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OAR Box 1828 

Prepped by Ollie Stewart 

Document Number: 

276) ll-K- (I) -89 

Docket Number: 

A-83-27 

Printed 11/12/2008 11:12:58 AM Sheet 276 of 325 
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J • 

An occasional publication of Gas Research Institute on topics of current interest. 

The GRI Hydrocarbon Model: The Structure, 

Results, and Sensitivities of the 

Model in its Initial Form 

prepared by 

Thomas J. Woods 

Gas Research Institute 

Strategic Analysis and Energy Forecasting Division 

and 

E. Harry Vidas 

Energy and Environmental Analysis, Inc. 

May 1983 

H*PW^ 

Abstract 

This paper describes the Gas Research Institute (GRI) Hydrocarbon Model which is currently being constructed by Energy and Environmental Analysis, Inc. (EEA) under contract to GRI's Division of Strategic 

Analysis and Energy Forecasting (SA&EF). 

Planning and evaluation of an R&D program within GRI requires an institutional comprehension of the 

outlook for United States energy supply and demand and a projection of the physical, social, and economic 

environment that will confront GRI and the gas industry in the years ahead. A quantitative understanding 

of the natural gas supply and the physical and economic factors that affect it is essential both for general 

supply and demand forecasting and for specific evaluations of research activities which will impact upon 

natural gas supply and upon supplemental sources of gaseous fuels. 

The purpose of the GRI Hydrocarbon Model is to provide a rigorous and consistent framework for analyzing 

the resource cost of finding, developing, and producing natural gas and crude oil in the lower-48 United 

States. The important features which distinguish the GRI modeling approach from other oil and gas supply 

models include: 

• extensive use of detailed field and drilling data bases; 

• high degree of disaggregation in the characterization of the potential resource base; and 

• modeling of industry decision-making techniques to determine the level, location, and direction (i.e., 

oil vs. gas) of drilling activity over time. 

This paper outlines the basic structure of the model, presents the results of some test runs to demonstrate 

the operations and capability of the model, and briefly describes further development work planned for 

the model in the upcoming year. 

or\ Gas Research Institute, 8600 West Bryn Mawr Avenue, Chicago, Illinois 60631 312/399-8100 
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Overview of GRI Hydrocarbon Model 

Introduction 

This paper describes the Gas Research Institute (GRI) Hydrocarbon Model which is currently being constructed by Energy and Environmental Analysis, Inc. (EEA) under contract to GRI's Division of Strategic 

Analysis and Energy Forecasting (SA&EF). 

Planning and evaluation of an R&D program within GRI requires an institutional comprehension of the 

outlook for United States energy supply and demand and a projection of the physical, social, and economic 

environment that will confront GRI and the gas industry in the years ahead. A quantitative understanding 

of the natural gas supply and the physical and economic factors that affect it is essential both for general 

supply and demand forecasting and for specific evaluations of research activities which will impact upon 

natural gas supply and upon supplemental sources of gaseous fuels. The GRI Hydrocarbon Model has 

been developed both as an aid to projecting gas supply volumes and costs under differing assumptions 

and as a research tool to explore the technical and economic parameters which govern natural gas 

production. 

In 1982 EEA began a project for GRI to develop a computerized model to project future natural gas prices 

and availability. The initial form of that model was completed and tested in late 1982. This paper outlines 

the basic structure of the model, presents the results of some test runs to demonstrate the operations 

and capability of the model, and briefly describes further development work planned for the model in 

the upcoming year. 

Model Coverage 

The purpose of the GRI Hydrocarbon Model is to provide a rigorous and consistent framework for analyzing 

the resource cost of finding, developing, and producing natural gas and crude oil in the lower-48 United 

States. The important features which distinguish the GRI modeling approach from other oil and gas supply 

models include: 

• extensive use of detailed field and drilling data bases; 

• high degree of disaggregation in the characterization of the potential resource base; and 

• modeling of industry decision-making techniques to determine the level, location, and direction (i.e., 

oil vs. gas) of drilling activity over time. 

The lower-48 United States is broken down into the regions used by the Potential Gas Committee (PGC) 

in estimating remaining undiscovered gas resources. (See Figure 1.) The model has 10 onshore and 

three offshore regions. PGC regions H and I are combined in the model, and the Gulf offshore is treated 

as a single region. The onshore regions in the model are divided into four depth intervals: 0-5,000 ft, 

5-10,000 ft, 10-15,000 ft, and below 15,000 ft. Each depth interval has its own particular resource base 

and hydrocarbon find-rates. 

The model covers the exploration, development, and production of oil as well as natural gas. There are 

two primary reasons to include oil in the model. The first is that the find-rate methodology selected for 

the model is based on "areal exhaustion"—i.e., as more and more wells are drilled in a given cubic mile 

volume of sedimentary rock, the probability of finding a field of a given size is reduced. Because both 

oil and gas fields may be found in the same geographic area, oil, gas, and combination oil/gas fields 

must be treated together in using historical data to develop find-rate equations based on areal exhaustion. The second reason for including oil in the model is that the economics of exploration for oil and 

gas are intertwined. While explorers can identify a region as oil or gas prone, they cannot identify a particular prospect as being either oil or gas before a well is drilled to test the prospect. Therefore, in areas 

where both resources may be found, exploration activity and costs cannot be modeled credibly for gas 

independently of oil. 

Model Structure in Brief 

The GRI Hydrocarbon Model has been designed to operate in two modes: as a time-dimensionless curve 

generator and as a simulator of drilling activity over time. The first mode is used to show how the oil 
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and gas resource base is distributed with regard to the cost of discovery, development, and production. 

In this mode, a cost/quantity curve is created showing the amount of gas that eventually would be found 

and produced given a certain price. Examples of such curves produced by the GRI Hydrocarbon Model 

are presented in the section on test results. 

In the second mode of operation, the model simulates drilling decisions in each model period—generally 

a five-year interval. The model chooses the level and location of exploratory drilling in new fields in each 

model period. Within the model, this exploratory drilling then leads to the discovery of new fields and, 

over time, to reserve additions, development drilling, and production. The timing of reserve additions, 

development drilling, and production following a field's discovery in the GRI Hydrocarbon Model is based 

on historical experience for hydrocarbon fields with similar characteristics. 

Decisions on where to drill are made in the model based primarily on economics. Each increment of 

exploratory drilling of, say, 500 wells in a region is evaluated to determine whether the results of that 

increment (including all subsequent development drilling and production) will result in the required 

minimum rate of return. Because of resource depletion, each additional increment of drilling usually will 

find less oil and gas and thus will have a lower rate of return. At some point, a drilling increment will 

have a rate of return below the minimum required rate, and further drilling will be uneconomical. 

In any given five-year period, there may be several economic drilling increments available in each region. 

