GAO 

United States Government Accountability Office

Report to Congressional Requesters

MINERAL REVENUES

MMS Could Do More 

to Improve the 

Accuracy of Key Data 

Used to Collect and 

Verify Oil and Gas 

Royalties 

July 2009 

GAO-09-549 
What GAO Found

United States Government Accountability Office

Why GAO Did This Study

Highlights

Accountability Integrity Reliability

July 2009

MINERAL REVENUES

MMS Could Do More to Improve the Accuracy of Key 

Data Used to Collect and Verify Oil and Gas Royalties

Highlights of GAO-09-549, a report to 

congressional requesters 

MMS has several key efforts underway to improve the accuracy of the payorreported 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 empanelled 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. 

Production Facilities on a Federal Lease in Colorado 

Source: GAO.

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 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 GAO-09-549 or key components.

For more information, contact Frank Rusco, 

(202) 512-3841, ruscof@gao.gov. 
Page i GAO-09-549 

Contents 

Letter 1

Background 3 

MMS Has Ongoing Efforts to Improve the Accuracy of PayorReported Royalty Data, but It Is Too Early to Assess the 

Effectiveness of These Efforts 7 

In Several Instances, Data Used to Collect and Verify Royalties Are 

Either Missing or Appear to Be Erroneous 12 

Multiple Factors Affect Oil and Gas Companies’ Abilities to 

Accurately Report Royalties Owed to the Federal Government 22 

Conclusions 28 

Recommendations for Executive Action 28 

Agency Comments and Our Evaluation 29 

Appendix I Scope and Methodology 31 

Appendix II Comments from the Department of the Interior 38 

Appendix III GAO Contact and Staff Acknowledgments 42 

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 16 

Table 2: Royalty Rate Calculations Outside of Expected Ranges for 

Federal Oil and Gas Leases, Fiscal Years 2006 and 2007 18 

Figures 

Figure 1: MMS’s Processes for Submitting, Checking, and 

Accepting Royalty Data 9 

Figure 2: Percentage of Gas Production Reports without 

Corresponding Royalty Reports in the Offshore Gulf of 

Mexico for Fiscal Years 2006 and 2007 14 

Figure 3: Range of Reasonable Oil Prices in the Offshore Gulf of 

Mexico Based on Highest and Lowest Daily Spot Prices 

for Each Month 19 

 Royalty Data 
Figure 4: Sales Prices for Oil from Federal Leases in the Offshore 

Gulf of Mexico That Appear Erroneous, Fiscal Years 2006 

and 2007 20 

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 21 

Figure 6: Sales Prices for Gas from Federal Leases in the Offshore 

Gulf of Mexico That Appear Erroneous, Fiscal Years 2006 

and 2007 22 

Figure 7: Block Diagram Illustrating the Hypothetical Creation of a 

Federal Unit 24 

Figure 8: Block Diagram Illustrating a Hypothetical Complex 

Relationship between Unit Agreements and Potential 

Impacts on Oversight 25 

Figure 9: Numbers of Oil and Gas Royalty Records and Leases 

Reported per Month for Fiscal Years 2006 and 2007 32 

Page ii GAO-09-549 Royalty Data
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 

This is a work of the U.S. government and is not subject to copyright protection in the 

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Page iii GAO-09-549 Royalty Data
Page 1 GAO-09-549 

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 selfreported 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 

 Royalty Data 
 

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 

Page 2 GAO-09-549 Royalty Data
 

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. 

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.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 

Background 

 

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. 

Page 3 GAO-09-549 Royalty Data
 

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 MMS2014 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.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.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 

 

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. 

Page 4 GAO-09-549 Royalty Data
 

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.4

 Similarly in 2004, we found that 40 percent of the royalty data 

we examined for 10 geothermal projects was either missing or erroneous.

that 

s 

 

5

In 2006, we examined the relationship between the increases in oil and ga

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.6

 In 2008, 

we reported that MMS’s royalty management system lacked several 

capabilities that would provide greater assurance that royalties are 

4

GAO, Mineral Revenues: Cost and Revenue Information Needed to Compare Different 

Approaches for Collecting Federal Oil and Gas Royalties, GAO-04-448 (Washington, D.C.: 

Apr. 16, 2004). 

5

GAO, Renewable Energy: Increased Geothermal Development Will Depend on 

Overcoming Many Challenges, 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, GAO-06-786R

(Washington, D.C.: June 21, 2006). 

