007; 
LLS spot price per barrel: $77; 
Mars spot price per barrel: $61. 

Date: July 2007; 
LLS spot price per barrel: $82; 
Mars spot price per barrel: $67. 

Date: August 2007; 
LLS spot price per barrel: $79; 
Mars spot price per barrel: $63. 

Date: September 2007; 
LLS spot price per barrel: $85; 
Mars spot price per barrel: $69. 

Source: GAO analysis of MMS data. 

[End of figure] 

In addition to possible errors in reported sales values or sales 
volumes, MMS officials said that low oil prices may reflect poor 
marketing, sales of low quantities of poor quality oil that settle in 
storage tanks, or sales of oil at offshore platforms where the sales 
price may be discounted for transportation. MMS officials also said 
that royalty payors may also be netting the cost of transportation from 
their sales value, which is against MMS regulations. On the other hand, 
high oil prices may reflect good marketing. Figure 4 depicts the 
percentage of our calculated oil prices that appeared erroneous and 
distinguishes between when the prices fell below or above the expected 
range. 

Figure 4: Sales Prices for Oil from Federal Leases in the Offshore Gulf 
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007: 

[Refer to PDF for image: stacked vertical bar graph] 

Percentage appearing erroneous: 

Date: October 2005; 
Percentage below reasonable range: 2.19%; 
Percentage above reasonable range: 0.66%. 

Date: November 2005; 
Percentage below reasonable range: 1.66%; 
Percentage above reasonable range: 2.45%. 

Date: December 2005; 
Percentage below reasonable range: 2.37%; 
Percentage above reasonable range: 0.9%. 

Date: January 2006; 
Percentage below reasonable range: 5.88%; 
Percentage above reasonable range: 0.16%. 

Date: February 2006; 
Percentage below reasonable range: 1.44%; 
Percentage above reasonable range: 0.64%. 

Date: March 2006; 
Percentage below reasonable range: 2.69%; 
Percentage above reasonable range: 0.4%. 

Date: April 2006; 
Percentage below reasonable range: 3.86%; 
Percentage above reasonable range: 0.36%. 

Date: May 2006; 
Percentage below reasonable range: 2.72%; 
Percentage above reasonable range: 0.14%. 

Date: June 2006; 
Percentage below reasonable range: 2.21%; 
Percentage above reasonable range: 0.43%. 

Date: July 2006; 
Percentage below reasonable range: 4.52%; 
Percentage above reasonable range: 0.13%. 

Date: August 2006; 
Percentage below reasonable range: 1.72%; 
Percentage above reasonable range: 0. 

Date: September 2006; 
Percentage below reasonable range: 0.9%; 
Percentage above reasonable range: 6.03%. 

Date: October 2006; 
Percentage below reasonable range: 2.06%; 
Percentage above reasonable range: 6.97%. 

Date: November 2006; 
Percentage below reasonable range: 2.75%; 
Percentage above reasonable range: 0.59%. 

Date: December 2006; 
Percentage below reasonable range: 2.39%; 
Percentage above reasonable range: 0.4%. 

Date: January 2007; 
Percentage below reasonable range: 1.58%; 
Percentage above reasonable range: 7.05%. 

Date: February 2007; 
Percentage below reasonable range: 2.38%; 
Percentage above reasonable range: 0.2%. 

Date: March 2007; 
Percentage below reasonable range: 2.8%; 
Percentage above reasonable range: 0.06%. 

Date: April 2007; 
Percentage below reasonable range: 5.29%; 
Percentage above reasonable range: 0.13%. 

Date: May 2007; 
Percentage below reasonable range: 2.81%; 
Percentage above reasonable range: 0.19%. 

Date: June 2007; 
Percentage below reasonable range: 2.96%; 
Percentage above reasonable range: 0.19%. 

Date: July 2007; 
Percentage below reasonable range: 3.33%; 
Percentage above reasonable range: 0.38%. 

Date: August 2007; 
Percentage below reasonable range: 1.34%; 
Percentage above reasonable range: 0.32. 

Date: September 2007; 
Percentage below reasonable range: 2.28%; 
Percentage above reasonable range: 0.72%. 

Source: GAO analysis of MMS data. 

[End of figure] 

For gas produced offshore in the Gulf of Mexico, we found that our 
calculated implicit sales prices fell outside of the range of 
prevailing market prices 6.6 percent of the time. We used a range of 
market prices at the Henry Hub--a major gas trading center in the Gulf 
of Mexico--each month for comparison. To establish a low and a high 
price, we examined three specific prices each month and chose the 
highest and the lowest price from among the three. These three prices 
are the maximum mid-day spot price during that month, the minimum mid- 
day spot price during that month, and the First of the Month price. 
[Footnote 18] All three prices are common prices upon which producers 
sell their gas in the Gulf of Mexico, according to MMS, and we believe 
this is a conservative approach. The average difference between the 
highest and the lowest prices was about $3 per MMBtu during the period 
October 2005 through September 2007. These prices are illustrated in 
figure 5. 

Figure 5: Range of Reasonable Gas Prices in the Gulf of Mexico Based on 
Highest and Lowest Daily Spot Prices for Each Month and the First of 
the Month Price at the Henry Hub (Dollars per MMBtu): 

[Refer to PDF for image: multiple line graph] 

Date: October 2005; 
Highest gas price: $15; 
Lowest gas price: $12. 

Date: November 2005; 
Highest gas price: $14; 
Lowest gas price: $8. 

Date: December 2005; 
Highest gas price: $16; 
Lowest gas price: $9. 

Date: January 2006; 
Highest gas price: $12; 
Lowest gas price: $7. 

Date: February 2006; 
Highest gas price: $9; 
Lowest gas price: $6. 

Date: March 2006; 
Highest gas price: $8; 
Lowest gas price: $6. 

Date: April 2006; 
Highest gas price: $8; 
Lowest gas price: $6. 

Date: May 2006; 
Highest gas price: $8; 
Lowest gas price: $5. 

Date: June 2006; 
Highest gas price: $8; 
Lowest gas price: $5. 

Date: July 2006; 
Highest gas price: $8; 
Lowest gas price: $5. 

Date: August 2006; 
Highest gas price: $9; 
Lowest gas price: $6. 

Date: September 2006; 
Highest gas price: $7; 
Lowest gas price: $4. 

Date: October 2006; 
Highest gas price: $8; 
Lowest gas price: $3. 

Date: November 2006; 
Highest gas price: $8; 
Lowest gas price: $6. 

Date: December 2006; 
Highest gas price: $9; 
Lowest gas price: $5. 

Date: January 2007; 
Highest gas price: $8; 
Lowest gas price: $5. 

Date: February 2007; 
Highest gas price: $10; 
Lowest gas price: $6. 

Date: March 2007; 
Highest gas price: $8; 
Lowest gas price: $6. 

Date: April 2007; 
Highest gas price: $8; 
Lowest gas price: $7. 

Date: May 2007; 
Highest gas price: $8; 
Lowest gas price: $7. 

Date: June 2007; 
Highest gas price: $8; 
Lowest gas price: $6. 