The model chooses among available increments based on the highest rate of return. This selection process, however, is constrained such that the total of exploration wells falls between a pre-specified minimum 

and maximum in each region. These regional minimum and maximum drilling limits are used to simulate 

industry inertia and industry resource constraints (i.e., rig availability, industry cash flow). These limits 

are set in the model as a user-specified percent deviation from the previous period's exploratory drilling 

solution. For instance, if 1,500 exploratory wells are drilled in the 1981-85 period for a specific region 

and depth interval, the minimum and maximum number of wells that could be drilled in the 1986-90 period 

might be 750 and 2,250 wells. 

The model also has a feature allowing the specification of maximum dollar expenditures for each period 

as a simulation of producer's capital constraints. When this feature is used, the selection of drilling increments among regions is stopped when the sum of the expenditures required for the selected increments 

reaches the predetermined maximum. Another feature of the model allows for the specification of lower-48 

Represents Offshore Areas 

ffilh Depths Less Than 

• 1,000 liters 

Figure 1. Hydrocarbon Model Regions. 
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gas production levels for future years. When this feature is employed, the selection of drilling increments 

stops in each period when enough new gas is found to push total lower-48 production up to the targeted 

level of gas production for the last year of the period. For instance, the user might specify lower-48 production as 18 Tcf in 1990. If the model predicted production from all fields found before 1985 to be 16 

Tcf in 1990, the model would add sufficient reserves in the 1986-90 period to increase production by 

2 Tcf in 1990. 

Selection of Modes of Operation 

Depending on what questions are being addressed, the model can be run in several ways. When the 

user wants a simple exposition of how potential gas reserves in new fields are distributed with respect 

to cost, the curve-generating mode of the model is run. The resulting cost/quantity curves can be aggregated in any desired combination of region and depth as well as by total lower-48. These curves represent the quantities of natural gas that could be found and produced at various prices irrespective of when 

discovery and production might take place. 

If the user wishes to investigate an issue related to production and cost trends over time, the simulation 

mode of the model must be run. Here the user can specify production quantity and have the model solve 

for prices, or the user can specify price and have the model solve for maximum possible production. 

In the first case, the user would specify a target natural gas production level for the lower-48 states for 

each period. The model then would calculate the price needed to bring on sufficient gas to meet that 

level of production. In the second instance, the user would specify a price trajectory for natural gas and 

oil, and the model would solve for drilling levels, reserve additions, and production in each period. The 

major difference in these two techniques for running the GRI Hydrocarbon Model is whether a specific 

production target or a price will constrain drilling activity in each period. 

In addition to these production targets and price constraints, the model's physical drilling limits (expressed 

as a minimum and maximum number of wells that are to be drilled in each region each period) and the 

expenditure constraint (expressed as the total dollar amount for exploration and development started 

each period) also can act as constraints on the level of exploratory drilling, reserve additions, and production in the model. For instance, the user might specify a production target of 25 Tcf for 1985, but 

the user-specified constraints on the maximum increase to be allowed in drilling of, say, 20 percent per 

year might make the target impossible to reach. In that case, the model would drill up to the physical 

drilling limits and 1985 production would not reach the specified target. 

Model Logic and Data Sources 

The Discovery Process 

The key feature of any exploration and development model is its representation of how exploratory activity leads to the discovery of additional reserves. This discovery process is usually modeled through 

"find-rate equations." The most commonly used specification for find-rate equations (e.g., the Department of Energy's National Oil and Gas Supply Model) relates footage drilled to barrels of oil or Mcf of 

gas found. Such find-rate equations usually are statistically fitted using historical American Petroleum 

Institute (API)/American Gas Association (A.G.A.) reserve data along with API/American Association of 

Petroleum Geologists (AAPG) aggregate drilling statistics. These equations indicate that, as exploration 

is carried out in an area, the amount of reserves found per foot of drilling declines. 

In developing the discovery process for the GRI Hydrocarbon Model, a major consideration was that 

the approach be as accurate as possible and that it be able to reflect accurately the cost of finding and 

developing oil and gas reserves. The major constraints found in the conventional footage/reserve findrate equations were: 

• The cost per foot for a well rises steeply with the depth of the well. Using footage as the independent 

variable in the find-rate equation would distort drilling cost when deeper wells are drilled in an area 

as the resources at shallower depths are depleted. 

• There exist significant economies of scale in developing oil and gas fields, both onshore, and especially, in the offshore areas. The use of find-rate equations that do not specify reserves found by the 

distribution of field sizes cannot accurately deal with development costs. 
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• The API/A.G.A. annual reserve addition data are quite volatile and complicate statistical analyses 

of the data, especially on a state or a regional basis. 

To overcome these constraints, it was decided that areas should be broken out into depth intervals and 

that the distribution of field sizes within each depth interval should be modeled using modified ArpsRoberts find-rate equations. These equations are used to predict the number of fields of a certain size 

that will be discovered after a given number of exploratory wells have been drilled. There are separate 

equations for each size class of field (e.g., size class 10 is between 0.76 and 1.52 million barrels of oil 

equivalent) within each depth interval within each region. The GRI model has 13 regions, up to four depth 

intervals, and 20 field sizes for a total of approximately 1,000 separate find-rate equations. 

For regions and depth intervals with substantial exploratory histories, these find-rate equations are solved 

using historical data. For relatively unexplored areas where insufficient data exist to fit these equations, 

the equations are estimated by analogy to mature areas. This is done by taking an estimate of the 

recoverable resource in an area (e.g., from U.S. Geological Survey (USGS) or PGC estimates) and 

distributing it by an assumed field size distribution for the GRI model. 

The operation of the find-rate equations is shown in Figure 2. A level of exploratory wells is entered into 

the equations for a given "area," i.e., a specific region and depth interval, to solve for the number of 

discovered fields in each size class. The number of wells that is entered is the cumulative number of 

wells actually drilled up to the starting date of the model simulation, say, 5,000 wells. The additional 

interval of wells, say, 500, can be determined by inputting the value 5,500 into the equations and computing the difference in the cumulative field discoveries between 5,000 and 5,500 wells. The number 

of fields to be found with yet another 500 wells is found by repeating this procedure with the inputted 

values of 5,500 and 6,000 wells. 

Unit of 

Exploration Activity 

Find-Rate E 

for Each Fie 

(e.g.) 

500 

Wells 

• 

\ 

i 

2 

3 

n 

/ 

18 

19 

20 

quations 

Id Size 

Distribution of 

Field Discoveries 

»n * Xm 

»n 

> H 

it n 

• i l 

~~w feu] 

W WSM 

w BU 

Figure 2. Operation of Find-Rate Equations. 

Data Sources for Find-Rate Equations 

The data with which the equations are solved are taken from several sources. Individual field-by-field 

data have been compiled from the Petroleum Data System's computerized field/reservoir record files 

maintained at the University of Oklahoma's Energy Resources Center. These records have been compil-
P.7 

ed under contract to the USGS from several sources, most notably individual state oil and gas regulatory 

agencies. 

