IMBSIR 80-2044 (DoE)

An Annotated Restatement of the

Midterm Oil and Gas Supply

Modeling System Methodology

Karla L Hoffman

Lambert S. Joel

Center for Applied Mathematics

National Bureau of Standards

U.S. Department of Commerce

Washington, D.C. 20234

July 1980

with portions contributed by:

Charles Everett*

Steve Muzzo**

William Stitt**

*Energy Information Administration, Department of Energy, Washington, D.C.

**ICF, Inc., 1850 K Street, N.W., Washington, D.C.

NBSIR 80-2044 (DoE)

AN ANNOTATED RESTATEMENT OF THE

MIDTERM OIL AND GAS SUPPLY

MODELING SYSTEM METHODOLOGY

Karla L Hoffman

Lambert S. Joel

Center for Applied Mathematics

National Bureau of Standards

U.S. Department of Commerce

Washington, D.C. 20234

July 1980

with portions contributed by;

Charles Everett*

Steve Muzzo**

William Stitt**

*Energy Information Administration, Department of Energy, Washington, D.C.

**ICF, Inc., 1850 K Street, N.W., Washington, D.C.

U.S. DEPARTMENT OF COMMERCE, Philip M. Klutznick, Secretary

Luther H. Hodges, Jr., Deputy Secretary

Jordan J. Baruch, Assistant Secretary for Productivity, Technology, and Innovation

NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director
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TABLE OF CONTENTS

LIST OF FIGURES iii

LIST OF TABLES iv

PREFACE V

ABSTRACT vii

I. INTRODUCTION 1

II. THE OIL SUPPLY PROCESS 5

II. 1 The Reservoir 5 11. 2 The Reservoir Investment Decision 10

11. 3 Exploration Versus Development 11

11. 3.1 Proved Reserves 11

11. 3. 2 Indicated Reserves 12

II. 3. 3 Inferred Reserves ....12

II. 3. 4 Undiscovered Reserves 14

III. OVERVIEW OF THE OIL SUPPLY MODELING SYSTEM 16

IV. THE RESOURCE SUBMODEL (TRANSLATING THE RESOURCE BASE INTO

PRODUCTION) 18

IV. 1 Production From Existing Fields 18

IV.

2

Discovery and Production from New Fields; Finding Rates 27

IV.

3

Production and Coproducts of Oil 36

V. THE ECONOMIC SUBMODEL (CALCULATING MINIMUM ACCEPTABLE PRICES) 37

V.l The Minimum Acceptable Price Calculations.... 40

V.1.1 Investments Which Must Be Capitalized 42

V.l. 2 Investments Which Can Be Expensed 45

V.l. 3 Cash Expenses 46

V.l. 4 Non-Cash Expenses 49

V.l. 5 Tax Credit 50

V.l.

6

Calculating Total Cost and Minimum Acceptable Price.... 51

VI. THE DRILLING SUBMODEL (CONSTRUCTING THE DRILLING PROFILE AND

REGIONAL ALLOCATION) 53

VI. 1 Constraints to Drilling in the Offshore Region 53

VI.

2

Calculating a Cumulative Exploratory Drilling to Minimum

Acceptable Price Curve 60

1
VI. 3 Calculating the Regional Drilling Profiles 63

VI. 3.1 The Equations of the Drilling Submodel 65

VI. 3. 2 Discrepancies Between Code and Documentation in

the Drilling Submodel 74

VII. THE OTHER MAJOR MODELING SYSTEMS 78

APPENDIX A - THE RESOURCE BASE SUBMODEL INPUT DATA 79

APPENDIX B - THE ECONOMIC SUBMODEL INPUT DATA 90

APPENDIX C - DISCOUNTED CASH FLOW CALCULATIONS 112

REFERENCES 114

ii
1

2

3

4

5

6

7

8

9

10

11

2

4

6

8

13

16

19

21

23

33

61

LIST OF FIGURES

1985 Oil Supply, Western Gulf Basin

Estimation Process for Oil Supply

Activities and Events of One Reservoir

Reservoir Life Cycle

U. S. Resource Base

Regional Boundaries for Oil and Gas Model

Translating the Resource Base into Production Activities

Offshore Oil Production Profiles

Hubbert's Percentage of Total Ultimate Recovery

Proved as Reserves

Translating Oil-in-Place to Reserve Additions

Ultimate Exploratory Drilling as a Function of Price

iii
LIST OF TABLES

TABLE 1 Cash Flow Categories 39

TABLE 2 Outer Continental Shelf Leasing Schedule 54

TABLE 3 Oil/Gas Lease Acreage Split 55

TABLE 4 List of Environmental Impact Statement Reports

Used in the Model 56

TABLE 5 Oil Lease Acreage Exploratory Drilling Schedules 56

TABLE 6 Well-Density Factors 57

TABLE 7 Initial Depth 58

TABLE 8 Total to Exploratory Ratio Calculation 59

iv
PREFACE

Under contract to the Office of Analysis Oversight and Access, the Operations

Research Division of the National Bureau of Standards was charged with the de~

velopment of methodologies for the assessment of energy models. The Midterm

Oil and Gas Model (MOGSM) was to be used as the vehicle for testing these

methodologies.

A natural first task was to read the documentation related to this model in

order to obtain an understanding of the methodology and mathematics of the

model. The tasks of assessing the MOGSM documentation and developing and

testing generic guidelines for energy model documentation took place concurrently. The results of this research are reported in [13].

One conclusion of this documentation assessment was that the existing documentation for MOGSM did not contain information sufficient for us to obtain a thorough understanding of the mathematical/logical structure of the model.

However, through many discussions with the model developers, the structure of

the model was exposed and the model assessment activities continued. Since a number of people were involved in a variety of assessment tasks, we decided to

produce an internal document describing the model's mathematical/logical

structure as we understood it. This document is an outgrowth of that activity.

We note, however, that notwithstanding the overall inadequacy of the model

documentation, substantial portions of this report were extracted with minor

emendations, from the existing model documentation. The authors of those reports, whose names are listed on the title page of this one, supplied additional contributions through conversations and letters.

We never intended as model assessors to supplement the "primary" documentation

of the model we were assessing, especially since our major concern is the development of assessment methodology, not the actual assessment of the model.

However, the need for at least an internal document became apparent. As the

production of this document progressed, we realized that this activity was advancing our general methodology-development goals. It clarified and synthesized many of our notions about documentation which later were incorporated

into the guidelines presented in [15] and reinforced the recommendations presented in that report. We also believe that the existence of this report will

help advance the most important by-product of proper model assessment—that of

making the models more "transparent", i.e. more open to peer review and more

understandable to policy makers who rely on information produced by models.

V
A number of caveats must, however, accompany this document. MOGSM consists of

three submodels: the Economic Submodel, the Resource Base Submodel, and the

Drilling Submodel. Descriptions of both the Economic Submodel and the Resource Base Submodel are based on the verbal descriptions provided by the model developers. No computer code listings were examined to see if there were

discrepancies between the structure described by the modelers and the computer

implementation. We have, however, requested the model developers to review a draft of this document to insure that what we have written is consistent with

their "conceptual" model.

On the other hand, information on the Drilling Submodel was obtained by reading the computer code labeled "OILDRL 78". This exercise uncovered discrepancies between the computer implementation and descriptions in either the existing documentation ul in verbal statements made by the developers. These discrepancies are noted in this report.

A major portion of the model and its methodology was totally undocumented at

the outset of the present exercise. Thus, the methodology used to detemine

the costs of exploratory and developmental drilling are presented for the

first time in this document, thereby allowing previously unavailable review of

this submodel.

It is a difficult task to document work performed by others and to record verbal explanations of a highly complex model. Furthermore, we do not believe

that the task is complete until the computer code of both the Economic Submodel and the Resource Base Submodel have been reviewed by a third party and

any discrepancies between the implementation and the "conceptual" model documented. We hope that this document will assist others in understanding the

mechanics of this model.

VI
ABSTRACT

The Midterm Oil and Gas Supply Modeling System is a computer model based on economic and engineering factors, that projects yearly domestic oil and natural gas production over a 30-year period. The regional oil and gas supply

curves developed by MOGSM are input to the Midterm Energy Forecasting System

(MEFS).

The Oil Supply Model consists primarily of three interconnected submodels: a Drilling Submodel that projects regional exploratory drilling on the basis of

information about the economic gradations of the resource base, the level of

future expected prices, and various constraints to exploratory drilling activity; a Resource Submodel that derives annual regional production quantities

based on exploratory drilling, the prospects for finding oil, the intensity of

development, the fraction of oil-in-place (OIP) which can be recovered by

either primary, secondary, or tertiary methods, and the fraction of proved re- serves which can be produced each year; and an Economic Submodel that calculates a minimum acceptable price for each year's quantity of reserves proved.

The Gas Supply Model produces supply projections for non-associated natural

gas and its coproducts and is identical to the Oil Supply Modeling System with

the following exceptions: gas finding rates are estimated as a function of

total drilling (exploratory and developmental) rather than exploratory drilling; the components of the oil model which represent enhanced recovery-

-secondary and tertiary processes —are not present, and the Gas Supply Model

has disaggregated the Eastern states into two regions.

Also included in the Midterm Oil and Gas Supply Modeling System is a Financial

Model which tabulates detailed costs and revenue information, calculated from

the economic model into regional income statements and selected balance sheet

items for the oil and gas producing industry. This model is used to determine

the capital expenditures necessary to provide the projected production quantities. It provides the capability to permit the MEFS oil and gas supply solutions to be translated into detailed schedules of oil and gas expenditures,

defined in terms compatible with the national income accounts.

KEYWORDS : Documentation of DOE supply model; economics of oil and gas supply;

gas supply; oil supply; resource modeling; supply projections.

vii
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MIDTERM OIL AND GAS SUPPLY M.ODEL ZliG S'fSZT',

DESCRIPTION

SECTION I: I^riRODUCTION

The Midtem Oil and Gas Supply Modeling Systen (MOGSM) uses conpu~er-based

nodeis vhich project the onshore and offshore supply of oil and natural gas

for the lower 43 states and for Alaska south of the Brooks Range. Tne forecasting procedure incorporates engineering and econonic factors to estinate

the supply of oil and gas.

Tne estinating procedure focuses on two najor areas: (1) cr-ade oil and the

coproducts of associated (and dissolved) natural gas and natural gas lituids

and (2) non-associated natural gas and natural gas liquids. Tne results of

the estimation are regional oil and gas supply cur^/es. Eigure I represents a

typical regional oil supply cuirve for 1985. These curves are part of the dat

base for the Departnent of Energy (DOE) Midterm Energy Forecast System ('dEFS)

MEFS uses a linear prograaniing technique to balance these supply estimates

with demand estimates for refined petroleum products and gas. MEFS also accounts for transportation, prices of imports, prices of alternative fuels, am

other factors (for a description of 1-G7S see : 46 ] )
Figure

1.