Page 5 GAO-09-549 Royalty Data
 

collected accurately.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 

empanelled 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. 

 

7

GAO, Mineral Revenues: Data Management Problems and Reliance on Self-Reported 

Data for Compliance Efforts Put MMS Royalty Collections at Risk, GAO-08-893R

(Washington, D.C.: Sept. 12, 2008). 

Page 6 GAO-09-549 Royalty Data
 

MMS has three major efforts underway to improve the accuracy of payorreported 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.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 Has Ongoing 

Efforts to Improve the 

Accuracy of PayorReported Royalty 

Data, but It Is Too 

Early to Assess the 

Effectiveness of 

These Efforts 

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 MMS2014 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 

 

8

GAO, Mineral Revenues: Data Management Problems and Reliance on Self-Reported 

Data for Compliance Efforts Put MMS Royalty Collections at Risk, GAO-08-893R

(Washington, D.C.: Sept. 12, 2008). 

Page 7 GAO-09-549 Royalty Data
 

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 sitebased 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 upfront 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. 

Page 8 GAO-09-549 Royalty Data
 

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

Data submission Data acceptance Data used for operations

MMS specified edit checks

integrated into company 

information systems

Company 

information 

systems MMS

 information 

systems – 

royalty

 database

Electronic 

reporting 

interface

Electronic data interchange

MMS edit checks

• If data pass, data

allowed into MMS

database

• If data fail key edit 

checks, data are 

rejected

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. 

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 

Page 9 GAO-09-549 Royalty Data
 

calculation.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, 

 

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. 

Page 10 GAO-09-549 Royalty Data
 

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. 

Page 11 GAO-09-549 Royalty Data
 

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 MMS2014.10 When conducting this process, MMS also is able to identify 

instances when a royalty payor fails to submit the required Form MMS2014. 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. 

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 

In Several Instances, 

Data Used to Collect 

and Verify Royalties 

Are Either Missing or 

Appear to Be 

Erroneous 

 

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

Page 12 GAO-09-549 Royalty Data
 

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 2007.11

For each month in which operators reported gas production, we checked 

MMS’s monthly royalty reports to ensure that payors reported sales of 

gas.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.13 However, it is possible that instead of reporting 

royalties on the appropriate reports, payors may have misreported these 

 

11We excluded October through December 2005 because major hurricanes disrupted 

production. 

12We 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. 

13This 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. 

Page 13 GAO-09-549 Royalty Data
 

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 

0

1

2

3

4

5

6

7

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept.

Percentage

Source: GAO analysis of MMS data.

2006 2007

Checks for 

Reasonableness of PayorReported 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 

Page 14 GAO-09-549 Royalty Data
 

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.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 

 

14When 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. 

Page 15 GAO-09-549 Royalty Data
 

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 

Percent error 

rate found

Reporting sales volume when reporting allowances separately from 

royalties due 

0

Exceeding the regulatory limit for processing allowancesa0.02

Exceeding the regulatory limit for transportation allowancesa0.06

Reporting negative sales volume 0.12

Reporting negative sales values 0.20

Reporting negative royalty values 0.20

Reporting positive processing allowances 0.77

Reporting positive transportation allowances 1.73

Claiming processing allowance for unprocessed gas or coalbed 

methane 

2.29

Source: GAO analysis of MMS data. 

a

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

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, 

Page 16 GAO-09-549 Royalty Data
 

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.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 

 

15We 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. 

Page 17 GAO-09-549 Royalty Data
 

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 Apparent error rate (percent)

Offshore oil 2.2

Offshore gas 2.0

Onshore oil 7.4

Onshore gas 4.8

Source: GAO analysis of MMS data. 

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.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.17

 

16We 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. 

17We 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. 

Page 18 GAO-09-549 Royalty Data
 

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 

Dollars per barrel

Source: GAO analysis of MMS data.

2005 2006 2007

0

10

20

30

40

50

60

70

80

90

Mars spot price

LLS spot price

Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept.

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 

Page 19 GAO-09-549 Royalty Data
 

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 

Percentage appearing erroneous

Source: GAO analysis of MMS data.

2005 2006 2007

0

1

2

3

4

5

6

7

8

9

10

Percentage above reasonable range

Percentage below reasonable range

Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept.

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 

Page 20 GAO-09-549 Royalty Data
 

month, and the First of the Month price.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. 

ber 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 

Dollars per MMBtu

Source: GAO analysis of MMS data.