The data were verified and supplemented by EEA for the largest 2,500 fields in the United States through 

the use of a Rand Corporation study recently completed for DOE.' EEA further worked with these data 

bases to put all records on the same basis; that is, individual reservoir records were combined into field 

records, and natural gas production and reserves were put into a standard basis (14.72 psia, at 60°F). 

For states where production and reserves for associated gas or natural gas liquids were not kept, these 

parameters were estimated. 

The resulting "clean and consistent" data base contains records for nearly 30,000 fields discovered in 

the United States before 1976. The records contain over 160 pieces of information on each field. The 

relevant data used for estimating the find-rate equations in the data base include: 

• location of field (state, county, geologic basin, PGC region), 

• estimated size of field (cumulative production plus reserves for crude oil, natural gas, and natural 

gas liquids), 

• year of discovery, 

• depth, and 

• surface area in acres. 

These field records were summed by size in each model region and depth interval for solution of the 

find-rate equations. 

Historical drilling statistics for solution of the equations came from several sources. The most important 

source is a computerized data base of exploratory well records collected by the AAPG and the API. This 

data base contains individual well data (e.g., date, location, depth, successful or not) for all exploratory 

wells drilled since 1954. These data were supplemented by aggregated annual drilling data (total number 

of exploratory wells and total footage) from the AAPG Bulletin for state and substate areas between 1937 

and 1953. Prior to 1937, records reconstructed by the API for total (exploratory and development) wells 

by state back to the first oil wells in 1859 were used.2 Exploratory wells were estimated by assuming 

a consistent ratio between exploratory and total wells. 

Model Logic Flow 

The way the number of fields discovered at different increments of exploratory drilling is used in the 

GRI Hydrocarbon Model is shown in Figure 3 in simplified form. The number of new fields in each size 

class is first broken down into oil and gas fields based on geologic occurrence. (The ratio of gas to oil 

fields increases with depth as well as varying by region.) Based on the expected prices of oil and gas, 

the after-tax cash flow of developing and producing each field is determined to see if it meets the required rate of return. If not, that field will not be developed. At higher expected oil and gas prices, smaller 

fields are economic to develop. (See Figure 4.) This procedure is repeated for each type and size of 

field. For fields economic to develop, the results are summed for number of fields, reserve additions, 

and development cash flows. The cost of drilling the 500 exploratory wells is then added to these results 

to determine total after-tax cash flow for the drilling increment of 500 exploratory wells. 

This procedure is repeated in the GRI Hydrocarbon Model with higher and higher drilling increments 

for each region. If the total cash flow from an exploratory drilling increment along with the associated 

development and production meets the required rate of return, the next increment of 500 wells is tested. 

Eventually the process of resource depletion causes the rate of return at some very high number of exploratory wells to fall below the required level. The higher the oil and gas prices assumed in the model 

run, the larger the number of exploratory wells and reserve additions that will be economic. 

When the model is run in a simulation mode, each economic increment of 500 exploratory wells is placed 

in the model's "Options Table." This is Step 1 of the overall logic shown in Figure 5. The Options Table 

represents those drilling options that would be economic for the oil and gas industry to undertake. The 

order in which these options are taken in Step 2 depends primarily on their relative economics. The model 

first chooses those options with the highest return as measured by the profit index, i.e., the ratio of net 

present value to investment present value. The profit index is used in the model because it is widely 
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« • Repeat for Each Area: 

Repeat for Higher Increments of Exploratory Drilling 4 -

Additional Drillini in Area not 

Economic; Move to Next Area 

NO 

1. 

Using Find Rate Equations, Estimate Expected 

Number of Fields in Each Size Class From 

Drillini Increment I j 

2. 

Calculate Cost of Developing Oil and Gas Fields 

in Each Size Class and Project Cash Flows 

From Development and Production 

3. 

Detennine Which Sizes of Oil and Gas Fields will 

be Economic to Develop (i.e. Cash Flow will 

Meet Required Rate of Return) 

Sum Development Cash Flows for Economic Fields 

and Add to Exploration Cash Flows to Get Total 

Cash Flow for Drillini Increment I j 

Does 

Cash Flow for 

Exploratory Drilling Increment lj " 

Meet Required 

Return? 

YES Put Increment lj Into Options Table 

and Move to Next Increment 

Figure 3. Method of Estimating Maximum Economic Level for Exploratory Drilling in Each Area. 

Development and Production Costs for Field 

Dollars per Million Cubic Feet 

SIZES MADE ECONOMIC WITH 

HIGHER PRICES 

16 18 

Field Size Class 

Figure 4. Based on Expected Prices, Model Calculates Minimum Field Size Worth Developing 

Once Found. 
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Resource Base 

Costs 

Financial Parameters 

Expected Prices and Takes 

i 

Determine 

Maximum Economic 

Level for 

Exploratory Drilling 

in Each Area 

Capital Constraints 

Production Targets 

Industry Inertia 

I I i 

If Constraints are 

Binding, Select 

Among Economic 

Drilling Options in 

Various Areas 

Step One Step Two 

• Oil and Gas 

Reserve Additions 

and Production 

Rates 

• Drilling Activity 

• Hydrocarbon Cost 

Outputs 

Figure 5. Basic Structure of GRI Exploration and Development Model. 

used in the oil and gas industry,3 and because it is more easily computed than the best other criterion, 

internal rate of return. 

As discussed in the previous chapter, the order and timing in which the options are exploited in the model 

may also be constrained by setting upper and lower limits on the total number of wells that can be drilled 

in any period (industry inertia), by setting limits on the total expenditures that the industry can undertake 

(capital constraints), or by targeting a specific level of gas production. 

Data Sources for Costs 

The key cost parameters used in the model are shown in Table 1. Well costs by region, depth, and type 

(dry, oil, or gas) were obtained from the annual Joint Association Survey. Lease equipment and well 

operating costs were taken from the annual Energy Information Administration (EIA)/DOE publication 

Costs and Indexes for Domestic Oil and Gas Field Equipment and Production Operation. Production platform costs were estimated from data in industry publications, particularly Offshore magazine. Operating 

costs for platforms were taken from the Cost and Indexes annual. Other costs such as leasehold costs 

(geographical surveys, test holes, etc.) and overhead costs were taken from the Census report Annual 

Survey of Oil and Gas. The method of tax accounting used in the model is derived from Income Taxation 

of Natural Resources, an annual publication of Prentice-Hall, Inc. 

Financial Calculations in Model 

The method used in the model to evaluate investments is net, after-tax, discounted cash flow. Investments 

that have an after-tax present value greater than or equal to zero when discounted at the minimum required rate of return are considered economic and may be undertaken in the model. In choosing among 

economic investments, the relative desirability of investments is measured by the profit index: the aftertax net present value of the investment divided by the before-tax present value of expenditures for the 

investment. Investments that have a rate of return exactly equal to the minimum required rate of return 

have a profit index equal to zero. Investments with returns above the minimum have profit indices above 

zero. In general, the higher the rate of return, the higher the profit index. 