1985

OIL

SUPPLY

WESTERN

GULF

BASIN

(|8JJBq/SJB||op 9i6ll 30IIU

2

QUANTITY

|mb/d|
As a preview of Che more detailed discussion to follow, a flow chart of the

estimation process for oil supply is presented in Figure 2 (natural gas would

have an equivalent flow chart). The process consists of three separate estimating activities or sub-models: (1) estimation of future profitable drilling

levels; (2) estimation of new production from these drilling levels and old

production directly from currently booked reserves; and (3) economical graduation of new and old production to produce a supply curve.

This document describes the methodology used by the Department of Energy (DOE)

to estimate oil and natural gas supply curves for use by JiEFS. It first describes the key features of the oil and natural gas supply process simulated

in the estimation procedures. It next describes, in general terms, the model

used to project future oil supply as a function of various Federal and Corporate policy actions and market prices for crude. Finally, it discusses the

estimation of natural gas supply, highlighting the differences between it and

the oil supply estimation.

3
r igui ^ t— uoiimniiui^ rr\uuL.oo run uiu ourrui

Drilling Submodel
SECTION II. THE SUPPLY PROCESS

DOE projections of oil and gas supply are based on the economic and engineering factors which affect domestic oil and natural gas supply decisions. This

section describes the major features of this supply decision-making process.

For a more detailed description of the underlying process, see [10,11,17,21,

47].

The Oil Supply Model consists of an analytic framework which represents the

real-world activities and events associated with domestic oil exploration,

development and production. In particular, it includes the important economic

and engineering factors which are known to affect future production, as well

as the way these factors interact in oil supply decision making by private

firms. Since the basic investment decisions center mainly around individual

reservoirs, the discussion begins there.

II. 1 The Reservoir

A reservoir is a continuous, interconnected volume of rock containing oil and

gas as a hydraulic unit. The life cycle of a typical reservoir spans three

kinds of activities: exploration , development , and production (Figure 3).

Exploration converts "undiscovered resources" to discovered "oil-in-place";

development converts "oil-in-place" to "reserves"; and production brings "reserves" to the surface so they can be transported, refined and consumed. (Oil

and gas which has already been found and is considered producible under present prices and technology are known as "reserves.") These activities overlap

in time and, taken together, encompass the useful life of the reservoir from

time of discovery to time of abandonment (Figure 4).

*Throughout this report, the term "oil-in-place" will mean discovered "oil-inplace" rather than all existing resources (whether found or not yet discovered) .

5
ngure 3. ACTIVITIES AND EVENTS OF ONE RESERVOIR

72 Undiscovered — resources —

r

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Ij 1

-- Discovered — — oil in place —

I

I

I 1

Develop

I

!

I1

— Reserves —

It^ 1

I Produce !
The exploration process begins first, continuing until the reservoir's physical dimensions and other engineering aspects are determined sufficiently to

estimate the economic feasibility of recovering these resources. During this

period, the reservoir's total oil-in-place is continually reassessed until

this total approaches the limit of the ultimate discoverable resources present.

After exploration (and discovery), the development process begins with the

formulation of an initial plan to convert the deposit to reserves. As reservoir knowledge improves, the plan is modified to show more "proven” reserves,

until the economic limit of the reservoir is achieved and development ceases.

At this point, the cumu'lative amount of proven reserves has reached the level

ultimately recoverable under the economic and technological conditions expected to prevail over the reservoir's producing life.

As development begins to prove reserves, production commences. After development ceases, production declines over time, at a rate defined by the reservoir's physical properties and the intensity with which the reservoir has been

developed. When all of the reserves have been produced, the reservoir is

abandoned.

Tnere are three general methods of recovery corresponding to stages in oil

production. Early on, when the natural reservoir pressure is high, crude will

flow to the surface unaided; at this stage, production is classified as "primary recovery”. As more and more oil is produced the natural reservoir pressure is generally reduced. At some point, additional developmental investment

Ir

7
Discoverable

resources

9»

AUlNVnD 3AllVinNnQ

3
is necassary Co institute "secondar^^ recovery". Secondary methods

natural gas into the reser“/oir and/or inject vater to increase or n

reser^/oir pressure. Later, it nay be necessary to enploy nore rigo

phisticated (and costly) nethods. These processes are designed to

fron Che reseirvoir rock, and are referred to as "tertiary/ recovery"

niques.

(The technologies used Co produce shale or synthetic fuels are quit

ent. Since the production of these fuels is outside the scope of t

ing effort, no discussion of these technologies will be presented.

)

reintroduce

aintain

rous, 30 -

free oil

tech—

e differ—

his nodel9
II. 2 The Reservoir Investment Decision

Exploration, development, and production will be undertaken only when expected

oil prices (and natural gas prices, in the case of associated-dissolved gas)

are sufficient to yield a return on investment competitive with alternative

investments of similar risk. Typically, reservoir investments are evaluated

by means of a discounted cash flow (DCF) technique. The DCF technique considers the time value of money in comparing the cash expenditures and cash revenues of a reservoir investment. The basic variables are the expected costs

(including taxes and the costs of capital, discounted) to find, develop, and

produce a deposit; the expected time-profile of production from the deposit;

and the expected selling price for the reservoir's output.

One way to use the DCF technique is to calculate a "minimum acceptable price".

This is the lowest market price required to pay the costs associated with

finding, developing and producing a given quantity of reserves and, in addition, provide a competitive return on the capital employed. If the minimum

acceptable price for a particular reservoir is less than or equal to the market price expected in the future, the reservoir would be economically viable.

If, however, the minimum acceptable price is greater than expected prices, the

reservoir would not be a competitive investment.

In the early life of a reservoir, these economic evaluations are based on uncertain assumptions, incomplete data, and little actual experience with the

reservoir. Consequently, a reservoir usually is developed in stages. As

knowledge of the reservoir improves, the minimum acceptable price required for

additional development is repeatedly revised.

10
Once a reservoir’s economic viability is established, the operator will develop it to the point where incremental costs (which includes competitive return on capital) equal incremental revenues. For example, additional producing wells will be planned until the additional costs of one more well would

exceed the additional revenues that would accrue from it (including the time

value of money and the effects of such intensive development on the ultimate

recovery and production over time).

II. 3 Exploration Versus Development

Investments in oil supply can be allocated across different kinds of opportunities. For instance, investments can be made in exploration to discover new

oil reservoirs. Investments can also be made to increase the development of

known reservoirs. The range of choices can be illustrated by considering the

status of the domestic resource base. The resource base is analogous to a

complex inventory, organized along two dimensions (Figure 5). The first dimension distinguishes between discovered (identified) and undiscovered resources. A second distinction is between economic and subeconomic resources

with measured reserves being the most economic to develop, followed by indicated , inferred, and finally undiscovered resources in that order.

II. 3. 1 Proved Reserves

The most assured portion of the resource base is "proved” reserves. This portion has been discovered and is economically recoverable. Measured reserves

support today’s production. All or most of the developmental investment

11
needed to produce these reserves have been made. The additional cost of withdrawing these reserves will be small compared to the cost of locating, developing, and proving undiscovered resources.

II. 3. 2 Indicated Reserves

"Indicated" reserves are also reasonably assured of being produced in the future. Such reserves consist additional recovery from known reservoirs when

engineering knowledge and judgment indicate that secondary recovery is economically feasible. However, additional investment, e. g. in fluid injection

wells and equipment, is necessary to initiate production from indicated reserves.

II. 3. 3 Inferred Reserves

"Inferred" reserves are the last category within the discovered and economic

portion of the resource base. These reserves result from extensions and revisions of knowledge about reservoirs. Extensions arise through exploratory

drilling that extends the knowledge about the size of a deposit and the amount

of resource it contains by drilling outside the proven perimeter of a reservoir. Revisions usually arise from drilling and other experience within the

known perimeter of a deposit which provide new information concerning the reservoir's characteristics. Like indicated reserves, inferred reserves require

additional investment to initiate productions.

12
Rgure 5. U.S. RESOURCE BASE

identified | Demonstrated

Inferred i Undiscovered

Measured indicated 1

A

'•='*

^

=

- iii^^

Economic f^RESER.V

: R F n i r R'p'Fc f\ L O U U i\ U L O

I Sub- 1 Economic 1

1

1

t

Increasing (tegree of geologic assurance

13

Increasing

degree

of

economic

feasibility
II. 3. 4 Undiscovered Resources

Finally, "undiscovered" resources account for the remaining share of the resource base. These resources require the full range of exploration and development investment in order to initiate production.

For these four types of resources, the time required to increase oil production varies widely. Production from producing portions of known reservoirs

can be increased in the short run, but such additional production is usually

small. Increased development of discovered, but not fully developed portions

of known reservoirs yields more substantial results. Although production increases from increased development of known reservoirs may appear very quickly, the total impact of this development is usually spread over a three to

five year period. Finally, exploration produces large results over a much

longer period of time (five to twenty years), especially in areas remote from

known reservoirs.

This section has provided a very brief introductory description of the oil

supply process. For more detailed discussions see [10,11,17,21,47]. The next

four sections will describe the methodology of MOGSM.
SECTION III: OVERVIEW OF THE OIL SUPPLY MODELING SYSTEM

The United States oil producing areas considered by this model are divided into 14 regions whose petroleum-bearing lands are somewhat homogeneous. "These

regions correspond closely to province boundaries established in the American

Association of Petroleum Geologists (AAPG) Memoir 15 [Cram, 1971]. The numbering of these regions and the location of the boundaries generally conform

with those used by the AAPG and the National Petroleum Council (NPC)" (USGS Circular 725, p. 14). The 14 oil producing regions are shown in Figure 6 as Regions la,^ 2, 2a, 3, 4, 5, 6, 6a, 7, 8, 9, 10, 11 and 11a. Regions 8, 9 and 10

have been aggregated into one region for modeling oil supply. Regions 8 and 9

are combined in the gas submodel with region 10 becoming a separate region.

There are, therefore, 12 regions in the oil model and 13 in the gas model.

Other oil producing provinces, such as the North Slope and Alaskan Outer Continental Shelf (OCS) North of the Brooks Range, as well as tertiary recovery

and unconventional petroleum (synthetics and shale) are treated outside this

modeling framework in other DOE models (e.g., the Enhanced Oil Recovery Model

[43,44,45], and the Alaskan Hydrocarbon Model [38,39,40,41,42]).

The Oil Supply Model follows the process described in the preceding section.

It consists primarily of three interconnected submodels:

Resource Submodel - A model component that translates the following information into annual regional production quantities: exploratory drilling, the

prospects for finding oil, the intensity of development, the fraction of oilin-place which can be recovered by either primary or secondary methods, and

the fraction of proved reserves which can be produced each year.

^Region 1 includes both onshore and offshore petroleum-bearing lands south of

the Brooks Range. For modeling purposes. Region 1 is treated as an "offshore"

region.

15
Figure

6.

REGIONAL

BOUNDARIES

FOR

OILAND

GAS

MODEL

16

North

Slope
Economic Submodel - A model component which calculates a minimum acceptable

price associated with a given quantity of proven reserves.

Drilling Submodel - A drilling profile and regional allocation model component

which uses economic gradations of the resource base, expected price levels,

and constraints on exploratory drilling activity as a basis for projecting regional exploratory drilling.