Date: July 2007; 
Highest gas price: $7; 
Lowest gas price: $5. 

Date: August 2007; 
Highest gas price: $8; 
Lowest gas price: $5. 

Date: September 2007; 
Highest gas price: $7; 
Lowest gas price: $5. 

Source: GAO analysis of MMS data. 

[End of figure] 

As with oil prices, being outside of the range does not necessarily 
mean that the price is erroneous, but we would not expect this to be a 
common occurrence. Conversely, being within this range means that the 
sales price is reasonable but not necessarily correct. In addition to 
possible errors in reported sales values or sales volumes, MMS 
officials said that low or high prices can reflect marketing efforts. 
Quality does not affect calculated prices because gas quality is 
standardized by reporting sales prices per MMBtu. The percentage that 
our calculated gas prices appeared erroneous is depicted in figure 6, 
distinguishing between implicit prices that fell below and above the 
expected range. 

Figure 6: Sales Prices for Gas from Federal Leases in the Offshore Gulf 
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007: 

[Refer to PDF for image: stacked vertical bar graph] 

Percentage appearing erroneous: 

Date: October 2005; 
Percentage below reasonable range: 16.8%; 
Percentage above reasonable range: 2.5%. 

Date: November 2005; 
Percentage below reasonable range: 6%; 
Percentage above reasonable range: 7.9%. 

Date: December 2005; 
Percentage below reasonable range: 6%; 
Percentage above reasonable range: 1.3%. 

Date: January 2006; 
Percentage below reasonable range: 3%; 
Percentage above reasonable range: 2%. 

Date: February 2006; 
Percentage below reasonable range: 0.9%; 
Percentage above reasonable range: 3.1%. 

Date: March 2006; 
Percentage below reasonable range: 3%; 
Percentage above reasonable range: 2.6%. 

Date: April 2006; 
Percentage below reasonable range: 2.7%; 
Percentage above reasonable range: 2.5%. 

Date: May 2006; 
Percentage below reasonable range: 0.9%; 
Percentage above reasonable range: 2%. 

Date: June 2006; 
Percentage below reasonable range: 1.8%; 
Percentage above reasonable range: 1%. 

Date: July 2006; 
Percentage below reasonable range: 2.3%; 
Percentage above reasonable range: 1.2%. 

Date: August 2006; 
Percentage below reasonable range: 2.8%; 
Percentage above reasonable range: 1.8%. 

Date: September 2006; 
Percentage below reasonable range: 1.5%; 
Percentage above reasonable range: 8.3%. 

Date: October 2006; 
Percentage below reasonable range: 1.2%; 
Percentage above reasonable range: 2.2%. 

Date: November 2006; 
Percentage below reasonable range: 3.4%; 
Percentage above reasonable range: 3.2%. 

Date: December 2006; 
Percentage below reasonable range: 1.9%; 
Percentage above reasonable range: 1.5%. 

Date: January 2007; 
Percentage below reasonable range: 2.3%; 
Percentage above reasonable range: 1.5%. 

Date: February 2007; 
Percentage below reasonable range: 1.3%; 
Percentage above reasonable range: 1.2%. 

Date: March 2007; 
Percentage below reasonable range: 2.8%; 
Percentage above reasonable range: 3.5%. 

Date: April 2007; 
Percentage below reasonable range: 7.9%; 
Percentage above reasonable range: 4.7%. 

Date: May 2007; 
Percentage below reasonable range: 4.4%; 
Percentage above reasonable range: 4.4%. 

Date: June 2007; 
Percentage below reasonable range: 1.8%; 
Percentage above reasonable range: 5.5%. 

Date: July 2007; 
Percentage below reasonable range: 2.3%; 
Percentage above reasonable range: 10.6%. 

Date: August 2007; 
Percentage below reasonable range: 2.3%; 
Percentage above reasonable range: 1.2. 

Date: September 2007; 
Percentage below reasonable range: 5.7%; 
Percentage above reasonable range: 2.9%. 

Source: GAO analysis of MMS data. 

[End of figure] 

Multiple Factors Affect Oil and Gas Companies' Abilities to Accurately 
Report Royalties Owed to the Federal Government: 

Oil and gas company representatives reported that several factors can 
affect their ability to accurately report royalty data, including 
complex land ownership patterns, unit agreements, ambiguity in federal 
regulations, short time frames for filing royalty reports, and 
inaccuracies in MMS's internal databases. 

Complexity of Ownership Can Make Accurate Reporting of Oil and Gas 
Royalties More Difficult: 

The complexity of unit agreements (units) can impact the accuracy of 
royalty data. Upon the request of companies, BLM and MMS can 
administratively combine contiguous leases into units to more 
efficiently explore and develop an oil or gas reservoir and to lessen 
the surface disruption caused by the building of roads and the 
installation of pipelines and production equipment. MMS requires payors 
to report royalties for each producing lease and, if a lease is 
assigned to a unit, to provide information identifying the unit in the 
agreement data field. If a lease does not belong to a unit, the 
agreement data field should be left blank. However, companies can fail 
to complete the agreement data field when a lease belongs to a unit, 
which raises questions about whether the royalties paid were for 
production belonging to a unit or for production outside of a unit. 
This complicates the auditing of the royalty data. Figure 7 shows how 
federal leases can be combined into a federal unit to explore for oil 
and gas, and figure 8 illustrate the complexity of auditing these 
leases when a payor fails to complete the agreement field. 

Figure 7: Block Diagram Illustrating the Hypothetical Creation of a 
Federal Unit: 

[Refer to PDF for image: illustration] 

Indicated on the illustration are the following entities: 

Sandstone; 
Limestone; 
Salt; 
Shale; 
Lease number; 
Lease boundary; 
Boundary of unit A; 
Boundary of unit B; 
Oil reservoir; 
Producing oil well. 

Scenario A: 

The most straightforward example of paying royalties occurs when 
Company X, which owns lease 1004, drills well #1 and discovers oil in 
the shallow sandstone, as illustrated in scenario A. Company X submits 
one royalty report for lease 1004 and does not complete the agreement 
data field since the lease is not part of an agreement. Auditors have 
no difficulty in auditing this lease because there is only one 
producing zone, the shallow sandstone. 

Scenario B: 

This simple example can become more complex over time, such as the 
creation of a federal unit as illustrated in scenario B. Based on a 
seismic survey, Company Y wants to develop what it believes is an oil 
reservoir in the limestone on the leases it owns, leases 1001 and 1002. 
Because it believes the reservoir also extends below leases 1003 and 
1004, it approaches the owner of lease 1003, Company Z, and the owner 
of lease 1004, Company X, to form an agreement combining all four 
leases into Unit A, to share the risk and expenses of drilling and any 
profits from the sale of oil. Companies X and Z agree to do so but 
restrict the unit to production from the limestone. Company Y drills 
well 2 on lease 1002 and finds oil in the limestone, and proceeds from 
the sale of this oil is shared among the three companies. Each of the 
companies reports their respective royalties on lease 1002 to MMS 
separately, and all forget to complete the agreement field, which is 
required by MMS regulations. Auditors have little difficultly in 
auditing these royalty data because there is only one producing zone on 
the lease. 