The minimum required rate of return used in the model is usually 10 percent real, after-tax. If one assumes 

a 6 percent rate of inflation and a 40 percent average income tax rate, the nominal interest rate would 

be 27.7 percent if the investment were financed totally by debt or a nominal cost of equity of 16.6 percent 

if financed totally through equity. The translation into debt results in a higher rate because a company's 

interest payments on debt are tax deductible and thus result in a lower after-tax cost. If the investment 

8 
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were financed 30 percent by debt and 70 percent by equity, the after-tax cost of capital of 10 percent 

could be translated into a nominal cost of debt of 15 percent and a nominal cost of equity of 18.8 percent. * 

The tax rates used in the model's financial analyses are those applying to large companies. Special tax 

breaks (e.g., percent depletion on new investments) accruing to small companies are not included in 

the model. 

Moreover, all producers within each region and depth are treated as a single entity. For instance, an 

exploratory well increment of, say, 500 wells plus all subsequent development and production activity 

for a particular area is evaluated as if a single company were undertaking this activity. 

Natural Gas Resource Cost Calculation 

An important feature of the model is its calculation of the "resource cost" of gas. The resource cost of 

gas is defined as the price that would be needed to make the producer's after-tax rate of return exactly 

equal to the minimum required rate of return. Because the model treats exploration for both oil and gas 

as a single activity, exploration costs must be allocated in some manner between oil and gas in order 

for the resource costs of gas to be calculated. In the current version of the model, exploration costs are 

allocated on a barrels-of-oil-equivalent (BOE) basis. If, for instance, an increment of exploratory drilling 

adds 40 million BOE of oil and 60 million BOE of gas, 40 percent of the exploratory cost is allocated 

to oil and 60 percent is allocated to gas in calculating the resource cost of the gas. Other forms of allocation could be applied such as the "oil derived" approach discussed later in this paper. 

Before the 1970s most gas was found as a by-product of exploratory activity directed toward oil. In that 

period oil, in effect, subsidized the exploration for gas. It is possible to hypothesize similar situations 

in the future whereby the gas resource cost is calculated with gas bearing only that portion of exploratory 

costs not recoverable from oil revenues. An example of such a calculation is shown in the following section in Table 6. 

Table 1. Key Cost Parameters in the GRI Hydrocarbon Model 

Exploration 

Successful Exploratory Wells 

Dry Exploratory Wells 

Bonus Costs 

Leasehold Costs (other than Bonus) 

G&A 

Development 

Successful Development Wells 

Dry Development Wells 

Lease Equipment Costs 

G&A 

Production 

Revenue 

Depreciation, Depletion Allowances 

O&M Costs 

Royalties 

Severance Taxes 

Windfall Profits Tax 

Income Tax 

G&A 

*This is only one of many combinations of debt/equity splits and nominal debt and equity capital costs 

equivalent to 10 percent real after-tax rate of return. 
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Test Results ol Model 

Resource Base Assumptions Used in Test Runs 

The test runs presented in this report are based on initial estimates of the resource base and find-rate 

equations for each model region. These runs are intended to illustrate the operations and sensitivities 

of the model and are not intended to be projections of future hydrocarbon costs and production. 

The initial assumptions for the resource base in undiscovered fields were derived by applying Arps-Roberts 

equations to historical data on cumulative discovery of fields by size. The estimates were developed so 

that the total resource base roughly approximated the USGS mean estimate. A comparison of the model's 

resource base assumptions with USGS and PGC estimates for undiscovered fields is shown in Table 

2. Note that these estimates are for fields undiscovered as of 1976, the first year which is projected in 

the GRI Hydrocarbon Model's operation. To match the USGS and PGC estimates made in 1981 to the 

1976 resource base starting point for the model, GRI has calculated that some 43.6 Tcf of gas and 2.26 

billion barrels of oil were added to approximate the resources in new fields discovered between 1976 

and 1980. 

Table 2. Resource Base Used in Model Test Runs and Comparable USGS and PGC Estimates (Billion 

Barrels of Oil and Tcf of Gas in Undiscovered Fields 

Model Region 

A East 

B FL, MS, AL 

C Midwest 

D N. LA, N.E. TX, AR 

E S. LA, Onshore 

G S. TX, Onshore 

HI West 

JN Mid Continent 

JS Permian Basin 

L Pacific Coast Onshore 

EGO Gulf Offshore 

LO Pacific Offshore 

' Total Lower-48 

Hydrocarbon 

Oil 

1.2 

4.0 

2.2 

2.6 

0.6 

1.3 

18.1 

6.3 

3.8 

7.2 

3.9 

4.1 

55.5 

Model3 

Gas 

37.6 

19.6 

4.9 

43.6 

30.5 

58.5 

198.5 

74.7 

41.3 

25.5 

91.4 

6.9 

633.4 

as of 1975) 

USGSb 

Oil 

0.9 

1.7 

2.2 

4.0 

1.5 

2.9 

24.1 

4.7 

4.0 

4.5 

5.5 

4.4 . 

60.4 

Gas 

21.6 

10.1 

9.0 

29.5 • 

48.0 

67.5 

140.5 

47.6 

34.7 

14.9 

87.2 

7.3 

517.9 

PGCC 

Gas 

45.3 

16.9 

4.1 

46.4 

18.5 

26.3 

155.7 

111.1 

36.3 

24.3 

75.2 

17.4 

577.5 

a

 The resource base in the model is an estimate of resources recoverable from all undiscovered fields. It is not equivalent to the 

economically recoverable resources. 

Adapted from mean estimates in "Estimates of Undiscovered Recoverable Conventional Resources of Oil and Gas in the United 

States." U.S. Geological Survey. Circular 860, 1981. 

c

 Adapted from possible and speculative reserve estimates in "Potential Supply of Natural Gas in the United States." Potential Gas 

Committee, 1981. 

In addition to reserve additions from new (i.e., post-1975) fields, the modef also tracks the growth in 

reserves for existing (i.e., pre-1976) fields. The ultimate amount of reserve appreciation for the pre-1976 

fields is modeled as 192 Tcf of gas and 22.0 billion barrels of oil based on USGS and PGC estimates. 

The rate at which reserves are added to existing fields is based on the observed trends of reserve additions in existing fields. In the period of 1976 to 2000, some 146 Tcf of gas (76 percent of the total) and 

some 17.9 billion barrels of oil (81 percent of total) are being modeled as added to reserves in pre-1976 

fields. The oil figures include some additions to reserves expected through enhanced oil recovery. 