These three submodels will be discussed separately with their interactions

noted. The first submodel discussed is the Resource Submodel, an engineering

simulation model which translates the resource base into production. This

model component forms the core of the modeling process.

17
SECTION IV. THE RESOURCE SUBMODEL (TRANSLATING THE ElESOURCE BASE INTO

PRODUCTION)

The Oil Supply Model estimates regional reserve additions and annual production quantities according to the U, S. Geological Survey Division of the domestic resource base (see Figure 7),

The dominant partition of the resource inventory is divided into identified

(known) and undiscovered resources —old fields and new fields. This division

represents principally the choice between exploration and development investment. The lesser separation involves the different types of recovery—primary

and secondary. This division represents the life cycle of reservoirs after

discovery and the short and intermediate run development intensity investment

choice. The methodology for translating the resource base into production in

old fields is different from that in new fields. This section will first describe the methodological approach used for estimating reserves in old fields

and then contrast that with the approach used in new fields.

IV. 1. Production from Existing Fields

The proved reserves segment of the resource base is the most assured, and

its translation into production quantities is easily achieved. Each region’s

reported reserve figure as of January 1 of the beginning year of the forecasts

is multiplied by a (constant) decline rate^ which represents the expected percentage of remaining reserves that will be produced for a given year. These

decline rates are based on historical data for each of the regions.

^We note that "decline rate" is the term used by DOE modelers to denote the

rate of production (extraction) of oil.

18
Figure

7.

TRANSUTING

THE

RESOURCE

BASE

INTO

PRODUCTION

ACTIVITIES

Aiinqjsea^ ojuiouooa aaj3ap Suisaajaui

o

C/J

19

Increasing

degree

of

geologic

assurance
The decline rates for onshore regions are approximated by the production-toreserves ratio. This production-to-reserves (?/R) ratio is estimated from the

last year of actual experience in each region, which can be obtained from data

published by the American Petroleum Council. Tables lA and 2A in Appendix A

of this report present the actual data used in the 1978 Annual Report to Congress for Initial Oil Reserves and Decline Rates, respectively. For the onshore region, peak production is assumed to occur the year after discovery and

to decline at a constant rate thereafter. (No production occurs the year of

the discovery.

)

Decline rates for offshore regions and for R.egion 1 (South Alaska) are handled

differently since lags between exploration and production typically exceed one

year. Consequently, a specific annual production profile is used for each of

these regions which recognizes these lags- and results in a gradual build-up of

the production levels from reserves. These production profiles are derived

using production and reserves data from Environmental Impact Statements prepared for the latest lease sales in each of these regions. As an example, the

production profile from new reserves in South Alaska (Region 1) might peak the

tenth year after discovery (Figure 8 and Table 3A of Appendix A present more

information about production profiles for offshore regions).

20
Rgure 8. OFFSHORE OIL PRODUCTION PROFILES (Percent)

21
The next most assured portion of the resource base consists of inferred and

indicated reserves. These are additions and extensions to known reservoirs

through additional drilling experience or through investments in fluid injection equipment. The USGS assessment of inferred and indicated reserves is

based on a procedure outlined by Hubbert. He developed multipliers that could

be applied to identified oil-in-place which would represent the growth (from

extensions, revisions, and new pays) in reported ultimate recovery over time

from known reservoirs (Figure 9). Although Hubert calculated multipliers on a

national basis, the Oil Supply Model applies these "Hubbert factors" to annual

discoveries since 1920 in each region and translates them into regional annual

reserve additions from the indicated and inferred categories in old fields.

Hubbert 's (1974) equations for estimating oil and gas ultimate recovery are as follows

Yy = Ultimate production,

= Y'j * M,

where;

T = elapsed time, in years, from the beginning of the year of discovery

of the reservoir;

Y^ = total past production plus the current estimate of the proved

reserves of the reservoir; and

M = the Hubbert Multipliers,

= 1/ [ l-e“0* 076(T + 1.053)]^^^^ fQ-j.

= 1/ [ 1-e”^* for gas.

22
Figure

9.

HUBBERT’S

PERCENTAGE

OF

TOTAL

ULTIMATE

RECOVERY

PROVED

AS

RESERVES

H0VlN33d3d

23

YEARS

AFTER

DISCOVERY
The Hubbert factors are used to predict the quantities of inferred reserves to

be added to old fields, based on the American Petroleum Institute (API) estimate of ultimate recovery found in their Reserves of Crude Oil, [3]. This exercise is performed outside the model and has the following steps:

o First, API state data on ultimate recovery (defined as cumulative

production to date plus current proved reserves) are aggregated

into NPC regluiis.

o Then, Hubbert equations are used to determine how these ultimate

recoveries will increase during successive 5-year periods. An example might clear up any confusion. In the Gulf of Mexico, fields

discovered in 1971 have an ultimate recovery of 298.5 million barrels after 7 years. The Hubbert oil equation would suggest that

the ultimate recovery after 12 years would be 298.5 times the ratio

of the Hubbert equation at year 12 and at year 7:

Year 12; 1 / [ i-g-O. 076( 12 + 1.503)] = 1.5585.

Year 7 : 1 / [ i-e“0*0^6(7 + 1.503)] = 2.1009.

ratio = 1.348

Thus, the ultimate recovery after 12 years would be 1.348 x 298.5 =

402., and 103.9 million barrels of reserves must have been added to

reach that ultimate recovery figure,

o A similar procedure is performed for all fields within a region

discovered since 1920, aggregated over fields discovered in a given

year. Estimates for all discovery years are summed to provide the

total reserves addition estimate for each 5 year period.

24
o Then the 5-year reserve addition estimates are divided by 5 and

then by the estimate of initial oil-in-place to derive the quinquennial factors used by the model. The model receives, as input,

these quinquennial factors,

o Since the Hubbert factors predict "ultimate recovery” from all

recovery methods (primary, secondary, and tertiary), these estimates include some oil obtained from tertiary recoverv. Tnerefore,

DOE estimates how much of this oil is tertiary (using the Enhanced

Oil Recovery Model [43,44,45]) and subtracts that amount from the

total.

Tables 4A and 5A of Appendix A present the Initial Oil-in-Place Data and the

Quinquennial Factors, respectively, used in the 1978 Annual Report to Congress (ARC). The quinquennial factors used in the 1978 ARC are those estimated for the 1977 ARC.

To summarize, the calculations performed for determining future oil production

in existing fields are as follows: (1) The Hubbert equations for estimating

ultimate oil recovery are used to provide an estimate of the reserve additions

for each year of the forecast; (2) Additions for any given year are added to

the existing oil-in-place at the beginning of that year; (3) Production is

then obtained by multiplying the oil reserves by the decline factor.

A number of assumptions are made when calculating oil production in

this manner. Some are presented below.

(1) For onshore regions, the decline rate is obtained by calculating

production-to-reserve ratios based on the last year of available

information. The implicit assumption imbedded in the approach is

25
that what the oil companies did that year represents the most economic way to extract proven reserves and that they will, therefore,

continue to produce at this rate.

(2) A decline rate (i.e. extraction rate), independent of price, implies

that oil proven in existing fields will be produced by both primary

and secondary methods at this rate and that neither intensification

of oil extraction efforts nor capping of wells for later withdrawal

are likely.^

(3) The Hubbert’s equation includes oil from inferred reserves. These

reserves result from extensions and revisions of known fields by additional exploratory drilling. However, the model assumes all exploratory drilling will take place in "new fields,” and only developmental costs are applied when evaluating the economics of developing old fields. Thus, the output from this model (the amount produced in a region) may overestimate the actual production for low

price scenarios, since the cost of producing oil in old fields will

be represented to be lower than it would actually be, because exploratory costs are not included.

(4) Hubbert obtained these factors by examining trends of past data aggregated to a national level. Using these estimates assumes that

what has happened in the past nationally will continue in the future

on a regional level and is independent of economics (i.e., the time

path for finding extensions and revisions is independent of price).

^The model developers were well aware that decline rates, development intensities, recovery factors, and other aspects of the process by which resources

are brought to market respond directly to economic factors. However, the data

upon which a price dependent relationship for these factors could be constructed were not available and they, therefore, chose to model using this

simplifying assumption.

26
IV. 2 Discovery and Production from New Fields; Finding Rates

The methodology for estimating projections of production from new fields is

more complicated than that used in old fields. Under an economically rational

drilling program, the more exploratory drilling performed the more likely one

is to find oil. However, since the largest reservoirs will usually be found

first, average reservoir-size discovered will continue to decline over time.

The model uses a "finding rate curve" as a mechanism for relating amount of

oil discovered to the amount of drilling performed, where the "finding rate"

is defined to be the measure of the quantity of oil resources "found" by drilling one exploratory foot.

The finding rate curve used in the model assumes that the relationship of cumulative oil-in-place discovered to cumulative exploratory drilling has the

following form:

COIP = Cumulative oil-in-place discovered

= Q (1-e-bCMFT)^ ( 1 )

where

uses Ultimate 1956 to 1974

Q = Recoverable Resources

uses Total Recovery Factor

+ cumulative oil-in-place

discoveries

;

CMFT = Cumulative exploratory drilling; and

b = Constant

27
The finding rate can be calculated by differentiating (1) with respect to

CMFT, yielding FR = d(COIP) = bQe"^^^^"^ . This finding rate function

d(CMFT)

states that the rate at which oil will be found will decline exponentially as

drilling progresses.

The variable Q in the above equation represents the upper limit of cumulative

discoveries and is defined to be total amount of oil already discovered, plus

the estimated quantity remaining to be discovered. It was decided, that for

this modeling effort, estimates of oil already discovered include the resources discovered between 1956^ and 1974 (the year of the USGS Circular 725

forecast). Estimates for remaining oil-in-place to be discovered were obtained by taking USGS Circular 725 [51] undiscovered recoverable oil estimates and

dividing those estimates by USGS estimates of total ultimate regional recovery

factors (Tables 9A and lOA of Appendix A present these primary and secondary

recovery estimates, respectively). It should be noted that the USGS excludes

resources beyond 200 meters water depth offshore. To compensate for the 200

meters depth constraint, the USGS offshore estimates were multiplied by 1.6

(except for the Alaskan offshore, where depths greater than 200 meters are not

expected to produce discoverable resources). This factor is based on the NPC

Ocean Petroleum Resources Report [29] which estimates that oil resources

beyond 200 meter water depth exceed by .6 the resources within 200 meters.

Data does not exist on a regular and reliable basis for years prior to 1956.

28
Finding rates for regions 2 through 10 (excluding region 2a) are based on

analysis of the historical relationship between cumulative exploratory drilling footage and cumulative oil-in-place. Linear regression analyses, performed outside the MOGSM computer code, are performed on a region-by-region basis

to fit a function of the form (2) shown below obtained by rearranging (1) and

taking logs.

In(Q-COIPt) = InQ-bCMFTt (2)

where

Q = uses ultimate recovery + 1956-1974 cumulative

recovery factor oil-in-place discoveries,

C0IP|- = cumulative oil-in-place discovered through time t,

CMFT^ = cumulative exploratory drilling through time t, and

b = constant.