Source: GAO. 

[End of figure] 

Figure 8: Block Diagram Illustrating a Hypothetical Complex 
Relationship between Unit Agreements and Potential Impacts on 
Oversight: 

[Refer to PDF for image: illustration] 

Indicated on the illustration are the following entities: 

Sandstone; 
Limestone; 
Salt; 
Shale; 
Lease number; 
Lease boundary; 
Boundary of unit A; 
Boundary of unit B; 
Oil reservoir; 
Producing oil well. 

Scenario C: 

Paying royalties becomes much more complicated when the boundaries of 
units overlap as illustrated in scenario C. In this scenario, Company X 
wants to develop what it believes is an oil reservoir in the deep 
sandstone below its lease 1004 and Company Z’s lease 1003. It 
approaches Company Z, which agrees to combine the two leases into Unit 
B to explore and develop the deep sandstone. Company X drills well #3 
on lease 1004 and finds oil in both the deep sandstone and the 
limestone. Proceeds from the sale of the oil from the deep sandstone is 
shared among Companies X, and Z, but proceeds from the sale of oil from 
the limestone must be shared among the three companies participating in 
Unit A, according to the agreement. Each of the three companies reports 
their royalties for lease 1004 to MMS individually, and each provides 
royalty data for oil sold from the limestone and royalty data for oil 
sold from the deep sandstone, according to MMS guidance, but all fail 
to complete the agreement field. As a result, auditors have some 
difficulty differentiating the production data from Unit A and Unit B. 
In addition to reporting production data from Units A and B, Company X 
must report data for production from the shallow sandstone from the 
well located on its lease. Since company X has not populated the 
agreement field on any of its reports, auditors have great difficulty 
sorting out which production belongs to which of the three zones from 
which Company X is producing. State and tribal auditors reported that 
overlapping units involving onshore leases are common. In our work, we 
observed leases in the Gulf of Mexico that belonged to many units. 

Source: GAO. 

[End of figure] 

Complex ownership patterns of federal leases, particularly those issued 
by BLM for onshore lands, may also further impact the accuracy of 
royalty data, according to several oil and gas company representatives. 
For example, when there are intermingled federal, state, and private 
leases, royalty reporting can be challenging because companies said 
that they may need to rely on multiple operators to provide royalty 
information, which is not always consistent and clear, and because 
different regulations and rules apply to federal, state, and private 
leases. Confusion can sometimes cause the first royalty payment to MMS 
to be delayed. 

Industry Representatives Stated That Ambiguous Federal Regulations Can 
Create Difficulty in Establishing Gas Prices: 

Representatives from four companies reported that the ambiguity in 
extensive federal regulations that establish prices for oil and gas 
lead to difficulty in interpretation and hence, calculating the correct 
royalty payment. Nine of the 11 state and tribal auditors that we 
interviewed told us that the gas valuation regulations published in 
1988 are out of date and that the series of benchmarks within these 
regulations that prescribe prices for gas are impractical to apply. 
Concerning the gas regulations, the RPC report noted the difficulty of 
applying these benchmarks and recommended that MMS consider using 
market indices to establish gas prices when companies sell to their 
affiliates in lieu of the 1988 benchmarks.[Footnote 19] RPC also 
recommended that MMS more clearly define allowable transportation and 
processing deductions for natural gas in their regulations. 

Royalty Reports May Be Due before Payors Have All the Necessary Data to 
Accurately Complete These Reports, Which Necessitates Later 
Adjustments: 

In addition, three companies reported difficulty in paying royalties on 
gas production in a timely manner because they do not receive data from 
their gas purchasers in time to meet MMS's deadline for filing royalty 
reports and must submit estimates and later correct them. For example, 
a purchaser of oil and gas may report an adjustment to the volume of 
the gas purchased or the quality of the oil purchased after the payors 
are required to report, resulting in the payor having to make a 
correction to the original data. Reporting on gas is especially 
challenging, because gas transportation and processing are usually not 
reconciled within 30 days. However, payors are required to report 
royalties to MMS on or before the last day of the month following the 
month the product was sold or removed from the lease. Therefore, to 
stay in compliance with reporting requirements and avoid penalties, 
some company representatives reported that they file estimated gas 
royalty reports and keep funds deposited with MMS to cover variances in 
royalties due. This is not problematic as long as companies correct 
their original data as necessary and pay the correct amount of 
royalties. 

Royalty Reports on New Leases Are Rejected by MMS's System When BLM 
Does Not Provide the Lease Information to MMS in a Timely Manner: 

Oil and gas company representatives stated that BLM data on new leases 
and units is not always incorporated into MMS's system in a timely 
manner, resulting in edit checks rejecting correct payor data. Two of 
these representatives reported that BLM's delays in revisions to data 
on participating areas--the part of a unit for which participating 
companies have agreed to a manner for allocating production--can cause 
them to go back and adjust MMS royalty data that is over a year old. 
[Footnote 20] This lack of coordination between BLM and MMS was also 
addressed in the December 2007 RPC report, which found that incorrect 
data leads to errors in royalty receipts and revenue distribution, 
requiring MMS staff to correct the information and redistribute the 
revenue. The RPC report recommended that BLM and MMS improve data 
exchanges by establishing a coordinating committee with representatives 
from senior management levels, which would be charged with defining 
common data standards and developing solutions for technical issues of 
coordination and information sharing at MMS and BLM. MMS is addressing 
this issue. 

Oil and Gas Company Representatives Generally Understand Key Data 
Fields, but Better Clarification of Certain Codes Could Improve the 
Accuracy of Payor Reports: 

While oil and gas company representatives with whom we spoke reported 
that they generally have little difficulty understanding key data 
required to complete the Form MMS-2014, most state auditors with whom 
we spoke identified some problems with company submitted data. All 10 
of the representatives we contacted explained that the major data 
fields, such as the sales value, sales volume, and royalty value, are 
easy to understand and complete. Eight of the representatives added 
that major royalty reporting codes, such as those that define product 
types and that provide more information on the nature of the sale of 
oil and gas, are also easy to understand. Only, two representatives 
reported some difficulty with using certain codes. However, 8 of the 11 
state and tribal royalty auditors that we contacted identified a 
specific product code that creates difficulty for oil and gas companies 
in reporting royalties. Specifically, state auditors told us that 
product code 39 for coalbed methane is inconsistently used by payors 
reporting royalties, creating difficulty in auditing leases. During our 
analysis of MMS's royalty data, we also noted that some companies claim 
a processing allowance for coalbed methane, which is not processed, 
possibly indicating confusion on use of this code. Additionally, these 
auditors told us that a certain code used to explain adjustments, known 
as adjustment reason code 10, is commonly used by royalty payors for 
all types of adjustments. They said that not having specific adjustment 
reason codes for volume adjustments, price changes, royalty 
adjustments, processing allowance adjustments, and transportation 
allowance adjustments, makes it difficult for auditors to clearly 
determine why a royalty payment was adjusted. 