10 
P.12 _ 

The hydrocarbon resource base used in the GRI Hydrocarbon Model is summarized below (billions of 

barrels of oil and Tcf of gas): 

Oil Gas 

Existing Fields (pre-1976) 

New Fields (post-1975) 

Total 

22.0 

55.5 

77.5 

192.0 

633.4 

825.4 

Cost Distribution of New Field Resources 

The cost distribution of the new field resources in the lower-48 states can best be displayed through 

use of the curve-generating form of the model. This form of the model displays the total quantity of the 

gas resource base that can be found, developed, and produced at various prices regardless of when 

such activity might take place. 

Figure 6 shows such a curve for the reference case assumption of 10 percent real, after-tax rate of return. 

All costs are in 1980 dollars. In generating the curve, a cutoff point of approximately $10.00/Mcf is used. 

No gas with a resource cost above that point appears on the graph. Similar curves are also shown in 

Figure 6 for sensitivity cases with 5 and 15 percent real, after-tax rates of return. Note that the reduction 

in the assumed minimum required rate of return from 10 to 5 percent reduces the resource cost of a 

given quantity of gas by 20 to 25 percent. 

PRICE IN DOLLARS 

PER THOUSAND CUBIC FEET 

GAS IN TRILLION CUBIC FEET 

Figure 6. New Field Resource Cost Curves (Lower-48 States). 

It is important to note that the quantity of gas that is exploitable at or below $10.00/Mcf is only a portion 

of the total resource base assumed to exist in fields undiscovered as of 1975. In the 10 percent rate 

of return case, for instance, approximately 300 Tcf of gas is economic at $10.00/Mcf out of the 633 Tcf 

assumed undiscovered resource base. When the assumed rate of return drops to 5 percent, the amount 

of gas economic at $10.00/Mcf increases to approximately 345 Tcf. 

11 

jgj 
P.13 

Comparison of Model Results in Simulation Mode to Historical Data 

The reasonableness of the results obtained by the GRI Hydrocarbon Model can be tested by comparing 

the results of the model to historical data for a simulated period. Since the model's first projected year 

is 1976, this can be done rather easily. 

The right side of Table 3 shows the results of a model run for the period 1976 to 1979 for the total quantity of oil and gas in fields "discovered" by the model in that period. The oil and gas quantities represent 

the reserves that ultimately will be found in those fields—not just that portion found and booked in that 

four-year period. The table also shows estimates of the ultimate recovery from 1976-79 fields based on 

three data sources. 

The first source is the ultimate recovery by year of discovery tables in the API/A.G.A. "Blue Book" from 

1979.4 The figures in that source were adjusted upward by so-called "alpha factors" to account for the 

expected future reserve additions in these fields. Because more growth is expected in the younger fields, 

the alpha factor is largest for one-year-old fields and becomes smaller as the age of the field increases. 

The second source is the annual new field discovery data taken from the Blue Book for the years 1976 

through 1979. These data are the amount of reserves booked in the first year of discovery. To convert 

these figures into ultimate recovery, they were multiplied by the alpha factor for one-year-old fields. The 

third estimate on Table 3 is from the annual new field discovery series from EIA.5 As with the similar 

API/A.G.A. series, these figures were multiplied by the alpha factor for one-year-old fields. 

Because the EIA began collecting reserve data only in 1977, it was necessary to create 1976 data consistent with the EIA series. This was done by assuming that the relationship between the API/A.G.A. 

series and EIA series observed between 1977 and 1979 could also be applied to 1976. For instance, 

if EIA reported new field discoveries of oil in 1977-79 in a certain area as 120 percent of those reported 

by API/A.G.A., the API/A.G.A. new field discovery of oil in 1976 was multiplied by 120 percent to extrapolate the EIA series back to 1976. 

As seen in Table 3, estimates of ultimate recovery from new fields discovered between 1976-79 vary 

considerably among data sources. Generally, the API/A.G.A. ultimate recovery by year of discovery (columns 1 and 2) and the API/A.G.A. annual new fields series (columns 3 and 4) are similar. The EIA data 

for oil is similar to both API/A.G.A. series, but the EIA gas figures are in many cases much higher than 

either of the API/A.G.A. estimates. 

In general, the results obtained from the GRI Hydrocarbon Model in terms of barrel of oil equivalent of 

oil and gas fall within the ranges observed in the published data. The model, however, would appear 

to overstate oil discoveries relative to gas. 

Model Results 

Two sets of model results are presented in this paper, one from the "producer" perspective and the other 

from the "gas purchaser" perspective. In the "producer" perspective mode, the GRI Hydrocarbon Model 

calculates trends in natural gas production and costs based on "producer" expectations of oil and gas 

selling prices. In the "gas purchaser" perspective mode, the model calculates natural gas production 

and cost trends which result when purchasers seek to obtain a particular level of natural gas supply under 

a particular set of producer price expectations. It must be stressed again that the results presented here 

are not intended to be projections of natural gas or oil production and costs. Rather these are results 

of test runs chosen to illustrate the operation of the model and the interrelations between oil and natural 

gas production and prices. 

In discussing the results of the GRI Hydrocarbon Model, one caveat should be kept in mind. The oil 

production trends calculated by the model do not include any oil production from enhanced oil recovery 

(EOR) of oil-in-place beyond that indicated by USGS estimates and DOE reserve estimates. Because 

the future recoverability of oil-in-place will probably increase over that estimated by USGS and DOE, 

the impact of incremental EOR activities on oil production trends could be significant. For example, according to GRI calculations, in the 1970s over half of the lower-48 oil reserve additions resulted from 

increased recovery of oil-in-place. It is reasonable to expect that the inclusion of incremental EOR activities beyond those implied by USGS and DOE estimates would result in higher production than that 

calculated by the GRI Hydrocarbon Model. 

GRI plans to include the effects of incremental EOR activities on the trends in hydrocarbon production 

and costs in the 1983 Hydrocarbon Model development program. The introduction of EOR into the GRI 

12 
- i . 

• 

' 

Table 3. Comparison of Ultimate Recovery of Fields Discovered 1976-79 from Model Results and 

A 

B 

C 

D 

E 

G 

HI 

JN 

JS 

L 

Various Data Sources 

Model Region 

East 

FL, MS, AL 

Midwest 

N. LA, N.E. TX, AR 

S. LA, Onshore 

S. TX, Onshore 

West 

Mid Continent 

Permian Basin 

Pacific Coast Onshore 

EGO Gulf Offshore 

CO Pacific Offshore 

• Total Lower-48 

Total Lower-48 BOE X 106 

Ultimate Recovery 

by Year of Discovery 

API/A.G.A. 

Gas 

(Bef) 

1,075 

1,520 

928 

3,490 

2,060 

3,420 

3,740 

2,515 

1,020 

205 

14,590 

300 

34,880 

Oil 

(Million bbl) 

7 

49 

129 

150 

43 

66 

452 

140 

126 

28 

236 

326 

1,752 

7,751 

Annual New Fields 

API/A.G.A. 