The linear regression estimates the value of the constant b defining the shape

of the curve for each region. The analysis uses both historical data of oil

found per exploratory foot drilled and the USGS estimate of undiscovered resources in each region.

Cumulative oil-in-place discovered was selected as the dependent variable (before the log transformation) because it represents the total oil resource

present in the ground. As t approaches infinity, cumulative discoveries must

approach the amount of oil-in-place already discovered plus that remaining to

be discovered. Oil-in-place discoveries were obtained from the NPC study for

1966-69 [28]. For the years 1970-74, the source is the API Reserves of Crude

29
Oil [3]. Reserve additions due to exploration were determined, first, by summing New Reservoir Discoveries in Old Fields, New Field Discoveries and Extensions, as reported by American Petroleum Institute (API) [3]. Then, these reserve additions were converted into oil-in-place by dividing reserves by regional primary recovery factors. These factors were developed by the NPC for

each oil region and represent the proportion of oil-in-place that can be recovered using primary recovery methods.

The source of historical exploratory drilling is the NPC, U. S. Energy Outlook;

Oil and Gas Availability , for 1956-1969 [28]; (based on API drilling data).

For 1970-74, exploratory drilling is obtained from the API Quarterly Review of

Drilling Statistics [2]'. Consistent with the NPC, dry hole footage is allocated to oil according to the proportion of successful oil exploratory drilling

to total successful gas and oil drilling. For the specific data used for

these regressions, see Hirshfeld [18]. Tables 6A, 7A, and 8A of Appendix A of

this report collect the regression analysis results for the 1978 ARC, the initial finding rates, and the regression analysis results for the 1977 ARC, respectively.

The values of b, Q and (initial) values for CMFT are input parameters of the

MOGSM computer code. Finding rates for any value of cumulative footage drilled is calculated within MOGSM for regions 2 through 10 using the following

formula:

FR = bQe"bCM^'^

30
Finding rates for Regions 1, 2a, 11, and 11a cannot be calculated with the

above procedure due to historical data inadequacies. In these cases, the

finding rates are estimated using the following formula:

FR = finding rate (barrels per foot drilled)

= Q(l-e-[(Y/Q)*CMFT])^

where:

Y = initial finding rate (Y intercept or ordinate);

Q

= discoverable resources remaining in barrels; and

CMFT = cumulative exploratory drilling (in feet).

This calculation requires two data inputs. The initial finding rate, Y, is

the oil found during the first year of exploratory drilling. The remaining

discoverable resources, Q, is the USGS estimate of recoverable resources divided by the regional primary recovery factor. The input data to the model is

the variables b(where b=Y/Q) and Q.

Data from Environmental Impact Statements prepared for the most recent lease

sales in each of these regions are analyzed to determine the expected outcome

of the search process within the leased area and used to estimate the initial

point of the finding rate curve. Finding rates then are assumed to decline

exponentially to the point where all discoverable oil-in-place would be found.

Thus, to determine new field production, one begins by estimating parameters

of the finding rate curve for each of the onshore and offshore regions. These

parameters are input into the computer code MOGSM. MOGSM then calculates the

amount of oil-in-place discovered in that region by multiplying the annual regional exploratory drilling footage (from the drilling allocation section described later) by the finding rate. The model then translates oil-in-place to

31
reserves by using regional recovery factors (see Tables 9A and lOA, Appendix

A) for each recovery method on new fields. Regional time lags between discovery and each subsequent phase of development are imposed. The model assumes

all oil which can be extracted using primary recovery methods will be discovered the year the exploratory drilling takes place. Production will begin the

following year. ^ Similarly, all oil which can be recovered in the first phase

of secondary recovery will be found five years after the exploratory drilling

took place and production of that oil will take place in the sixth year. The

resulting pattern of reserve additions from new discoveries is shown in Figure

10 .

The reserves proved by-each of the recovery methods (primary and secondary)

are then produced according to the regional decline rates noted earlier.

A number of implicit assumptions were made when estimating the production of

oil from new fields using the methodology described above. These are collected below.

(1) In the DOE reports [36,37] that describe the methodology and data

sources for MOGSM it is stated that the finding rate curve-form in

the onshore regions "was selected to reflect the log-normal distribution of reservoirs in a field and was suggested by the theoretical

and empirical work of Kaufman [5,6,21] and Arps and Roberts [1]."

^The model has subsequently been modified to address the "vintaging of primary

production" issue. The reserve addition process in the model used for the

1979 ARC is spread out over a five-year period to reflect the gradual build-up

of reserves following a discovery.

32
Figure

10.

TRANSLATING

OIL-IN-PLACE

TO

RESERVE

ADDITIONS

33
These works examine whether pool sizes in a play (the terms "pools"

and "play" are technical, geological terms which are explained in

most texts on oil geology) are lognormally distributed and do not

examine the lognormality on a regional aggregation. For more analysis of this assumption, see [16].

(2) Included in the past data used to estimate finding rates are new

field discoveries, new reservoirs in old fields, and extensions to

old fields. The model will allocate all of this oil to new fields.^

(3) In regions 1, 2a, 11, and 11a the finding rate curve is based on two

data points: the initial finding rate Y (the oil found during the

first year of exploratory drilling) and the USGS estimate of remaining oil. This formula, like that used in regions 2 through 10,

reflects the assumption that the probability of a certain-sized

reservoir being found is proportioned to its size. When this assumption is translated into the deterministic equation used in the

model, the largest reservoirs are found first and cumulative finds

over time decline exponentially. However, having only one data

®The model developers maintain that the relationship between a given year's

OIP additions and that year's exploratory drilling (which has applied to

fields discovered over several years ) is a good proxy for the relationship

between the amount of oil-in-place which will be eventually added (probably

over several years) to a discovery taking place in a given year and the amount

of drilling these OIP additions will require.

34
point might make use of this formula specious. (The first year of

exploratory drilling might be relatively unsuccessful. Corrections

to this initial estimate should be made as more data becomes

available.

)

(4) The assumption that all oil which can be extracted using primary

recovery methods will be discovered the year the exploratory drilling takes place, and that all oil obtained by the first phase of

secondary drilling will be found five years later, has the effect of

overestimating oil production in the short term, since this methodology actually telescopes the discovery process.^

^As noted earlier, the model used for the 1979 ARC has corrected this deficiency; at present, reserve additions are spread out over a five-year period

to reflect the gradual build-up of reserves suggested by Hubbert.

35
IV. 3. Production of the Coproducts of Oil

Production estimates for the principal coproducts of oil wells (associateddissolved natural gas and associated-dissolved natural gas liquids) are projected using historical ratios. Historical data is used to develop a gas-oil

ratio for each region which is the ratio of the previous year's marketed

associated-dissolved wellhead gas production to the total oil production.

This factor sets the gas-oil ratio for the first year of the forecast. The

ratio expected at the end of the forecast period represents an engineering

judgment influenced by regional geology (particularly the ratio of remaining

undiscovered associated-dissolved gas and oil reserves) and the likely trends

of enhanced recovery techniques. Ratios for associated-dissolved natural gas

liquids are derived in a similar fashion.

Given the gas-oil ratio for the first and last years of the forecast, the modeling system calculates annual ratios by linear interpolation through these

end points. It then multiplies the quantity of each year's primary product

(oil in the case of associated-dissolved gas, and associated-dissolved gas in

case of associated-dissolved natural gas liquids) by the appropriate ratio to

calculate the coproduct production level. Table llA of Appendix A presents

the oil/gas ratios used for the 1978 ARC. For the scenarios described in that

report, the gas/oil rates for 1991 were the same as those given for 1978.

I 36
SECTION V; THE ECONOMIC SUBMODEL (CALCULATING MINIMUM ACCEPTABLE PRICES)

The second major part of the Oil Supply Model is the Economic Submodel which

estimates the minimum acceptable price associated with each reserve addition

(by region, by year, by type of recovery). Only that oil which has a selling

price greater than or equal to the minimum acceptable price will be produced.

The model assumes that the relevant costs are the incremental expenditures required to convert resources from their present state (measured, inferred, or

undiscovered) to the "proved" category and, subsequently, to produce them.

For example, the incremental costs of producing today's proved reserves (principally well-operating costs) are much less than the costs to produce undiscovered resources (exploration, development, and production investments, plus

well-operating costs).

In the model, each activity requiring expenditures has a cash flow category

associated with it. These cash flow categories form the basis for the minimum

acceptable price calculation (see Table 1). The basic computation of the minimum acceptable price associated with each reserve addition is through a discounted cash flow analysis (see Appendix C for a simplified description of the

basic calculations). All cost elements, including return on investment, are

discounted to a common year, as are all production quantities. Production

quantities are discounted to represent the time value of the revenues which

would accrue from the production over time. This discounted production quantity can then be multiplied by a price (which can be ramped—i.e., allowed to

37
increase a constant rate each year to reflect the price of oil increasing at a

rate faster than inflation) to provide discounted revenues. In this case,

discounted costs divided by discounted quantity equals the minimum acceptable

unit price (i.e., price per barrel) required to generate sufficient revenue

to cover costs plus provide a competitive return. A project, either exploratory or developmental, is included in the forecast only if its minimum acceptable price is less than or equal to the expected future market price.

38
TABLE 1. CASH FLOW CATEGORIES

INVESTMENT EXPENDITURES (Expensed)

Dry holes

Successful wells (intangible portion)

Lease rentals

Preproduction overhead

INVESTMENT EXPENDITURES (Capitalized)

Lease bonus

Successful wells (tangible portion)

Preproduction geological/ geophysical

Gas plant

Other lease equipment

Environment/ safety

GROSS ANNUAL REVENUES

Crude oil

Associated and dissolved natural gas

Natural gas liquids

ANNUAL EXPENDITURES

Producing well and lease operating

Gas plant

Production geological/ geophysical

Production overhead

Royalties

Ad valorem and severance tax

Federal/state income tax (net of tax credit)

ANNUAL NON-CASH EXPENSES

Depreciation

Depletion

Note ; Primary data source for all cash flow items is

Survey of the U« S« Oil and Gas Producing Industry

,

and

Annual Survey of Oil and Gas«

the Joint Association

the Bureau of Census,

39
V. 1 The Minimum Acceptable Price Calculations

The calculation of minimum acceptable prices (MAPs) is straightforward. It is

the constant, real unit breakpoint price (i.e. dollars/Bbl if oil, or dollars/

Mcf of gas) that enables the producer to recoup his costs plus bring him his

desired minimum return. It is calculated as follows:

MAP = Costs (after tax, discounted)

Production (discounted)

Thus, one will invest if the price is greater than or equal to the costs

(where costs include the return on investment). Costs are basically of five

types:

o Investments which must be’ capitalized

o Investments which can be expensed for tax purposes

o Cash expenses

o Non-cash expenses

o Tax credits.

Before describing each of these five different cost calculations, the methodology used for calculating the present value equivalent of the revenue stream

will be discussed.