Conclusions: 

Royalties paid to the federal government for the extraction of oil and 
natural gas from federal lands and waters remain both a large source of 
revenue to the federal government and a key element in the discussion 
on how to balance the use of these lands. Our past work has 
consistently raised questions about how MMS oversees the collection of 
these royalties and ensures that the country receives fair value for 
the resources removed. 

MMS has ongoing efforts to improve the reasonableness and accuracy of 
its royalty data. However, the agency still has more to do to ensure 
that key data used to report, pay, and audit federal royalties are 
accurate. In our view, MMS still lacks some effective controls to (1) 
prevent erroneous data on allowances from being accepted into the 
system, (2) detect errors in data once they are accepted into the 
system, and (3) ensure that key data needed for complex oil and gas 
units are consistently provided, and this can make the auditing and 
other compliance work done by MMS staff more difficult and could result 
in the federal government not receiving all the royalties it is due. In 
particular, our detailed examination of a portion of key fiscal year 
2006 and 2007 data has identified missing data, significant errors, and 
questionable data, raising doubts about the 97 percent accuracy level 
that MMS reports. In light of our findings, it seems unlikely that MMS 
could sustain its goal of 98 percent data accuracy without taking 
additional steps. 

Recommendations for Executive Action: 

To improve the accuracy of royalty data and to help provide a greater 
assurance that federal oil and gas royalties are being accurately 
reported, to improve the efficiency of audit and compliance activities, 
and to increase the likelihood of collecting additional royalties in a 
timely manner, we are recommending that the Secretary of the Interior 
direct MMS to take five actions. 

To better prevent the submission of erroneous data into MMS's database, 
we are recommending that MMS: 

* share with payors that submit their data through the Electronic Data 
Interchange (EDI) MMS's recent edit check that prevents payors from 
submitting data claiming processing allowances for gas that is not 
processed, including coalbed methane. 

To improve the quality of data that has been accepted by MMS's 
database, we are recommending that MMS: 

* design and implement additional edit checks to evaluate the net 
impact of all adjustments on original entries for critical royalty 
variables, including sales values, royalty values, sales volumes, 
transportation allowances, and processing allowances, by summing each 
month all entries for the variable submitted by each payor for each 
lease and each commodity and highlight potentially erroneous 
submissions to payors and appropriate MMS staff and: 

* use the monthly sums of original and adjusting entries for royalty 
values, sales values, and sales volumes to ensure that calculated 
royalty rates and unit prices for each payor on each lease for each 
commodity fall within expected ranges and highlight potentially 
erroneous submissions to payors and appropriate MMS staff. 

To simplify the auditing of leases and compliance work, we are 
recommending that MMS: 

* enforce current MMS requirements to populate the agreement field with 
the correct agreement number and to populate the agreement field for 
leases outside of agreements with a single unique code that is easily 
identifiable, and: 

* collaborate with state and tribal auditors on the possibility of 
adding more specific adjustment reason codes that describe why payors 
made corrections to royalty data on the Form MMS-2014. 

Agency Comments and Our Evaluation: 

We provided a draft of this report to Interior for review and comment. 
Interior provided written comments, which are presented in appendix II. 
In general, Interior agreed with our findings, concurring with four of 
our five recommendations and partially concurring with the other 
recommendation. With regard to this latter recommendation, which 
involves populating the agreement field, Interior agreed with us that 
it is important that MMS improve the enforcement of requirements for 
populating the agreement field. However, Interior was uncertain about 
how best to achieve this goal and stated that MMS is evaluating the 
best methods to ensure accurate reporting for agreements. 

As agreed with your offices, unless you publicly announce the contents 
of this report earlier, we plan no further distribution until 30 days 
from the report date. At that time, we will send copies of this report 
to appropriate congressional committees, the Secretary of the Interior, 
the Director of MMS, and other interested parties. In addition, the 
report will be available at no charge on GAO's Web site at [hyperlink, 
http://www.gao.gov]. 

If you or your staffs have any questions about this report, please 
contact me at (202) 512-3841 or ruscof@gao.gov. Contact points for our 
Offices of Congressional Relations and Public Affairs may be found on 
the last page of this report. Key contributors to this report are 
listed in appendix III. 

Signed by: 

Frank Rusco:
Director, Natural Resources and Environment: 

[End of section] 

Appendix I: Scope and Methodology: 

To examine MMS's key efforts to improve the accuracy of royalty data, 
we reviewed and discussed with MMS officials their action plans to 
implement RPC recommendations, reviewed a demonstration of MMS's 
Compliance Program Tool (CPT), discussed their implementation of the 
CPT to systematically identify misreported volumes and missing royalty 
reports, reviewed their plan to monitor adjustments, and discussed 
efforts to adopt additional edit checks. 

To assess the reasonableness and completeness of MMS's royalty data, we 
obtained from MMS an extract from their financial management system 
consisting of all oil and gas royalty records from fiscal years 2006 
and 2007 and assessed the completeness and reasonableness of key data 
fields based on extensive data reliability studies documented in two 
previous GAO reports.[Footnote 21] We removed records related to rental 
payments, gas storage agreements, taxes, contract settlements, and 
geothermal operations by using transaction codes, and removed sulfur, 
helium, nitrogen, and carbon dioxide, using product codes. We also 
limited our analysis to cash royalty payments, excluding royalty-in- 
kind (RIK) payments whenever possible or appropriate. Our resulting 
analysis file consisted of about 4.1 million royalty records. 

First, we assessed the completeness of MMS's data. We developed a 
frequency distribution of the number of records per month and compared 
these frequencies from month-to-month, looking for abnormal patterns. 
We discovered that there were about half as many records for April 2007 
as for other months on average. At our request, MMS investigated the 
reason and discovered that the contractor who extracted the data 
inadvertently excluded records accepted by MMS's system in June 2007-- 
the month in which much of the data from April 2007 would have been 
submitted and accepted. We then obtained from MMS a new file of records 
accepted in June 2007 and combined the new data with the rest of the 
royalty data, and rechecked the monthly totals. This procedure revealed 
a fairly consistent number of records and leases on a month-to-month 
basis. We determined that the data we received from MMS were a complete 
representation of what was in their data system through our study date 
and was therefore reliable enough to allow us to use the extract in our 
more detailed review of royalty data. This monthly consistency is 
illustrated in figure 9. 

Figure 9: Numbers of Oil and Gas Royalty Records and Leases Reported 
per Month for Fiscal Years 2006 and 2007: 

[Refer to PDF for image: multiple line graph] 

Date: October 2005; 
Number of Records: 189,880; 
Number of Leases: 21,811. 

Date: November 2005; 
Number of Records: 191,395; 
Number of Leases: 22,390. 

Date: December 2005; 
Number of Records: 183,936; 
Number of Leases: 22,291. 

Date: January 2006; 
Number of Records: 188,488; 
Number of Leases: 22,462. 

Date: February 2006; 
Number of Records: 192,930; 
Number of Leases: 22,312. 

Date: March 2006; 
Number of Records: 189,561; 
Number of Leases: 22,399. 