Gas Oil 

(Bef) (Million bbl) 

225 10 

1,895 56 

1,155 127 

3,035 184 

2,989 ' 40 

3,640 63 

2,865 412 

2,010 209 

1,400 142 

285 80 

14,200 440 

425 925 

34,120 2,688 

8,556 

Extrapolated 

EIA Annual New Fields 

Gas Oil 

(Bef) 

635 

1,275 

1,205 

2,655 

7,120 

5,265 

5,830 

6,890 

3,055 

340 

22,375 

505 

57,150 

(Million bbl) 

10 

75 

207 

85 

55 

91 

436 

249 

194 

20 

835 

219 

2,476 

12,305 

• 

Model Results 

Gas 

(Bef) 

473 

1,047 

300 

2,692 

3,666 

3,565 

5,605 

3,018 

1,118 

473 

13,995 

276 

37,000 

Oil 

(Million bbl) 

28 

224 

230 

185 

78 

151 

581 

320 

314 

174 

677 

183 

3,145 

9,509 

-
P.15 

Hydrocarbon Model will increase lower-48 oil production, but, because the price of hydrocarbons and 

pil in the model are set by the marginal new field resource discovery and expected world oil prices, the 

inclusion of EOR is not expected to impact either resource or oil-based prices. 

Producer Perspective Results 

The target prices for oil and gas used in the test runs to represent the producer price expectations are 

shown in Table 4. The low oil price track is consistent with recent reduced expectations of world oil price 

trends, while the high price track is based on the mid-range National Energy Policy Plan IV study. There 

are two different gas price tracks used for each oil price trend. The gas price tracks are set at 55 percent 

and 75 percent of the expected oil price. 

Table 4. Target Hydrocarbon Prices 

High Oil Prices 

1980 

1985 

1990 

1995 

2000 

Low Oil Prices 

1980 

1985 

1990 

1995 

2000 

Oil Price 

(1982$/BBL) 

34.80 

32.50 

42.50 

51.33 

62.00 

34.80 

29.97 

33.09 

36.55 

40.34 

Gas Price 

(1982$/MMBtu) 

55 Percent 

3.30 

3.08 

4.03 

4.87 

5.88 

3.29 

2.84 

3.14 

3.47 

3.83 

75 Percent 

4.50 

4.20 

5.50 

6.64 

8.02 

4.50 

3.87 

4.28 

4.72 

5.22 

The effects of oil price expectations on lower-48 hydrocarbon production trends when gas prices are 

expected to be at 75 percent of oil prices on a Btu basis are shown in Figure 7. The following general 

observation can be made about Figure 7: 

• Natural gas production can remain over 20 Tcf throughout the 1980s for both the high and low oil 

price cases. This is a result of the domination of natural gas production by gas fields discovered through 

1980. Natural gas production declines steeply in the 1990s as production from the pre-1981 fields 

declines and the find-rates for new gas fields fall as the resource base is depleted. 

• While there is less than a one quad difference between the two natural gas production trends by 1990, 

the difference widens to almost three quads by 2000. Thus, natural gas production in the 1980s appears relatively insensitive to producer oil price expectations. In the 1990s, however, natural gas production is quite oil price sensitive. 

• The trends in oil production (with no incremental EOR production included) through 1990 show very 

little sensitivity to oil prices. While oil production in the 1990s is more sensitive to producer oil price 

expectations, it is not as sensitive in this price range as natural gas production. 

• The steep declines in oil production estimated by the GRI Hydrocarbon Model indicate that incremental EOR will be a very critical factor for future oil production. The extent to which the decline in oil 

production can be slowed will depend on the economic attractiveness and technical success of 

incremental-EOR activities to increase recovery of oil-in-place above that currently estimated. 

It is apparent from Figure 7 that, given the exploration activity trends since the mid-1970s, the hydrocarbon industry could produce far more natural gas in the 1980s than many projections indicate gas markets 

would absorb. If gas production were constrained by lack of demand, this implies some slowing in the 

rate of development and production of gas fields discovered through 1982 and/or a slowing in exploration activity to discover new fields. 

14 
P.16 

PRODUCTION (QUADS) 

24.0-f 

22.0' 

20.0 — 

18.0 — 

16.0 — 

14.0 -

12.0 -

10.0 -

8.0 -

Gas Production 

Oil Production 

i 

1975 

1^ 

1980 

T 

1985 

1 ^ 

1990 

1 ^ 

1995 2000 

Figure 7. Effects of Oil Prices on Hydrocarbon Production (Gas Prices = 75% Crude). 

The trends shown in Figure 7 are based on producer expectations that gas will be sold at 75 percent 

of crude. Wellhead gas prices, however, might have to be as low as 55 percent of crude prices to maintain gas competitiveness. Lowering the producer expectations for gas prices will not only lower natural 

gas production, but it will also lower crude oil production because both crude oil and natural gas finds 

pay for hydrocarbon exploration. Lowering the expected gas price lowers the economic cut-off point for 

new gas field development and lowers the rate of return on exploration activity, thus reducing the amount 

of oil and gas reserves and production. 

Figure 8 shows the effects of lowering producer expectations for lower-48 natural gas prices from 75 

percent of crude prices to 55 percent of crude prices. In both cases the high oil price track is assumed. 

The following observations can be made: 

• Lower-48 natural gas production begins to decline before 1985 as a result of lowered producer gas 

price expectations. In the 1990s, natural gas production in both cases declines by almost the same 

amount. 

15 
P.17 

• For the range of oil and gas prices considered, the sensitivity of natural gas production in the 1980s 

is essentially the same whether the producer expectations change for gas prices or for oil prices. 

In the 1990s, natural gas production is more sensitive to the change in expected oil prices than to 

the change in expected gas prices. 

• The lowered gas price expectation results in a production decline of about one quad by 1990; between 1990 and 2000 there is virtually no additional incremental loss. 

• Because of lowered producer expectations for gas prices, oil production declines by about 100,000 

barrels per day by 2000. 

• The production trends for oil show a greater sensitivity to producer expectations for gas prices through 

1990, but a greater sensitivity to producer expectations for oil prices in the 1990s. 

PRODUCTION (QUADS) 

21.0 - f 

22 0 

20.0 — 

18.0 

16.0 — 

14 0 -

12.0 -

10.0 -

Oil Production 

i 

1975 

I 

1930 

T 

1985 1990 1995 2000 

Figure 8. Effects of Gas Price Expectations on Hydrocarbon Production (High Oil Prices). 

The figure indicates that oil and gas producing companies collectively must be viewed as hydrocarbon 

producers. By depressing gas prices, a producer might enhance his ability to sell gas, but by reducing 

his gas revenue, his rate-of-return on exploration would decline, thus reducing his oil production and 

revenues as well. Thus, it would appear that producers would seek to maximize hydrocarbon revenues 

by selling both oil and gas, not one in preference to the other. 