As stated earlier, revenues equal production quantity (discounted) times

price. The present value equivalent of a revenue related to a continuously

declining production stream (PVEl)® is:

^See Appendix C for a more detailed discussion of the discounting procedure.

40
PVEl

l_e-(EH-DR)T

EH-DR if prices are held constant, and

l-[G*(e~(^DR))]

PVEl = , if prices are allowed to grow,

ln(G*e+(^DR))

where D = production decline rate (P/R ratio)

DR = discount rate (real, after taxes) [i.e., the rate of

return]

T = project life, and

G = price growth rate.

Thus Present Value equivalent production (PVEP)

PVEP = R * D * PVEl,

where R = Reserves, and

D = production decline rate

Thus the Minimum Acceptable Price is simply

MAP = COSTS/PVEPIO

We will now discuss (in Sections V.2.1 through V.2.5) how each of the five

types of costs are entered into the total cost stream calculations.

^See Page 1 of Appendix B for a discussion of the assumptions implicit in a choice of the value for the discount rate.

lOwe note that the calculation of PVEP assumes a constant production decline

rate, D. This assumption is inconsistent with the assumption made in the Resource Submodel that the production function for offshore regions is nonlinear

(see page 20 of this report). The model developers acknowledge this inconsistency, but argue that lease-constraints rather than economics (see Section V.l

for details) determines the amount of production in the offshore regions.

41
V. 1 . 1 Investments Which Must Be Capitalized

Investments which must be capitalized are assumed to occur during the discovery year and are, thus, added dollar-f or-dollar to the cost stream as follows

Cl = TSDC + LAI + GGI + ESI + LEI + GPI

where: Cl = investment costs.

TSCD = tangible portion of successful drilling costs.

LAI = lease acquisition investment.

GGI = geological/geophysical investment

,

ESI = environmental/safety investment.

LEI = lease equipment investment, and

GPI = gas plant investment.

Most investments are a function of drilling costs, either total drilling

costs, dry hole costs, or successful drilling costs. Drilling costs are calculated from depth-sensitive drilling cost curves (drilling cost per foot vs.

average depth)

o Total drilling costs (TDC)

TDC = EF*EFC+DF*DFC

42
where: EF = exploratory footage.

EFC = exploratory cost per foot,

DF = developmental footage, and

DFC = developmental cost per foot.

Tables IB through 4B, and the related discussion in Appendix B, explain how

exploratory and development footage costs are calculated.

o Dry hole costs (DHC):

DHC = EF*EFC*EDHF + DF*DFC*DDHF

where EF, EFC, DF, DFC are as defined above,

EDHF = exploratory dry hole factor (%), and

EDHF = developmental dry hole factor (%).

Tables 5B of Appendix B presents the data used for the exploratory and developmental dry hole factors.

o Successful drilling costs (SDC):

SDC = TDC - DHC.

Since only the tangible portion of the successful well expenditures need to be

capitalized rather than expensed:

TSCD = SDC * (1-IDF),

where TSCD = tangible portion of successful drilling costs, and

IDF = intangible drilling factor

Table 7B of Appendix B presents the Intangible Drilling Factors used in the

1978 ARC. .

43
Other investments (e.g. , lease acquisitions, geological/geophysical investments) are calculated as multiples of drilling costs from factors derived from

historical data. These are given below.

o Lease acquisition investment (LAI)

LAI = TDC*LACF

where LACF = lease acquisition cost factor

This factor is set to zero within MOGSM since lease acquisition costs

are considered by the model developers to be part of "economic rent,”

which is an input parameter to the MEFS integrating effort.

Geological/geophysical investment (GGI)

o GGI = TDC*GGCF

where GGCF = geological/geophysical cost factor

Environmental/ Safety investment (ESI)

o ESI = DHC*ESCF

where ESCF = environmental/safety cost factor

Lease equipment investment (LEI)

o LEI = DHC*LECF

where LECF = lease equipment cost factor

One investment is not a function of drilling costs:

Gas plant investment (GPI)

o GPI = IGP*GPIF

where IGP = increased gas production

GPIF = gas plant investment factor

44
Pages 102, 106, 107, and 108 of Appendix B provide information relating to the

geological/geophysical cost factors, environmental/safety cost factor, lease

acquisition cost factor, and Gas Plant Investment Factor.

V.1.2 Investments Which Can Be Expensed

Investments which can be expensed for tax purposes are reduced by the tax

effects; they are collected and handled as follows:

CE = (DHC + ISDC + LEI + DOI) * (1-TR)

where CE = expensable investment costs.

DHC - dry hole cost.

ISDC = intangible portion of successful drilling costs.

LEI = lease equipment investment

DOI = drilling overhead investment, and

TR = tax rate (federal and state);

Dry hole costs are discussed in the previous section. The remaining terms in

the equation for CE are discussed below.

ISDC = SDC * IDF

where SDC = successful drilling costs, and

IDF = intangible drilling factor (see Table 7B of Appendix B for

values).

Methods for calculating successful drilling costs and dry hole costs are given

in Tables IB through 4B and the corresponding text in Appendix B.

45
LEI = DC * LRIF

The lease rental investment factor (LRIF) is set to zero in MOGSM since it is

considered by the model developers to be part of "economic rent” which is an

input parameter to the MEFS integrating effort.

DOI = TDC * OCF

where

DOE = drilling overhead investment

OCF = overhead expense rate

TDC = total drilling cost

The drilling overhead expense rate used in the 1978 ARC is .133 for all years.

The tax rate is composed of a variety of taxes and is calculated as follows:

TR = FR + SR

where

FR = Federal Tax Rate, and

SR = State Tax Rate.

Appendix 3, Section B.ll presents the values for these tax rates.

V. 1.3 Cash Expenses

Cash expenses (E) are reduced by their tax effects in a manner similar to that

of expensed investments discussed above.

46
E = (PC + POE + GGE + LEE + ESE + GPE + PTE + RE) * (1 - TR)

,

where E = cash expenses,

PC = producing costs,

POE = producing overhead expense,

GGE = geological/geophysical expense,

LEE = lease equipment expense,

ESE = environmental /safety expense,

GPE = gas plant expense,

PTE = production tax expense,

RE = royalties expense, and

TR = tax rate (federal and state).

Most expenses are a function of producing costs. Producing costs are

calculated using annual producing cost per well factors, as follows;

o First, the present value equivalent of a constant continuous expense

(PVE2) is:

PVE2 = (i-e-(DR*T))

DR

where DR = discount rate (real, after tax) [i.e. return on investment], and

T = project life.

o Producing costs (PC) are calculated as:

PC = W*PCF*PVE2

where W = number of producing wells in project, and

PCF = producing cost per well.

47
Tables lOB and IIB of Appendix B provide regional data on initial oil wells

and operating costs per well, respectively. Other investments are calculated

as multiples of production costs from factors derived from historical data:

o Production overhead expense (POE):

POE = PC*OCF,

where OCF = overhead cost factor,

o Geological/geophysical expense (GGE):

GGE = PC*GGCF,

where GGCF = geological/geophysical cost factor,

o Lease Equipment Expense (LEE):

LEE = PC*LECF,

where LECF = lease equipment cost factor,

o Production Tax Expense (PTE):

PTE = PC*PTF,

where PTF = production tax factor (see Table 8B for actual regional

data)

.

o Royalty Rate Expense (RE):

RE = PC*REF,

where REF = royalty expense factor (see Table 9B for regional data

on royalty rates).

Other expense items are calculated separately:

o Environmental/safety expense (ESE):

ESE = W*ESF*PVE2,

where W = number of wells , and

ESF = environmental/safety cost per well.

48
Data related to overhead expenses, geological and geophysical expenses, environmental/safety costs, and lease equipment expenses can be found on pages 88

and 89 of Appendix B.

Finally one expense is calculated as a function of production decline over

time.

o Gas plant expense (GPE):

GPE = G0R*GDF*GPCF*IP0*PVE1

where GOR = gas/ oil ratio,

GDF =* gas drying factor,

GPCF = gas plant cost factor,

IPO = initial oil production, and

PVEl is as defined in the beginning of Section V.l.

V. 1.4 Non-Cash Expenses :

Depreciation expense (DF) is a non-cash expense which provides a tax shield

and is calculated on a unit of production basis (that is, the depreciation

schedule looks exactly like the production schedule), and is discounted as

follows

:

DF = CI*D*PVE1

where DF = depreciation expense.

Cl = capitalized investment,

D = production decline rate, and

PVEl = present value equivalent of a cost related to a declining production stream.

49
Now, the amount of depreciation (DE) allowed for tax calculations can be

defined as;

DE = DF*ADR

where ADR = accelerated depreciation rate, and

DF = actual depreciation expense.

Then the depreciation tax shield (DTS) is calculated as:

DTS = DE*TR

where DE = depreciation expense, and

TR = tax rate.

V.1.5 Tax Credits

Finally, several items qualify for an investment tax credit (ITC), which is

calculated as follows:

ITC = (TSDC + ESI + GPI + LEI) * TCR

where TSDC = tangible successful drilling costs,

ESI = environmental/saf ety investment,

GPI = gas plant investment,

LEI = lease equipment investment, and

TCR = tax credit rate.

50
V.2.6 Calculating Total Cost and Minimum Acceptable Price

To summarize, total costs are obtained from the five cost categories presented

above:

o Investments which must be capitalized (Cl),

o Investments which can be expensed for tax purposes (CE),

o Cash expenses (E),

o Non-cash expenses (DTS), and

o Tax credits (ITC).

Total costs, then, are:

COSTS = Cl + CE + E -DTS -ITC,

and the minimum-acceptable-price (MAP) is:

MAP = COSTS/PVEP

where PVEP = present value equivalent of production = l-e“®^ , D

D = production decline rate (P/R ratio),

T = project life, and

qQ = reserves.

When calculating the minimum acceptable price for a project, the costs and

revenues generated from both primary recovery alone and primary and secondary

recovery combined are calculated. If the production obtained through secondary recovery methods is found to be economic, then both primary and secondary

development will take place. This approach reflects the common practice of

establishing early a proposed development program which will consider the application of secondary recovery methods.

51
To calculate the secondary recovery costs, two additional terms are added to

the cost stream. A secondary investment cost (SIC) is added to the Investment

Costs and calculated as follows:

SIC = SCR * SCDCF,

where SIC = secondary investment cost.

SCR = secondary reserves, and

SCDCF = secondary drilling investment recovery cost factor

(additional cost/barrel).

Similarly, a secondary operating cost (SCOC) is added to the expensed costs

and calculated as follows:

SCOC = SCR * SCOCF * PVEl * D,

where SCR = secondary reserves.

SCOCF = secondary drilling operating factor (additional

cost/barrel)

,

PVEl = present value equivalent of a cost related to a declining

production stream, and

D = decline rate.

Tables 14B and 15B of Appendix B provide the data used in the 1978 ARC on

secondary investment and cost factors, respectively.

52
SECTION VI; THE DRILLING SUBMODEL (CONSTRUCTING THE DRILLING PROFILE AND

REGIONAL allocation;?