Date: April 2006; 
Number of Records: 184,503; 
Number of Leases: 22,325. 

Date: May 2006; 
Number of Records: 175,147; 
Number of Leases: 22,731. 

Date: June 2006; 
Number of Records: 171,641; 
Number of Leases: 22,840. 

Date: July 2006; 
Number of Records: 177,064; 
Number of Leases: 22,939. 

Date: August 2006; 
Number of Records: 173,084; 
Number of Leases: 22,945. 

Date: September 2006; 
Number of Records: 164,749; 
Number of Leases: 22,981. 

Date: October 2006; 
Number of Records: 166,901; 
Number of Leases: 22,647. 

Date: November 2006; 
Number of Records: 168,325; 
Number of Leases: 22,900. 

Date: December 2006; 
Number of Records: 176,174; 
Number of Leases: 22,962. 

Date: January 2007; 
Number of Records: 189,830; 
Number of Leases: 22,928. 

Date: February 2007; 
Number of Records: 159,642; 
Number of Leases: 22,787. 

Date: March 2007; 
Number of Records: 160,375; 
Number of Leases: 23,064. 

Date: April 2007; 
Number of Records: 163,465; 
Number of Leases: 22,764. 

Date: May 2007; 
Number of Records: 153,948; 
Number of Leases: 23,203. 

Date: June 2007; 
Number of Records: 152,484; 
Number of Leases: 22,897. 

Date: July 2007; 
Number of Records: 149,203; 
Number of Leases: 23,048. 

Date: August 2007; 
Number of Records: 136,109; 
Number of Leases: 22,647. 

Date: September 2007; 
Number of Records: 126,943; 
Number of Leases: 22,519. 

Source: GAO analysis of MMS data. 

[End of figure] 

To examine the completeness of records in more detail, we analyzed a 
subset of MMS's royalty data--leases that produced natural gas in the 
offshore Gulf of Mexico. We chose this subset because of: (1) its 
relatively manageable size--about 2,100 leases out of a total of about 
29,000 producing federal and Indian oil and gas leases and (2) its 
financial significance--the gas royalties from Gulf of Mexico leases in 
fiscal year 2008 account for almost 30 percent of total federal and 
Indian oil and gas royalty revenues.[Footnote 22] For each lease, we 
compared gas volumes reportedly sold by payors on Form MMS-2014 to gas 
volumes reportedly produced by operators on MMS's OGOR. Specifically, 
for each lease we added together all sales volumes on the Form MMS-2014 
of processed and unprocessed gas in thousands of cubic feet for each 
month from January 2006 to September 2007 and compared these to gas 
volumes disposed of on the OGOR-B for the same month. From the Form MMS-
2014, we included volumes for cash sales (transaction code 01), royalty-
in-kind sales (transaction codes 06 and 08), and non-royalty bearing 
sales under provisions for deepwater royalty relief (transaction code 
41). We excluded from our analysis October through December 2005 
because major hurricanes disrupted production in the Gulf of Mexico, 
resulting in many production facilities being shut down. We also used 
data from MMS's Technical Information Management System (TIMS) to 
identify all leases that belonged to unit agreements and excluded these 
leases in order to simplify the analysis. This resulted in about 1,500 
producing gas leases. Also, a significant number of these leases had 
royalty reports but no production reports, but missing production 
reports were more prevalent for the last 3 months of fiscal year 2007, 
possibly indicating that these reports had not yet been received or 
accepted by MMS's system. 

To investigate the completeness of individual royalty records, we 
examined key royalty data fields to ensure that they were populated. 
These data fields are necessary to match royalty payments to the proper 
payor, lease, sales month, and product code. Fields included payor 
number, lease number, sales date, and transaction code. We also checked 
that product code and sales type were populated. Because nearly 100 
percent of these critical data fields were populated, we discontinued 
additional tests on assessing the completeness of individual data 
fields. However, we examined certain data fields to ensure that they 
were not populated when they should not be. These fields included sales 
value and sales volume for certain transaction codes, including minimum 
royalty due (transaction code 02), estimated royalty payment 
(transaction code 03), transportation allowance (transaction code 11), 
processing allowance (transaction code 15), and quality bank adjustment 
(transaction code 13). Population of these data fields could result in 
counting sales values and sales volumes twice. 

We then developed tests to investigate the gross reasonableness of 
certain data fields that our past work highlighted as being 
problematic, including royalty value, sales value, sales volume, 
transportation allowance, and processing allowance. We identified 
royalty-in-kind transactions from transaction codes (06 and 08) and 
excluded them from this analysis. We employed a technique that is 
different from MMS's edit checks, which generally examine only 
individual royalty lines. We summed the data fields on all royalty 
records for each month on each lease for each royalty payor and product 
code. This technique aggregated the original royalty record with all 
subsequent adjustments, allowing us to examine the net effect and 
easily identify negative sums for royalty values, sales values, or 
sales volumes, which MMS's edit checks of individual lines cannot 
identify. Since payors generally submit one electronic fund transfer 
for all the leases upon which they owe royalties for a given month, a 
negative sum can go undetected if submitted along with many other 
positive sums. Although we found a relatively small percentage (less 
than or equal to 0.2 percent) of negative sums, we examined the 
corresponding royalty lines to determine if their financial impact was 
significant. 

We used the same technique of summing royalty records to examine the 
gross reasonableness of transportation and processing allowances. Being 
deductions, these allowances should be negative. We found that 
transportation allowances and processing allowances were positive 3.8 
percent and 10.1 percent of the time, respectively. However when we 
examined individual royalty records, we discovered that many of these 
records were associated with royalty-in-kind transactions, and 
therefore outside of the scope of our analysis. MMS, who creates the 
royalty-in-kind data, did not properly identify these RIK leases with 
the designated royalty-in-kind transaction codes (06 and 08), but 
instead used the codes for transportation (11) and processing (15) 
allowances. An MMS official with the RIK program explained that, due to 
constraints in their RIK system, some transportation and processing 
allowances could be positive due to their RIK system having populated 
the transportation and processing data fields for the current month 
with changes to prior months reported by pipelines and processing 
plants. This official also said that the RIK system included all 
revenues and expenses associated with natural gas liquids from the RIK 
leases in the processing allowances. These processes for RIK leases are 
inconsistent with processes for leases on which royalties are paid in 
cash. For cash royalties, adjustments to previous periods are posted to 
the specific sales month, not the current month. Also for cash 
royalties, revenue is identified as sales value, and allowable 
expenses, such as transportation or processing allowances, are 
individually identified as transportation or processing allowances for 
the appropriate product code. The MMS official said that they corrected 
this system problem in July 2007. We were then able to identify the RIK 
leases through their payor codes, which are alphanumeric as opposed to 
the numeric payor codes of cash royalty payments, and subsequently 
removed them. We also checked for transportation and processing 
allowances being taken in excess of the maximum amounts allowed by 
federal regulations and checked to see if transportation and processing 
allowances were taken for transaction codes for which they are not 
permitted, such as minimum royalties (transaction code 2), estimated 
royalty payments (transaction code 3), quality banks (transaction code 
13), and offshore deep water royalty relief (transaction code 
41).[Footnote 23] Lastly, we examined royalty data to see if payors 
reported processing allowances for products that are not processed, 
such as oil, condensate, unprocessed gas, and coalbed methane. 