2005 2006 2007

0

2

4

6

8

10

12

14

16

18

Lowest gas price

Highest gas price

Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept.

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 

 

18First 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. 

Page 21 GAO-09-549 Royalty Data
 

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 

Percentage appearing erroneous

Source: GAO analysis of MMS data.

2005 2006 2007

0

5

10

15

20

Percentage above reasonable range

Percentage below reasonable range

Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept.

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. 

Multiple Factors 

Affect Oil and Gas 

Companies’ Abilities 

to Accurately Report 

Royalties Owed to the 

Federal Government 

Page 22 GAO-09-549 Royalty Data
 

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. 

Page 23 GAO-09-549 Royalty Data
 

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

1001

1002

1003

1004

Deep sandstone

Shallow sandstone

Limestone

1001

Sandstone

Limestone

Salt

Shale Lease number

Source: GAO.

Lease boundary

Boundary of unit B

Boundary of unit A

Oil reservoir Producing oil well

1001

1002

1003

1004

Deep sandstone

Shallow sandstone

Limestone

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.

#2

#1

#1

A

B

Page 24 GAO-09-549 Royalty Data
 

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

Oversight 

1001

1002

1003

1004

#2

#1

Deep sandstone

Shallow sandstone

Limestone

1001

Sandstone

Limestone

Salt

Shale Lease number

Source: GAO.

Lease boundary

Boundary of unit B

Boundary of unit A

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.

#3

C

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. 

Page 25 GAO-09-549 Royalty Data
 

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.19 RPC also recommended that MMS more clearly define 

allowable transportation and processing deductions for natural gas in their 

regulations. 

Industry Representatives 

Stated That Ambiguous 

Federal Regulations Can 

Create Difficulty in 

Establishing Gas Prices 

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. 

 

19A 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. 

Page 26 GAO-09-549 Royalty Data
 

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.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. 

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 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 

 

20In 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. 

Page 27 GAO-09-549 Royalty Data
 

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. 

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. 

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. 

Conclusions 

Recommendations for 

Executive Action 

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 

Page 28 GAO-09-549 Royalty Data
 

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. 

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. 

Agency Comments 

and Our Evaluation 

Page 29 GAO-09-549 Royalty Data
 

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 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 

Frank Rusco 

of this report. Key contributors to this report are listed in appendix III. 

Director, Natural Resources 

 and Environment 

Page 30 GAO-09-549 Royalty Data
Appendix I: Scope and Methodology 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.1

 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. 

 

1

GAO-04-448 and GAO-06-786R. 

Page 31 GAO-09-549 Royalty Data 
Appendix I: Scope and Methodology 

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

Number of records (in thousands) Number of leases (in thousands)

Source: GAO analysis of MMS data.

2005 2006 2007

0

50

100

150

200

250

0

5

10

15

20

25

Leases

Records

Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept.

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.2

 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 

 

2

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. 

Page 32 GAO-09-549 Royalty Data
Appendix I: Scope and Methodology 

(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 

Page 33 GAO-09-549 Royalty Data
Appendix I: Scope and Methodology 

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 

Page 34 GAO-09-549 Royalty Data
Appendix I: Scope and Methodology 

13), and offshore deep water royalty relief (transaction code 41).3 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.4

 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.5

 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.6

 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 

 

3

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. 

4

GAO-06-786R, p. 12. 

5

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. 

6

Specifically, we identified exceptions to be outside of the range 12.4 to 25.1 percent, to 

account for rounding error. 

Page 35 GAO-09-549 Royalty Data
Appendix I: Scope and Methodology 

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 

Page 36 GAO-09-549 Royalty Data
Appendix I: Scope and Methodology 

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. 

Page 37 GAO-09-549 Royalty Data
Appendix II: Comments from the Department Appendix II: Comments from the Department of the Interior 

of the Interior 

Page 38 GAO-09-549 Royalty Data 
Appendix II: Comments from the Department 

of the Interior 

Page 39 GAO-09-549 Royalty Data
Appendix II: Comments from the Department 

of the Interior 

Page 40 GAO-09-549 Royalty Data
Appendix II: Comments from the Department 

of the Interior 

Page 41 GAO-09-549 Royalty Data
Appendix III: GAO

A

 Contact and Staff 

cknowledgments 

Page 42 GAO-09-549 

Appendix III: GAO Contact and Staff 

Acknowledgments 

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

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. 

 Royalty Data 

GAO Contact 

Staff 

Acknowledgments 

(360986) 
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