The last section of the Oil Supply Model is the Drilling submodel which projects levels of exploratory drilling for each region and year. Offshore regions and South Alaska (Region 1) are constrained by lease agreements which

dictate the maximum amount of drilling possible, while for all other onshore

regions only the price of oil constrains the amount of exploratory drilling.

For this reason, the model treats the lease-constrained regions differently.

We will first present the methodology for determining the constraints on exploratory drilling in offshore regions and South Alaska and then present the

methodology used to determine the drilling for both the onshore and the offshore regions.

VI. 1 Constraints to Drilling in the Offshore Regions

Because leasing constraints hamper access to more attractive prospects in the

Federally-owned Outer Continental Shelf (OCS) and South Alaska, drilling profiles for these four regions are constrained by leasing schedules. Thus even

if it is economic to do more exploration in these regions, the maximum amount

of drilling possible will be that offered in the leasing schedule. If, however, less than that amount is economic, then only that amount of drilling

which yields a price greater than the minimum acceptable price (MAP) will take

place.

For these regions, drilling trajectories are calculated to conform with leasing schedules supplied by DOE, and with resource estimates supplied by the

USGS. The calculation is as follows.
1. Annual lease acreage for Regions la, 2a, 6a, and 11a are derived from

Department of the Interior/Bureau of Land Management Leasing Schedule

Projections. Such schedules exist for the next three to five years and

data thereafter is extrapolated by DOE staff. Lease acreage schedules are

shovm in Table 2.

TABLE 2

Outer Continental Shelf Leasing Schedule

(Thousand of Acres Leased)

Year la 2a 6a 11a

1977 144 146 1068 no

1978 - 171 134 1039 183

1979 152 170 1028 255

1980 149 281 1006 307

1981 206 360 1106 279

1982 255 403 1234 240

1983 264 456 1315 212

1984 258 438 1348 177

1985 221 436 1375 161

1986 202 520 1251 131

1987 210 563 1024 130

1988 206 593 818 161

1989 205 592 774 192

1990 202 544 800 213

1991 202 442 731 229

1992 196 389 639 232

1993 174 353 593 235

1994 163 303 594 242

1995 157 271 595 250

1996 151 273 597 250

1997 151 379 598 227

1998 152 536 600 192

1999 152 622 601 175

2000 152 690 602 163

2001 152 732 604 157

2002 152 746 605 157

2003 152 760 606 157

2004 152 775 608 157

2005 152 789 609 157

2006 152 804 611 157

54
2. The oil drilling trajectory is developed by splitting annual lease acreage

into oil and gas acreage. DOE estimates of reservoir volumes of oil and

gas in place are used to determine the proportion of oil or gas bearing

fields in each region. Lease acreage is then split into oil and gas acreage according to the proportion of oil and gas present in a region. The

fractions in Table 3 indicate the oil and gas proportions used.

TABLE 3

Oil/ Gas Lease Acreage Split

Region Oil Fraction Gas Fraction

la 69.5 30.5

2a 97.7 2.3

6a 44.0 56.0

11a 72.0 28.0

3. After annual oil lease acreage is calculated, the proportion of lease

acres to be drilled each year must be determined. These are obtained from

Bureau of Land Management estimates of the time pattern of exploratory

drilling efforts. These estimates are published in varying detail in environmental impact statements (EIS) which must be filed for each lease

sale. An important assumption here is that the latest exploratory activities are representative of future activities in a particular region. The

following lease sale EIS reports were used are given in Table 4.

55
TABLE 4

Environmental Impact Statements

Lease Sale

Number Sale Date Region

#39 April, 1976 la

#C1 February, 1977 (tentative) la

#35 December, 1975 2a

#41 February, 1976 6a

#44 August, 1976 6a

#40 August, 1976 11a

The schedule in Table 5 presents the fraction of a regional lease sale that

will be explored each year following the sale.

TABLE 5

Oil Lease Acreage Exploratory Drilling Schedules

Years After

Sale la 2a 6a 11a

1 6% 6% 8% 6%

2 15% 15% 24% 15%

3 26% 26% 36% 26%

4 26% 26% 24% 26%

5 15% 15% 8% 15%

6 8% 8% - 8%

7 4% 4% 4%

56
4. Exploratory drilling schedules were converted into exploratory wells

through the following procedure. The lease acreage designated for exploratory drilling in each year from 1977 to 1991 by the drilling schedules were divided by a well-density factor. These factors are DOE*s judgmental estimates of the number of exploratory wells per 1000 acres. These

factors are listed in Table 6.

TABLE 6

Well-Density Factors

Exploratory Wells Per

Region Thousand Acres

1 .071

2a .5

6a .5

11a .071

5. The number of exploratory wells was next converted into exploratory drilling footage. This was accomplished by multiplying the number of wells to

be drilled each year by an exploratory depth factor corresponding to the

cumulative drilling that has occurred. Exploratory well depths increase

with cumulative footage. The initial oil drilling depths for 1976 drillings are given in Table 7.

57
TABLE 7

Initial Depth

Region Feet

1 10,096

2a 4,286

6a 8,650

11a 10,000

6. The final calculation converts exploratory oil drilling to total oil drilling. Total oil drilling is the sum of successful exploratory and developmental drilling plus dry hole drilling. This calculation is done by

multiplying exploratory drilling footage by a total to exploratory (T/E)

ratio. (This ratio is described in Appendix B, Table 5B. ) The ratio for

Region 6a is based on historical experience. The ratios for la, 2a, and

11a are calculated as follows.

(a) Average and peak oil production for oil acreage are determined

from estimates published in EIS reports.

(b) Production is converted into oil wells by dividing peak oil production by the Bureau of Mines* estimate of average daily well

production of 500 barrels per day.^^

(c) The number of exploratory wells drilled, calculated previously,

is multiplied by a success ratio derived from API data (see Table

6B of Appendix B). The result is the number of producing exploratory wells.

^^EIS on Accelerated OCS Leasing, 1975, Vol. 2, p. 3, Table 105.

58
(d) The number of producing exploratory wells is subtracted from the

number of total producing wells calculated in (b). This is the

number of producing developmental wells.

(e) The number of producing developmental wells is divided by a

developmental success ratio. This ratio is derived from NPC

data. This yields total developmental drilling footage.

(f) Service wells are included as indicated by the t;lS's.

(g) The number of exploratory developmental wells is added to the

number of service wells and the total is divided by the number

of exploratory wells to yield the total to exploratory drilling

ratio.

Table 8 presents parameters calculated to produce total to exploratory

ratios;

TABLE 8

Total to Exploratory Ratio Calculation

Region

Peak Oil

Production

Total #

Producing

Wells I-'

Exploratory

f Success

Ratio

- Developmental

Success

Ratio

#

Service

Wells

#

Exploratory

Wells

// Developmental

Wells

1 290,500 765 .299 .915 118 581 66

2a 201,600 806 .267 .9767 0 202 601

11a 132,000 264 .215 .756 44 45 264

^^We asked Charles Everett (of doe’s Division of Oil and Gas Analysis) why

total nvimber of producing wells did not agree with the directions for how to

calculate them (take peak production and divide by 500 Bbl/day) and he could

not explain the discrepancy.

59
Thus drilling information for the offshore regions is input into the model as

well as output from running the model. The amount of drilling done in the

offshore regions is constrained by lease agreements and therefore less sensitive to price trajectories than is true for onshore regions. Only when the

constraints are not binding (i.e. , the minimum acceptable price dictates that

less drilling take place in the offshore regions than that agreed to in the

lease schedules), will the outputs of the model be different from the inputs

discussed above.

VI. 2 Calculating a Cumulative Exploratory Drilling to Minimum Acceptable

Price Curve

The expected market price for crude oil and its coproducts defines the segment

of the undiscovered resource base which is economical to pursue. To determine

this quantity of economical resource in each region, a special run of the engineering and minimum acceptable price sections of the model are executed with

a hypothetical, ambitious exploratory drilling program in all geographical regions.

The process is as follows. For a given region, determine how much exploratory

drilling has been done to date (cumulative exploratory drilling), and calculate a minimum acceptable price for the oil obtained for that amount of drilling. This is the first (x,y) point on the cumulative exploratory drilling vs.

minimum acceptable price curve. Then increase drilling in 10 percent increments and calculate the MAP associated with each new quantity of drilling. If

the log of wellhead price is plotted against cumulative exploratory drilling,

the curve obtained is approximately linear (Figure 11). A curve of this type

is produced for each region.

60
Figure

11.

ULTIMATE

EXPLORATORY

DRILLING

ASA

FUNCTION

OF

PRICE

61

CUMULATIVE

EXPLORATORY

FEET
These curves represent an estimate of the time-independent "latent” demand for

drilling at alternative future oil prices. Due primarily to decreasing finding rates and increasing drilling costs (since one must drill deeper), as ciimulative exploratory drilling increases linearly, the corresponding increase in

the minimum acceptable price for the oil found will be approximately exponential. Each region, however, evidences a unique relationship between price and

latent demand for drilling.

These curves will be used to determine the amount of drilling required for any

given price trajectory. If additional drilling equipment is needed in order

to produce this oil, a capacity expansion program is instituted. The model

includes constraints which regulate the maximum rate of expansion for both onshore and offshore regions and limit production for offshore regions. These

constraints, therefore, have significant effects on the total production of

oil predicted by the model. The next section will present the methodology for

calculating the drilling profiles.

62
VI»3 Calculating the Regional Drilling Profiles

In general, the total amount of exploratory drilling indicated by a given level of expected market prices for oil cannot be accomplished in a single year

or even the usable lifetime of a current inventory of drilling equipment.

Therefore, the exploratory drilling process involves estimation of future capacity requirements. We find it convenient to describe the model process in

terms of a hypothetical regionally-aggregated representative planner/drilier.

Thus the model simulates the activity of 12 regional drillers (one for each

model region) , who transform latent demand into exploratory footage by use of

in situ (oil drilling) rigs with fixed annual drilling rates and usable lifetimes and similar equipment from exisiting rig plants with fixed production

lifetimes. If total estimated lifetime capacities from these "old rigs” and

’’new rigs from old plants” are less than the latent (cumulative) demand at the

expected (national) price, new plant construction is commissioned to provide

equal annual increments of drilling capacity, totaling over a fixed period to

the calculated shortfall. This planning calculation is repeated each model

year. (One year is the basic time interval in the model.)

Drilling capacity, once installed, is not retired (except through aging), nor

are existing rig plants, except in off-shore regions. This means that all of

the cumulative lifetime total drilling footage from existing rigs, from rigs

produced, and from rigs to be produced from existing plants will be realized,

even if prices should decline. Planned plant capacity additions (those commissioned but not yet built), however, will be curtailed in this event.

^^Price is the only variable in this part of the model which is not regionally

differentiated.

63
Aside from the incremental character of plant additions (the purpose of which

is to avoid unrealistic increases in a single year) , there are no explicit

constraints on the availability of drilling capacity. In other words, while

there is a rate restriction on capacity addition, there are no restrictions on

total magnitude except what may be incorporated into the tables of the cumulative drilling versus minimum acceptable prices (MAPs). Thus no question of

rig allocation arises in the model and the regions operate independently of

each other.