We then investigated the reasonableness and accuracy of royalty values, 
sales values, and sales volumes in more detail because these royalty 
data fields appeared to be problematic in our previous work.[Footnote 
24] Using the same method of summing these data fields each month for 
all royalty records for each payor for each lease and each product, we 
calculated the royalty rates by dividing royalty value prior to 
allowances by sales value. We then compared our calculated royalty 
rates to expected royalty rates based on general lease terms because we 
did not have access to individual lease terms for the estimated 29,000 
producing federal and Indian leases. For offshore leases (product codes 
01, 02, 03, 04, and 07), we used royalty rates of 12.5 percent and 
16.67 percent for comparison.[Footnote 25] We identified the lease 
numbers associated with royalty rates outside of expected values and 
compared the calculated royalty rates of these 331 leases to royalty 
rates for these leases in the TIMS database. Sixteen of these leases 
had royalty rates other than 12.5 or 16.67 percent, and we adjusted our 
analysis accordingly. For onshore federal gas production (product codes 
03, 04, and 07), we compared our calculated royalty rates to the same 
royalty rates as for offshore leases. For onshore federal oil 
production, we compared initially our calculated royalty rates to rates 
of 12.5 percent to 25 percent.[Footnote 26] According to MMS, this 
latter interval included a number of prescribed royalty rates that were 
common for oil production from certain leases issued before 1988. 
However because of the large number of calculated onshore oil and gas 
royalty rates that fell outside of expected values, we selected a 
sample of onshore leases for MMS to research. MMS reported that several 
leases had royalty rates that were either 5 percent or 10 percent-- 
rates that they identified as common for certain older leases. We 
adjusted our onshore comparison to include these two rates as 
acceptable. Because few other leases had royalty rates that were 
uncommon, we did not ask MMS to research additional onshore leases. For 
Indian leases, we similarly calculated royalty rates and determined 
that few leases had royalty rates of less than 12.5 percent, so we did 
not pursue comparing these to actual lease terms. 

We further investigated the reasonableness and accuracy of royalty 
values, sales values, and sales volumes by calculating unit oil and gas 
sales prices with Gulf of Mexico monthly data submitted by royalty 
payors for each lease. We limited our analysis to the offshore Gulf of 
Mexico because this area has well developed transparent markets where 
regional prices are readily available, unlike onshore markets. To 
compare oil prices, we used a range of market prices each month for 
comparison, the low price being the lowest daily spot price that month 
for Mars oil (rounded down to the nearest dollar), and the high price 
being the highest daily spot price for light Louisiana sweet (rounded 
up to the nearest dollar). We investigated doing similar comparisons 
onshore but discovered that the price range onshore, with West Texas 
Intermediate among the highest priced oil we found, and Wyoming 
asphaltic being about the lowest priced oil we found, created a range 
that was so wide that it made any comparison meaningless. To compare 
gas prices, we examined the maximum mid-day spot price, the minimum mid-
day spot price, and the First of the Month price at the Henry Hub and 
chose the highest and the lowest price from among the three (we rounded 
the lowest price down to the nearest dollar and rounded the highest 
price up to the nearest dollar). In calculating unit gas prices from 
MMS royalty data, we used volumes expressed per MMBtu to remove the 
effects of quality on price. As with oil prices, we investigated doing 
gas price comparisons onshore but found that exceptionally low gas 
prices at Opal, Wyoming created a range of prices that was so wide as 
to make any comparisons meaningless. 

To examine factors that affect oil and gas companies' abilities to 
accurately report royalties owed to the federal government, we 
interviewed a limited number of oil and gas company representatives. To 
solicit views on oil and gas companies' experiences with reporting 
royalty data to MMS, we used a nonprobability sample. To draw our 
sample, we identified the 20 oil and gas companies that submitted the 
highest number of royalty lines on Form MMS-2014 in fiscal years 2006 
and 2007 and contacted representatives from the top 15 to request 
information. The top 20 companies accounted for 63 percent of all the 
royalty lines reported, and the top 15 accounted for more than 56 
percent. In addition, we contacted the two largest national oil and gas 
industry associations--American Petroleum Institute (API) and the 
Independent Petroleum Association of the Mountain States (IPAMS)--to 
request information. IPAMS describes itself as a non-profit trade 
association representing more than 400 independent oil and natural gas 
producers, service and supply companies, banking and financial 
institutions, and industry consultants committed to environmentally 
responsible oil and natural gas development in the Intermountain West. 
API reports that it is the only national trade association that 
represents all aspects of America's oil and natural gas industry. API 
has 400 corporate members, from the largest major oil company to the 
smallest of independents. They include producers, refiners, suppliers, 
pipeline operators, and marine transporters, as well as service and 
supply companies that support all segments of the industry. 

For our semi-structured interview questions, we received a total of 10 
responses from oil and gas companies. Specifically, of the 15 companies 
with the most royalty lines, 2 responded to our request. From API 
members we received two responses, and from IPAMS members we received 
six responses. We personally met with two company representatives at 
the IPAMS office and discussed their written responses to our 
questions. Membership in these associations and being identified as 1 
of the 15 companies is not mutually exclusive. Results from this 
nonprobability sample cannot be used to make inferences about all oil 
and gas companies, because the companies that were not included in our 
list of the top royalty payors or members in the associations we 
contacted had no chance of being selected as part of the sample. 

[End of section] 

Appendix II: Comments from the Department of the Interior: 

United States Department of the Interior: 
Office Of The Secretary: 
Washington, DC 20240: 

June 30, 2009: 

Mr. Frank Rusco
Director, Natural Resources and Environment: 
Government Accountability Office: 
441 G Street, NW: 
Washington, D.C. 20548: 

Dear Mr. Rusco: 

Thank you for the opportunity to review and comment on the Government 
Accountability Office draft report entitled, Mineral Revenues: MMS 
Could Do More to Improve the Accuracy of Key Data Used to Collect and 
Verify Oil and Gas Royalties (GAO-09-549). 

We generally agree with your findings and concur with four of your five 
recommendations. We partially concur with Recommendation 4. Our 
responses to each recommendation are provided in the Enclosure. 

As noted in the draft report, the Minerals Management Service has 
several efforts underway to improve the accuracy of the payor-reported 
data used to collect and verify royalties. One key effort is the 
implementation of recommendations identified by the Royalty Policy 
Committee[Footnote 27] to improve edit checks, monitor the quality of 
natural gas, revise gas valuation regulations, and improve coordination 
with the Bureau of Land Management. The MMS is aggressively 
implementing the RPC recommendations and has already taken steps to 
improve the accuracy and completeness of royalty data. 

As GAO noted in the draft report, MMS subjects payor-reported royalty 
data to more than 140 edit checks and has incorporated up-front edits 
to prevent payors who report their royalties via the Web from 
submitting erroneous data. More recently, MMS has initiated a data 
mining effort as a second level screening process to increase the 
accuracy of payor-reported data before the data is subjected to 
compliance reviews and ultimately to audit. 