16 
Reserve additions for new field discoveries are sensitive to price. Table 5 summarizes reserve additions 

in new fields (i.e., those discovered from 1976 to 2000) for natural gas and oil in the four price scenarios. 

Note that the quantity of oil reserve additions is dependent not only on the expected price of oil but also 

on the expected price of gas. Among the scenarios, oil reserve additions in post 1975 fields range from 

16.2 billion barrels to 20.3 billion barrels. Reserve additions of natural gas range from 174 Tcf to 240 Tcf. 

Table 5. 

Price See 

"Low 55" 

"Low 75" 

"High 55" 

"High 75" 

Lower-48 Reserve Additions in 

>nariob 

Post-1975 Fields (1976-2000)

a 

Natural Gas Oil 

(Tcf) 

174 

203 

220 

241 

663 

(Billion bbl) 

16.2 

18.0 

19.5 

20.3 

Natural Gas 

as Percent of Total Oil 

and Gas Hydrocarbons0 

64.8% 

66.0% 

66.0% 

67.2% 

Underlying Resource Base Assumption 

55.5 66.0% 

a

 Excludes 94 Tcf of gas and 10.8 billion barrels of oil projected to be added in this period from pre-1976 fields. 

Refers to the percentages of expected gas prices relative to expected world oil prices on a Btu basis. 

c

 Calculated on a Btu basis. 

Directionality of drilling between oil and gas is shown for the four cases in Table 5. When gas is priced 

at 55 percent of oil, gas makes up 64 to 66 percent of the hydrocarbons discovered. When the gas price 

rises to 75 percent of oil, the portion of hydrocarbon reserve additions made up of gas increases to 66 

to 67 percent. By way of comparison, the underlying resource base developed for the model is 66 percent gas. Table 5 would appear to indicate that, over the range of prices considered in these four scenarios, 

the directionality of hydrocarbon exploration is determined more by the distribution of the remaining undiscovered fields between oil and gas than by the relative prices of oil and gas. 

Determining the wellhead price for natural gas is a highly complex process. Within the context of the 

target prices (producer expectations) and the resource cost for new hydrocarbon discoveries, a wide 

range of natural gas wellhead prices can be derived. Table 6 shows three concepts for developing natural 

gas prices using relationships in the GRI Hydrocarbon Model: 

1. The target oil and natural gas prices which the producer expects to get before undertaking the next 

increment of exploration activity. 

2. The resource cost, which is the average price the hydrocarbons discovered in the next exploration 

increment (oil and gas) would have to sell for if the producer is to realize a 10 percent real rate of 

return after taxes. The resource cost of gas is calculated with gas sharing exploration costs with oil 

in proportion to the relative amounts found of each hydrocarbon. 

3. The "oil derived" natural gas price, which is the price of natural gas sufficient to provide the "desired" 

producer return when oil prices are set equal to the higher of the target oil price (derived from a projected world oil price) or marginal resource cost. In this scheme, oil absorbs as much of the exploratory 

costs as possible, given the market price for oil, and the gas price can be less than the oil price. 

The oil-derived gas price also can be viewed from two different perspectives, which represent the range 

of gas prices under differing contracting procedures. They are: 

1. Marginal price. This is the weighted average marginal price of gas from all fields discovered in that 

year. If this were used as the average price for natural gas, it would imply that all contracts included 

a "most favored nation" clause permitting prices for flowing gas to escalate annually to the marginal 

price of new gas fields. 

17 
P.19 

Table 6. Natural Gas Prices (1982 S/MMBtu) 

Scenario 

"Low 55" 

1985 

1990 

1995 

2000 

"Low 75" 

1985 

1990 

1995 

2000 

"High 55" 

1985 

1990 

1995 

2000 

"High 75" 

1985 

1990 

1995 

2000 

Natural Gas Prices 

Target 

Oil 

5.17 

5.71 

6.30 

6.96 

5.17 

5.71 

6.30 

6.96 

5.60 

7.33 

8.85 

10.69 

5.60 

7.33 

8.85 

10.69 

Prices 

Gas 

2.84 

3.14 

3.47 

3.83 

3.87 

4.28 

4.72 

5.22 

3.09 

4.03 

4.87 

5.88 

4.20 

5.50 

6.64 

8.02 

Resource Costs 

3.45 

4.19 

4.81 

5.19 

3.88 

4.72 

5.46 

5.92 

3.82 

5.09 

6.33 

7.26 

4.20 

5.71 

7.06 

8.22 

Oil-Derived Prices 

Marginal 

2.63 

3.33 

3.91 

4.09 

3.27 

4.20 

4.98 

5.32 

2.96 

3.90 

4.96 

5.32 

3.55 

4.92 

6.14 

6.73 

Vintage 

2.48 

2.68 

3.04 

3.44 

2.67 

3.09 

3.69 

4.33 

2.57 

2.93 

3.59 

4.31 

2.76 

3.39 

4.33 

5.32 

2. Vintage. This price assumes that gas from each newly discovered field will continue to be sold until 

depletion at the real marginal price prevailing for that field at the initiation of production. If this were 

used for the average price of natural gas, it would imply that no escalation in contract prices would 

be allowed in excess of the inflation rate. 

Table 6 shows that the resource-based price of natural gas—that is, the price based on the hydrocarbon 

resource cost—is consistently above the target gas price. Because the resource cost is well below the 

target oil price, however, the new oil discoveries can be used to cover some of the gas exploration costs. 

The resulting marginal oil-derived gas prices in the high oil price scenario are generally below the target 

gas prices in the high oil price scenario. This indicates that, in the high oil price scenario, it would be 

possible to keep marginal gas prices, on the average nationwide, between 55 and 75 percent of the target 

oil prices and achieve the expected production trends. If gas supply contracts were vintaged, however, 

the average oil-derived gas price for flowing gas could be kept below 50 percent of expected oil prices. 

The low oil price scenarios, however, are a different story. Although oil revenues can "subsidize" gas 

prices through 2000 when target gas prices are 55 percent of oil, the oil-derived marginal natural gas 

prices exceed 55 percent of oil prices from 1990 on. By 2000 in the low oil price, 55 percent gas price 

scenario, the oil-derived marginal natural gas price is at 59 percent of the target oil price. In the 75 percent scenario, the oil-derived marginal gas prices also exceed the 75 percent target price after 1990, 

but by a very small amount. However, vintaging the price of flowing gas could keep the average gas 

prices well below the target gas prices. 

Table 6 indicates that merely viewing natural gas prices from the perspective of marginal prices could 

significantly overestimate the trends in the average price of all flowing gas. While it is unlikely that contracts can be signed with the perfect vintaging shown in Table 6, it is equally unlikely that contracts will 

be signed with 100 percent "most favored nation" clauses which would allow continual upward escalation of flowing gas prices to the price of new gas contracts. The marginal and vintage prices in Table 

6 indicate a range over which flowing gas prices could vary. "Market out" provisions, moreover, might 

limit the escalation of prices for flowing gas. The size of the range indicates that the gas contracting 

procedures could have a major impact on the future trends in gas prices. 