In regions 1, 2a, 6a, and I la exploratory footage realizable from drilling capacity (which is calculated as in the on-shore regions), is restricted by the

leasing agreements described in section VI. 1.

Both the thumbnail description of exploratory drilling above and the more detailed elaboration of the model equations below, are based almost entirely on

interpretation of the computer program labeled OILDRL 78. In consequence,

this "realized" model, deduced from FORTRAN statements, may differ from the

model conceived by the developers. We have included some discussion of the

possible effects of such discrepancies on the outputs of the model. A more

penetrating investigation would be desirable. It should consist of experimental runs of the model, and analysis of the properties of the solutions to

the differential equations induced by reduction of the recursions underlying

the stepwise simulated relationships.

^^For more on the difference between a "realized" and a conceptual model, see

[15]. A draft of this report was transmitted to the authors of the source documents accompanied by a request for comments. Ensuing discussions with one

of those authors disclosed the fact that the program listing which had been

furnished to us is not the current version. Since we have not been able to

obtain a "correct" listing, note that some comments herein are subject to

change.

64
VI. 3.1 The Equations of the Drilling Submodel

In what follows, as in previous sections, we have comprotnised conciseness for

intelligibility by using mnemonic labels, largely from the FORTRAN code, for

parameters and variables, wherever practicable. The symbol t denotes a discrete "time-step", i.e. a year, (thus COR^ and COR^+]^ denote Rapacity of O^ld

Rigs in year t and year t+1, and so forth). Because the simulation is repeated for each region, all or the variables should carry an additional index, say

j, to distinguish the region. This index has been omitted from the text to

improve legibility, but the reader is requested to bear in mind that each

eqioation has 11 equivalent counterparts, one for each model region.

We begin the mathematical presentation of the drilling model with the equations for calculation of expected price for estimating capacity requirements.

Equation (1) shows a three-year extrapolation of prices from the input "price

trajectory vector" of oil prices, to obtain a price argument for the latent

drilling demand function. This equation represents the regional developer's

"foresight" in planning for future development based on past trends. The developer uses the past year's and current year's price and extrapolates to a

"future" price of oil. He makes decisions based on that price. Equation (la)

refers to the first simulation year, in which the model allows the driller to

"foresee" next year's price to establish a price trend for extrapolation. (An

alternative would have been to set the expected price in year 1 equal to the

current price, i.e. PRICE

This is an example of a well-known unsolved

problem in the theory of modeling: how to treat "start ups" in discrete event

simulations.

)

65
PRICEc = ?c IFS*(?;. - ?c_i) =

?t + 3(?c - ?t-l) = ?t + 3A?c

PRICE^ < PMAX , C = 2, 3, lEND ; (1)

PRICEi =

?t: + IFS*(?2 “

?i) = ?1 3(?2 -

?i) = ?i + 3A?2

PRICE]^ _< PMAX , t = 1 ; (la)

where

PRICE^ is Che projected expected price for year t ; ? is the (input) prevailing national price in year t ;

APj- is P^ - ?t-l> the annual change in market price ;

PMAX is an upper limit price (input) ;

IPS is an input parameter of the computer model representing

the extrapolation interval. (In this model version, 3

years.); and

lEND is an input denoting the final year of the simulation, i.e.

the duration of the simulation, in model time.

The model's "backstop price" PMAX serves as a ceiling for expected prices in

periods of rapid market price increases. Note that according to the equations, declining prices could theoretically result in a negative extrapolated

price. Tne input price string is tested upon input and a warning message

printed if a price decline is detected but no other action is taken in the

computer program. See [lo] for a discussion of some effects of this action.

For any given price the developer estimates the corresponding demand for oil

by examining the cumulative exploratory drilling versus minimum acceptable

price cuir/e (see Section VI. 2). Equation (2) describes a linear interpolation

to determine latent demand when the price for year t (PRICE^) lies between the

66
smallest (MAPi) and largest (MAP 15 ) price values of the function table. Equation (2a) describes a log linear extrapolation for values of PRICE^ exceeding

the largest table entry. Equation (2b) is required for values of PRICE^ below

the smallest value which is considered economic.

The equations for drilling capacity requirements (Intent _Demand)

LD = L. , + AL. *

t 1-1 1

PRICEt - MAPj.i . , X PRICE^ < MAP

1 U

( 2 ) MAPi ” ^^i-1

LD = L_ + AL- *

t lo 15

log PRICEt - log MAP 15 .: PRICE > ’.iAP ( 2a)

log MAP 15 - log MAPii t '15

LD = 0 ; tPRICE^ ~< MAP^ ( 2 b)

where

is the latent demand for exploratory drilling in year t corresponding to PRICE^ ;

PRICEi is the expected or planning price of oil for year t

from equations ( 1 ) ;

is the i-th table value of cumxilative drilling ;

ALi is Li - Li_i ; and

is a "minimum acceptable price" in S/bbl corresponding to

a cumulative total of exploratory drilling of Li feet (in

units of 10^ ft). (The drilling versus price function described in section IV. 2 is represented as a table of 15 pairs

of values in the computer program for the exploratory drilling submodel. Thus the minimum acceptable price for

cumulative drilling of Li feet is MA?i.)

67
The rationale for equations (2) and (2a) is apparently that the tabular intervals are small enough for linear interpolation of the approximately logarithmic function not to cause serious error, but that for some prices outside the

range of the table, linear extrapolation could substantially overestimate total exploratory drilling (see Section VI. 2). We note that an expected price

equal to HAP]^, the smallest entry in any regional function table, will lead to

a meaningless value for latent demand because of the way the extrapolation is

" indexed.

Once the latent demand for drilling has been determined, one needs to determine if current drilling capacities will satisfy that demand. If not, a capacity expansion program is implemented. The following five quantities (Eq. 3-

7) are components of the equations for drilling and capacity planning.

The factor for residual rig capacity is:

a = 1 - j_ = RL-1 = IQ-1 = .9 . (3)

1 RL RL 10

Rig life (RL) is an input parameter of the computer program. In this model

version, rig life is assumed to be ten years. Thus a rig's output is assumed

to decline by 1/10 each year.

The estimated lifetime capacity factor for old rigs is:

RL

a„ = I Izi =1 (RL-1) = 4.5 . (4)

2 i=l RL 2

That is, a rig's lifetime output is estimated to be 4.5 times its initial

capacty (in 10^ ft. per annum).

68
The factor for residual capacity of rig building plants is:

a

3

1 -i_ = J±l= .9 . PL 10

( 5 )

Plant life (PL) is an input parameter of the computer program (ten years in

this model version). Thus a plant’s output is assumed to decline by 1/10 each

year.

The estimated lifetime capacity factor for new rigs built by old plants is:

PL

a, = a * = i (RL-1) * 1 (PL+1) = 24.75 . ^ 2 j=l PL _ 2 2

( 6 )

Thus a4 is the expected total output over the lifetimes of the rigs built in

the lifetime of the rig plant, as a multiple of the initial capacities.

Since new plants are not added in the year needed, but spread over a number of

years, one must determine the Capacity Additions from a Program Lasting (CAPL)

years. The total cumulative drilling factor from a capacity addition program

lasting CAPL years is calculated as:

a5 = CAPL * a4 = 10a4 - 247.5 , (7)

where CAPL is an input parameter to the computer model (set at ten years in

this version).

69
The above equations (Eq. 3-7) provide components of the equations for drilling

capacity planning. One must, however, begin with the current capacity of old

rigs and rig-plants. The current capacity of existing rigs ("^Capacity of £ld

Rigs") in any year is the amount of actual drilling in the previous year (D^_

]^). The initial capacity COR]^ is an input to the program. Thus, the equation

for annual update of capacity of rigs in place:

CORt = Dt_i . (8)

The current capacity of existing plants (^Capacity of ^Id plants) is the sum of

the previous year’s capacity (reduced by a decline factor) and any capacity

addition (CAP) in the -previous year. Initial capacity of the plants (COP]^) is

an input to the program. The equation for annual update of drilling capacity

of existing rig plants:

PL-1

COPt * COPfi + CAP = .9 COPt-i + CAP (9)

PL

70
Notice that the "outputs" of rigs and rig producing plants, as well as plant

capacity additions, are expressed in common units: millions of feet drilled

per year.

The equation for exploratory drilling in the current year is then composed of

"old rigs," CORj- (reduced by a decline factor), and of new rigs old plants,

COTf

D = RL-l * COR + COP = .9 COR + COP . t RL t t t t (10)

In the off-shore regions, drilling is limited by the lease constraints, equation lOc. Notice that lease-curtailed drilling at time t can be carried over

to the succeeding period because the limitation is defined by time-cumulative

constraints and prior drilling.

Dt _< CUMOCt - CUMDt-i (10a)

Cumulated drilling to date is:

i=t

CUMDt = Z Dt . i-1

(10b)

Cumulated lease constraints in an off-shore region:

i=t

CUMOCt = I OSLt , i=l

(10c)

where

OSLt is the off-shore lease constraint for year t

71
Once the total drilling footage from existing plants and rigs is known, the

total additional drilling capacity needed to satisfy latent demand (these are

the main equations of the planning process), can be calculated.

_New ^lant to satisfy _Latent _Demand in year t (NPLD^) (Eq. 11) is the difference between indicated latent demand (Eqs. 2, 2a, 2b) and the sum of three

components of estimated available capacity: the capacity of existing rigs

over their lifetime, the capacity of existing plants over their estimated

lifetime, and the aggregate footage from all previous (plant) capacity additions over their estimated lifetime. Since a capacity expansion program is

planned for installation over a fixed period (CAPL = 10 years), additions are

scheduled to furnish 1/10 of the extra capacity required in each year of the

program (Eqs. 9 and 12).

NPLDt LDt -

LD -

t

LDt -

t-1

a4 * COP^ — a2 * COR^ — a^, * Z CAPj^

k=l

t-1

l(RL-l) * COR - 1(RL-1)1(PL+1) [COP + Z CAP,J

2

t 2 2 ^ k=l ^

t-1

4.5 CORt - 24.75[COPt + Z CAP^] ; NPLDt >_ 0 . k=l

( 11 )

Portion of capacity addition to be installed in year t:

CAPt = NPLDt/a5 = NPLDt/CAPL * a4 = NPLDt/247.5 . (12)

72
If the model is reinterpreted to represent in each year a fraction of the regionally aggregated population of developer-drillers who plan production of

their "share" of exploration so that the capacity addition in any year corresponds to this fraction, the incongruous notion of unrecorded or forgotten capacity expansion plans does not have to be rationalized.

The model output consists of a time indexed vector of the quantities D^- , i.e.

a drilling trajectory for each region and the total annual drilling for all

regions for year t (USDHL^):

j=14

USDRLt = E Dti , (13)

j=l

where D^-j is the volume of drilling, in 10^ ft., in region j, in year t. (In

this final equation we see the "phantom" index j which has been omitted from

equations 1-12 as described in the introductory paragraph on page 64 for the

equations. From the variable D^j one can determine the total amount of oil

produced in each region in each year of the forecast. That quantity is a

final output of the model.