The diagram below illustrates MMS's overall data accuracy concept: 

Figure: MRM Data Accuracy Efforts: 

[Refer to PDF for image: illustration] 

The illustration depicts an inverted triangle with the precision of 
enforcement actions increasing at each subsequent level, using a risk-
based approach. The levels depicted are as follows: 

Top level: 
Up-Front System Edits; 
Timeline: 1 month. 

Second level: 
Data Mining: Missing Reports, Volume Comparisons, LVS/GVS, High Level 
Analyses of Sales Values Royalty Values, Adjustment Monitoring, etc. 
Timeline: 6-9 months. 

Third level: 
Compliance Reviews; 
Timeline: 2-3 years. 

Fourth level: 
Audits; 
Timeline: 7 years (Fed. oil and gas). 

[End of figure] 

Current technology has opened new avenues for MMS to identify and 
analyze erroneous data on a real-time basis. The MMS's data mining 
processes and analyses, when fully implemented, will be similar to 
Recommendations 2 and 3 in the draft report. 

We appreciate GAO's insights and recommendations to improve royalty 
data accuracy. If you have any questions, please contact Andrea Nygren, 
MMS Audit Liaison Officer, at (202) 2084343. 

Sincerely, 

Signed by: [Illegible], for: 

Ned Farquhar: 
Acting Assistant Secretary Land and Minerals Management: 

Enclosure: 

[End of letter] 

Enclosure: 

Response to Government Accountability Office draft report entitled, 
Mineral Revenues: MMS Could Do More to Improve the Accuracy of Key Data 
Used to Collect and Verify Oil and Gas Royalties (GAO-09-549). 

Recommendation 1: Share with payors that submit their data through the 
Electronic Data Interface MMS's recent edit check that prevents payors 
from submitting data claiming processing allowances for gas that is not 
processed, including coalbed methane. 

Response: Concur. The edit check that prevents payors that submit 
royalty reports via the Web from claiming processing allowances against 
unprocessed gas went into effect in April 2009. We have shared this 
edit with those payors that submit their data through EDI so that they 
may modify their systems. We are scheduled to implement this edit in 
the Minerals Management Service Minerals Revenue Management financial 
system in November 2009, so that the edit will apply to all payors, 
including those who submit their data through the EDI. 

Recommendation 2: Design and implement additional edit checks to 
evaluate the net impact of all adjustments on original entries for 
critical royalty variables, including sales values, royalty values, 
sales volumes, transportation allowances, and processing allowances, by 
summing each month all entries for the variable submitted by each payor 
for each lease and each commodity and highlight potentially erroneous 
submissions to payors and appropriate MMS staff. 

Response: Concur. The MMS recently designed and is in the process of 
implementing additional edit checks to improve the accuracy of royalty 
rates and pricing data reported to MMS. In addition, MMS has initiated 
a data mining effort as a second level screening process to increase 
the accuracy of payor-reported data before the data are subjected to 
compliance reviews and ultimately to audit. The MMS's data mining 
process, when fully implemented, will address this recommendation and 
will include monitoring adjustments made by payors to royalty reports, 
detecting missing royalty reports, comparing payor-reported sales 
volumes to third party source documentation, analyzing trends in payor-
reported data, and analyzing key royalty variables to ensure they fall 
within expected ranges. 

Recommendation 3: Use the monthly sums of original and adjusting 
entries for royalty values, sales values, and sales volumes to ensure 
that calculated royalty rates and unit prices for each payor on each 
lease for each commodity fall within expected ranges and highlight 
potentially erroneous submissions to payors and appropriate MMS staff 

Response: Concur. The MMS recently designed and is in the process of 
implementing additional edit checks to improve the accuracy of royalty 
rates and pricing data reported to MMS. In addition, MMS has initiated 
a data mining effort as a second level screening process to increase 
the accuracy of payor-reported data before the data are subjected to 
compliance reviews and ultimately to audit. The MMS's data mining 
process, when fully implemented, will address this recommendation and 
will include monitoring adjustments made by payors to royalty reports, 
detecting missing royalty reports, comparing payor-reported sales 
volumes to third party source documentation, analyzing trends in payor-
reported data, and analyzing key royalty variables to ensure they fall 
within expected ranges. 

Recommendation 4: Enforce current MMS requirements to populate the 
agreement field with the correct agreement number and to populate the 
agreement field for leases outside of agreements with a single unique 
code that is easily identifiable. 

Response: Partially Concur. The MMS is working to improve enforcement 
of agreement field reporting. We are not confident that populating the 
agreement number field for lease-basis reporting with a single unique 
code is the best solution to enforce proper reporting. The MMS is 
evaluating the best methods for ensuring that payors accurately 
populate the agreement number field. 

Recommendation 5: Collaborate with state and tribal auditors on the 
possibility of adding more specific adjustment reason codes that 
describe why payors made corrections to royalty data on the Form MMS-
2014. 

Response: Concur. We agree that the Form MMS-2014 should identify why 
payors make corrections to royalty data; however, we are not confident 
that adding more adjustment reason codes is the best solution to 
demonstrate reasons for corrections to royalty data. The MMS management 
and internal audit staff will collaborate with State and Tribal 
auditors to find the best solution. 

Other: In addition to the above responses to GAO's recommendations, we 
are bringing the following to your attention. On page 10 of the draft 
report, GAO states that MMS has a target date for completion of new 
proposed gas valuation regulations of December 2009. The MMS is 
revising that target date pending direction from the Department 
regarding royalty reform. 

[End of section] 

Appendix III: GAO Contact and Staff Acknowledgments: 

GAO Contact: 

Frank Rusco (202) 512-3841 or ruscof@gao.gov: 

Staff Acknowledgments: 

In addition to the individual named above, Jon Ludwigson, Assistant 
Director; Ron Belak; Melinda Cordero; Alison O'Neill; Kim Raheb; 
Barbara Timmerman; and Mary Welch made key contributions to this 
report. 

[End of section] 

Footnotes: 

[1] Offshore royalty rates for the leases included in the fiscal years 
2006 and 2007 royalty data that we examined are typically 12.5 percent 
or 16.67 percent while onshore royalty rates are typically 12.5 percent 
or from 12.5 to 25 percent for leases issued before 1988, based on 
production levels. For certain onshore leases producing heavy oil or 
oil classified as stripper production--generally low producing leases 
with higher relative costs--royalty rates may have been less than 12.5 
percent for part of fiscal year 2006. Certain amounts of oil produced 
in the Gulf of Mexico during fiscal years 2006 and 2007 may have been 
exempt from royalties under provisions of the Outer Continental Shelf 
Deep Water Royalty Relief Act. Royalty rates for newly issued offshore 
leases in the Gulf of Mexico were increased twice in 2007 and currently 
are 18.75 percent, but it is unlikely that any of the 2007 leases we 
looked at would fall into that royalty category because it typically 
takes several years at least to develop a lease and begin production. 