18 
P.20 

Gas Purchaser Perspective 

The previous calculations in all scenarios result in trends for natural gas production in the 1980s significantly higher than many current projections of potential gas consumption in the 1980s would appear to require. Deferring some of this "gas bubble" to the 1990s would tend to moderate the long-term decline 

in lower-48 natural gas production as well as the rise in gas prices in the future. Accordingly, a run was 

made from the "gas purchaser" perspective, targeting gas production along a more conservative path. 

The target oil prices used in the run are from the low price scenario shown in Table 4. Gas prices are 

targeted at a very high level—only $3.00 per BOE below oil prices—under the assumption that this is 

the maximum price of gas relative to oil at which gas could conceivably maintain its competitiveness. 

Figure 9 shows the trends in hydrocarbon production for both perspectives. The producer perspective 

run shows that lower-48 natural gas production remains over 20 quads through 1991 and declines steeply after 1990. By 2000, production is projected to decline to 14.6 quads. However, the gas purchaser 

perspective scenario is constrained to yield a steady decline in production from 20 quads in 1980 to 

16 quads in 2000. Constraining exploration to eliminate the potential "gas bubble" in the 1980s results 

in similar trends in oil production. 

PRODUCTION (QUADS) 

24.0-i 

22.0-

20.0-

Figure 9. Lower-48 Hydrocarbon Production Trends (Producer vs. Gas Purchaser Perspective). 

19 
P.21 

Figure 10 shows the trends in marginal resource costs for both perspectives along with the target oil 

prices. In the early years, the resource cost is generally lower than the target price (assumed market 

price) of oil for each scenario in Figure 10. Because of the effect of resource depletion, the hydrocarbon 

resource cost rises and, by the mid to late 1990s, overtakes or exceeds the assumed market price for 

oil. If the hydrocarbon resource cost were set equal to the target oil price, the producer's rate of return 

would fall below the 10 percent set in the model. 

1982 DOLLARS PER MMBTU 

9.00 -p-BB__a-B_ M 

1.00 -

7.00 — 

6.00 — 

5.00 — 

4.00 — 

3.00 • 

2.00 -

1.00 -

0 - J 

Target 

Oil Price 

Producer 

Perspective 

Resource Cosl 

Gas 

Purchaser 

Perspective 

Resource Cos! 

I 

1975 1980 1985 1990 

1 ^ 

1995 

r 

2000 

Figure 10. Hydrocarbon Resource Price Trends (Producer vs. Gas Purchaser Perspective). 

Figure 11 shows the trends in the marginal and the vintage natural gas prices for both perspectives along 

with the target oil prices. It also indicates that: 

• In the 1980s, constraining new exploration activity in order to reduce gas production will result in 

a significant decrease in marginal natural gas prices. 

• In the 1990s, however, as exploration activity is accelerated to hold the decline in lower-48 natural 

gas production steady, the marginal natural gas price in the gas purchaser scenario begins to rise 

very steeply, until, by the mid-1990s, it exceeds the marginal natural gas price in the producer scenario. 

This comes about because the exploration activities in the gas purchaser scenario require the 

20 
P.22 

discovery of more new gas fields to maintain gas production at 16 Tcf in 2000 than would have to 

be discovered in the producer scenario. 

1982 DOLLARS/MMBTU 

9.00-f 

1.00 • 

7.00 -

6.00 -

5.00 -

4.00 -

3.00 -

2.00 • 

Target 

Oil Price 

°-T1975 

MARGINAL: Weighted average price of all fields 

discovered in given year. Upper limit for flowing gas 

prices corresponding to 100% most favored nation 

contracts. 

VINTAGE: Newly discovered gas continues to be sold at 

original real marginal cost until depletion of field. Lower 

limit for flowing gas prices corresponding to no escalation 

of contract prices in excess of inflation. 

i 

1980 1985 

l 

1990 

I 

1995 2000 

Figure 11. Lower-48 Hydrocarbon Prices (Gas Purchaser vs. Producer Perspective: Intermediate 

Oil Prices). 

Additional Work Planned with the GRI Hydrocarbon Model 

This paper has outlined the basic structure of the initial form of the GRI Hydrocarbon Model and has 

presented test results. Over the next year, several improvements will be made in the model's structure 

and data. 

• The find-rate equations used in the model will be modified to better replicate exploration experience. 

EEA has developed a modification to the Arps-Roberts equation that incorporates improvements in 

the theory behind the equations and tends to fit the observed data more closely. The equations used 

in the model will be modified using this improved find-rate function. 

21 
P.23 

• The GRI Hydrocarbon Model will be integrated into the EEA National Pipeline Integration Model. 

• This will allow the tracking of "old" price-controlled gas production and pricing over time and will enable 

the model to convert regional wellhead prices into delivered end-use prices by consuming sectors 

and regions. 

• Currently, exploration constraints in the model are exogenously specified based on past drilling trends. 

Development drilling is derived from exploration success, that is, the wells necessary to develop what 

is discovered. In 1983, exploration and development drilling activity will be explicitly linked to the 

industry cash flows in the model. This will provide a more realistic framework for modeling drilling 

constraints based on industry capital limitations. 

• The costs to develop natural gas in tight sands will be explicitly calculated within the GRI Hydrocarbon Model framework. This work will utilize the results of the Tight Gas Analysis System currently 

being developed by GRI. Currently, the model characterizes fields as either oil or gas. The modified 

model will have three field categories: oil, conventional gas, and tight gas. 

• Oil production resulting from incremental EOR activities will be included in the calculations of the 

trends in oil production and costs in the GRI Hydrocarbon Model. These calculations will depict both 

economic costs of this production as well as assumed trends in EOR technology development. 

In addition to these changes in the model's structure and data, the model will be made more accessible 

to interested parties. This will be done by adding a preprocessor to the model to allow someone with 

limited computer experience to set up and run the model. 

22 
P.24 

References 

•t/ 

1. Richard Nehring, The Discovery of Significant Oil and Gas Fields in the United States. Santa Monica, 

CA: The Rand Corporation, 1981. 

2. American Petroleum Institute, Petroleum Facts and Figures. Washington, DC: API, 1971. 

3. A.W. McCray, Petroleum Evaluations and Economic Decisions. Englewood Cliffs, NJ: Prentice-Hall, 

Inc., 1975. 

4. American Petroleum Institute, American Gas Association, and Canadian Petroleum Association, 

Reserves of Crude Oil, Natural Gas Liquids, and Natural Gas in the United States and Canada as 

of December 31, 1979. Washington, DC: API/A.G.A., 1980. 

5. United States Department of Energy, Energy Information Administration, U.S. Crude Oil, Natural Gas 

and Natural Gas Liquids Reserves. Washington, D.C: DOE, 1982. 

23