[2] The Federal Oil and Gas Royalty Simplification and Fairness Act of 
1996, Pub. L. No. 104-185, §5(a) (1996), allows payors 6 years to make 
adjustments to royalty data. 

[3] Five-Year Financial Management Business Plan, FY2008-2012, 
Department of the Interior, Minerals Management Service, October 2008. 

[4] GAO, Mineral Revenues: Cost and Revenue Information Needed to 
Compare Different Approaches for Collecting Federal Oil and Gas 
Royalties, [hyperlink, http://www.gao.gov/products/GAO-04-448] 
(Washington, D.C.: Apr. 16, 2004). 

[5] GAO, Renewable Energy: Increased Geothermal Development Will Depend 
on Overcoming Many Challenges, [hyperlink, 
http://www.gao.gov/products/GAO-06-629] (Washington, D.C.: May 24, 
2006). 

[6] GAO, Royalty Revenues: Total Revenues Have Not Increased at the 
Same Pace as Rising Oil and Natural Gas Prices due to Decreasing 
Production Sold, [hyperlink, http://www.gao.gov/products/GAO-06-786R] 
(Washington, D.C.: June 21, 2006). 

[7] GAO, Mineral Revenues: Data Management Problems and Reliance on 
Self-Reported Data for Compliance Efforts Put MMS Royalty Collections 
at Risk, [hyperlink, http://www.gao.gov/products/GAO-08-893R] 
(Washington, D.C.: Sept. 12, 2008). 

[8] GAO, Mineral Revenues: Data Management Problems and Reliance on 
Self-Reported Data for Compliance Efforts Put MMS Royalty Collections 
at Risk, [hyperlink, http://www.gao.gov/products/GAO-08-893R] 
(Washington, D.C.: Sept. 12, 2008). 

[9] Sales volumes for gas on the Form MMS-2014 are actually listed in 
thousands of cubic feet (mcf). The industry standard for selling 
natural gas is known as MMBtu and refers to millions of Btus, which is 
equal to thousands of cubic feet times the heating value of a cubic 
foot of gas expressed in Btus. 

[10] MMS considers the precise thresholds used to be a confidential 
element in its oversight. 

[11] We excluded October through December 2005 because major hurricanes 
disrupted production. 

[12] We did not include all leases in our analysis because we found it 
difficult to directly match the operator-reported data with the payor- 
reported data for all 29,000 producing federal and Indian leases. Many 
leases, particularly those located onshore, may belong to one or more 
units. Operators may report production volumes either by unit or by 
individual lease, but royalty payors must report royalties by lease and 
indicate on their royalty report if the lease belongs to a unit, but it 
is common for royalty reporters not to identify the unit, creating 
possibilities for mismatching the operator-reported and payor-reported 
data. Furthermore, we found MMS's published lists identifying the 
leases that belong to units to be incomplete. As such, we used MMS's 
Technical Information Management System (TIMS) database, which appears 
to be complete but contains data only for offshore leases, to identify 
offshore leases within federal units. We then excluded all onshore 
leases and the offshore lease belonging to units. We also excluded 
offshore oil production because oil, unlike gas, can be held in storage 
tanks before being sold, and MMS officials said that there are problems 
with the volumes reportedly sold from some of these storage tanks. Our 
resulting sample of offshore gas leases numbers about 1,500. Because we 
did not evaluate all federal and Indian leases, or even random samples 
of all the various types of leases--onshore and offshore, oil and gas, 
large and small, for example--the results of this analysis cannot be 
extrapolated to the entire universe of federal and Indian leases. 
However, offshore gas leases account for a significant amount of gas 
production from all federal leases. 

[13] This estimate is based on the production volumes reported on the 
OGORs, an average Gulf of Mexico royalty rate of 14.7 percent for gas 
in fiscal years 2006 and 2007 after allowances, and the average monthly 
spot prices per MMBtu at the Henry Hub--a major gas-trading center-- 
during the month royalty reports were missing. 

[14] When we report on royalty data, such as sales volumes, we sum all 
sales volumes that an individual payor reports on each lease for each 
product code during each sales month. For example, if one company 
reports 100 barrels of oil sold from a lease during December and its 
partner reports 3 barrels of oil sold from the same lease during the 
same month, we have 2 sales volumes. We would then calculate the 
percentage of these two sales volumes that are positive--either 0, 50, 
or 100 percent. 

[15] We could not compare our calculated implicit onshore royalty rates 
with the actual royalty rates established in the lease terms because 
the latter data were not readily available to us. However, we examined 
a sample and found few onshore leases that departed from the royalty 
rate ranges we used for comparison. Because of the wide range of 
onshore royalty rates that we used, we believe that this is a 
conservative approach. Nevertheless, because of the possibility that a 
calculated royalty rate that is different from general onshore lease 
terms can be legitimate, we refer to the royalty values or the sales 
values for onshore leases in this situation as appearing erroneous, 
rather than being erroneous. 

[16] We refer to these sales values or sales volumes as appearing 
erroneous rather than being erroneous because there could be legitimate 
reasons for these prices being outside of expected ranges. 

[17] We reviewed sales in the offshore Gulf of Mexico because of the 
readily available transparent markets there, as opposed to the many 
different markets onshore that complicate the valuation of oil and gas. 
As in our analyses of sales volumes, sales values, royalty values, and 
transportation and processing allowances, we combined all royalty 
records submitted by a given payor for each month, product type, and 
lease. 

[18] First of the Month is a price that is published on the first day 
of the month in the publication entitled Inside FERC's Gas Marketing 
Report. 

[19] A sale of gas by a company to its affiliate is commonly referred 
to as a non arm's-length transaction, and according to the gas 
valuation regulations, the value of the gas is established according to 
the benchmarks. If a company sells gas to another company with which it 
is not affiliated, the transaction is commonly referred to as an arm's- 
length transaction, and the value of the gas is the sales price and any 
additional compensation that accrues from the sale. 

[20] In some cases, units are revised to either expand or contract to 
reflect better understanding of how oil and gas reservoirs are 
connected and can be developed. 

[21] [hyperlink, http://www.gao.gov/products/GAO-04-448] and 
[hyperlink, http://www.gao.gov/products/GAO-06-786R]. 

[22] Lease data are from MMS's Web site and include onshore and 
offshore leases current to November 14, 2008. We assumed that all 
offshore leases in the Gulf of Mexico produced some gas. 

[23] Maximum permitted transportation allowances are 50 percent of 
sales value. Maximum permitted processing allowances are 66 and 2/3 
percent of the sales value less the cost of transportation. 

[24] [hyperlink, http://www.gao.gov/products/GAO-06-786R], p. 12. 

[25] Specifically, we identified exceptions to be outside of the range 
12.4 to 12.6 percent and 16.567 to 16.767 percent, to account for 
rounding error. 

[26] Specifically, we identified exceptions to be outside of the range 
12.4 to 25.1 percent, to account for rounding error. 

[27] The Royalty Policy Committee is chartered to provide advice to the 
Secretary of the Interior on managing Federal and Indian mineral leases 
and revenues. 

[End of section] 

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