73
VI»3.2 Discrepancies Between Code and Documentation in the Drilling Submodel

The particulars, uncovered by study of the program, of the disparities between

the computer model of the drilling submodel and descriptions in the existing

documentation or verbal statements by the developers follow.

Calculation of physical depreciation of model rigs and rig-building plants,

i.e. annual decline in capacity of existing equipment is inconsistent with the

calculation of projected depreciation used in the determination of capacity

requirements to satisfy latent demand. Model output from existing rigs, COR,

is subject in each year to a decline of .1 of its current value. Thus the residual output after a year (Eq. 3) is (l-.l) * COR = .9 * COR (not counting

any additions); after two years, .9 * ;9 * COR = (.9)^ * COR ; and after ten

years, (.9)^^ * COR . A similar relationship obtains for rig plants, COP.

In models of physical or biological systems, this process is conventionally

called exponential decay . (For reasons which will become clear almost immediately, we will call it also exponential depreciation. ) In the calculation of

capacity requirements, i.e. the planning phase of the model drilling process,

the decline of in-place rig (and rig plant) capacity is treated as though it

were linear decay or straight line (physical) depreciation so that existing

rig output COR would be reduced in each year .1 of its initial value (again,

not counting additions). At the end of one year, we would have (l-.l) * COP =

.9 * COP (Eq. 3); but after two years, (1-.2) * COP = .8 * COP ; and after ten

years the original capacity would be exhausted, 1-10 *.1=0 with, as before,

a similar decline for rig plants. (Thus the labels RL and PL for _Rig _Life and

Plant Life.

74
Equations 4 and 6 expose these assumptions. Equation 4 gives the factor by

which to multiply first year production by rigs to determine remaining total

output if rigs age linearly over a ten-year lifetime. Lifetime total for a

rig would be initial capacity * (1 + .9+ .8+ .7 ... + .1) or 5.5 * initial

capacity. The factor 4.5 thus yields residual total capacity after one year.

Note that the actual exponentially depreciated model output from a "new" rig

over ten years would require the factor 1 + .9 + .81 + .729 + ... + .387 =

6.513 and a nine-year residual factor of 5.513 which is substantially (22.5%)

larger than 4.5. Notice also that after ten years the rig capacity is not exi=oo

hausted, but has a theoretical total-remaining-capacity factor equal to Z (q)^

i=10

or approximately 9.0 - 6.513 = 2.487. Thus, the "true" residual lifetime

factor after one year is 9.

Equation 6 yields an analogous factor for rig plants. The value of this factor after ten years is 35.906 for exponential depreciation, rather than 24.75.

Its true lifetime value after one year is 90. Within the context of the planning assumption of linearity, which could be interpreted as representing a uniformly biased planning methodology by drillers, i.e. a deliberate discrepancy

in the model between what the planners (drillers) expect and what actually occurs, there is another apparent error.

75
In equation 6, the component concerning plants should be a sum from the second

year through the ten-year plant life, and the factor concerning rigs should be

a sum from year one of rig life, because according to the timing of introduction in the model, that is the simulated updating of capacity in equation (9).

In other words, equation 10 shows drilling from "discounted” or "old" rigs

plus drilling from plants as output from the "new" rigs produced in the current year. Notice that the depreciation of old plant capacity is recorded in

the update equation for this variable, equation (9), but that the equation for

updating old rig capacity, equation (8), does not show the depreciation explicitly. This is because the rig capacity depreciation has been applied in

calculating drilling from existing rigs in the first element of equation (10).

It happens that in the'model as now constituted conceptually, with specific

numerical values for constants, the erroneous permutation of the factors has

no effect on the values of the outputs, because PL, plant life, and RL, rig

life, are equal (4.5 * 5.5 = 5.5 * 4.5).

The interchange does, however, invalidate the programmer's attempt to provide

additional flexibility in the computer model by treating a collection of model

constants labeled as input qxiantities, because if one were to change the model

by varying input values for labeled constants, the computed parameters a4 (Eq.

6) and a 5 (Eq. 7) would be incorrect whenever PL and RL were not given equal

values

.

Capacity expansions do not take place according to the model driller's planned

addition schedule because the model "forgets” that it is installing only the

first year's increment of the planned capacity increase, i.e. no record of the

expected total is retained in the model (see description of equations 11 and

12 above).

76
Because capacity additions feed into the stock of rig plants and rigs through

equations 8, 9, and 10, there is double counting of all available capacity in

equation 12, except for the most recent increment CAP^_]^, resulting in underestimation of additional capacity required. The term a4 * Z CAPj^ in the 1

equation should be replaced by a4* CAP^_i + CUMD^._]^ to capture drilling

equipment not yet carried in the inventory of existing capacity, and drilling

to date (see eq. 12, 10b). In this context at least, the assumption of linear

depreciation of equipment is a "compensating error.”

In the function table the drilling entry corresponding to a minimumacceptable-price relates to the initial year of the simulation. The generation of this function table is thus conceptually part of the drilling submodel. Therefore safeguards must be incorporated into the modeling system to

prevent the drilling submodel from being exercised independently on the generation of the values of the drilling price function.

Finally, because "drilling" and "equipment" are equivalent entities in the

model, curtailment of drilling owing to action of lease constraints can lead

(through equation 8) to "retirement" of rig capacity in an off-shore region.

This capacity may be subsequently replaced. Therefore, if "existing capacity," i.e. rigs and plants in place, or the components of annual drilling as

labeled in equation 10, should become of interest as model outputs, the accounting procedure would have to be modified. (At present, they are printed

out under the rubric "debugging dump" and do not influence final outputs of

the overall model system.)

77
SECTION VII. THE OTHER MAJOR MODELING SYSTEMS

The Gas Supply Model

The modeling system which produces supply projections for nonassociated natural gas and its coproducts is almost identical to the Midterm Oil Supply Modeling System. The economic basis for estimating minimum acceptable prices is

the same, as is the basis for estimating "latent demand" for drilling and regulating the rate of drilling over time. There are, however, two main distinctions; first, gas finding rates are estimated as a function of total drilling

(exploratory and developmental) rather than just exploratory drilling; and

second, the components of the oil model which represent enhanced recovery —

secondary and tertiary — are not present.

The Financial Model

Also included in the Midterm Oil and Gas Supply Modeling System is a Financial

Model which uses detailed cost and revenue information calculated in the Economic Submodels of the other two models to provide regional income statements

and selected balance sheet items for the oil and gas producing industry. This

model determines the capital expenditures necessary to provide production

quantities. It provides the capability to translate oil and gas supply solutions into detailed schedules of oil and gas expenditures, defined in terms

compatible with the national income accounts. These schedules are needed as

input to the DOE integrating model MEFS.

78
APPENDIX A

This Appendix identifies the input data for the resource base submodel of

MOGSM. In this report, by input data we mean "the set of data elements physi

cally read in and processed by the computer programs that formally constitute

the analysis system" [18, pg. 5]. The data set presented is that corresponding to the "Series C" forecasts shown in Volume III of the 1978 Annual Report

to Congress [36]. Section IV of this report describes how this data is processed. The data is presented below in the order described in that Section.

Initial Oil Reserves

The model input values given below represent the proved reserves existing at

the end of the last year. The reserve estimates are obtained from the American Petroleum Institute’s annual publication. Reserves of Crude Oil , Natural

Gas Liquids , and Natural Gas in the United States and Canada and Productive

Capacity as of December 31, 1977

;

TABLE 1-A

Initial Oil Reserves (million barrels)

Region Reserves

lA

2

2A

3

4

5

6

6A

7

316

2348

617

346

1243

5660

5027

1874

1486

563

33

8-10

11

llA 0

79
Decline Rates:

The decline rates employed by the model are estimated from the productionto-reserves ratio expected to prevail in each region. In turn, this is estimated from the last year of actual experience in each region, which can be obtained from data published by the American Petroleum Institute in its Reserves

Report (cited previously).

TABLE 2-A

Decline Rates

Region Decline Rates

8,9,10

11

lA

2

3

4

5

6

. 7

158

103

174

168

130

127

134

156

180

30
TABLE 3-A

PRODUCTION PROFILES FOR REGIONS lA, 2A, 6A, AND llA

YEAR OIL GAS

lA 2A 6A llA lA 2A 6A llA

1 0 0 0 0 0 0 0 0

2 0 0 0 0 0 0 0 0

3 0 0 .042 0 0 0 0 0

4 .004 .112 .064 .151 .014 .050 .050 .005

5 .016 .100 .074 .130 .035 .099 .099 .048

6 .033 .090 .085 .112 .047 .090 .090 .045

7 .059 .080 .085 .096 .047 .080 .080 .043

8 .093 .0-72 .085 .083 .047 .070 .070 .041

9 .080 .064 .073 .071 .047 .070 .070 .039

10 .070 .057 .063 .061 .047 .070 .070 .037

11 .061 .051 .054 .053 .047 .067 .067 .035

12 .052 .046 .042 .045 .047 .058 .058 .034

13 .045 .041 .040 .039 .047 .050 .050 .032

14 .039 .037 .034 .033 .047 .044 .044 .030

15 .034 .033 .029 .029 .047 .038 .038 .030

16 .033 .032 .028 .028 .047 .035 .035 .029

17 .032 .031 .027 .027 .047 .030 .030 .027

18 .031 .030 .026 .026 .047 .026 .026 .026

19 .030 .029 .025 .025 .047 .025 .026 .025

20 .029 .028 .024 .024 .047 .026 .026 .024

21 .028 .027 .023 .023 .047 .026 .026 .022

22 .027 .026 .022 .022 .047 .026 .026 .021

31
TABLE 3-A

PRODUCTION ;PROFILES FOR REGIONS lA, 2A, 6A , AND llA

YEAR

lA 2A

OIL

oA

(Continued)

llA lA

GAS

2A 6A llA

23 .026 .025 .021 .021 .047 .026 .026 .020

24 .025 .024 .020 .020 .047 .026 .026 .019

25 .024 .023 .019 .019 .047 .026 .026 .018

26 .023 .022 .018 .018 .047 .026 .026 .017

27 .022 .021 .017 .017 .047 .026 .026 .016

28 .021 .020 .016 .016 .047 .026 .026 .015

82
Initial Oil-in-Place

Initial oil-in-place was calculated by adding oil-in-place additions for 1971-

1977 (calculated for finding rate data) to oil-in-place estimates for 1970 as

reported in the NPC Energy Outlook; Oil and Gas Availability . The original source for this data is API Reserves of Crude Oil , Natural Gas Liquids

and Natural Gas in the United States and Canada.

TABLE 4-A

Initial Oil-in-Place (million barrels)

Region OIP

L\ 2941

2 78998

2A 2263

3 7294

4 26191

5 110645

6 84613

6A 14860

7 61983

8-10 33015

11 163

llA 0

S3
TABLE 5-A

Quinquennial Reserve Additions

(Obtained through the Use of Hubbert Equations)

1st Stage (Yrs. 2-6) 2nd Stage (Yrs. 7-11) 3rd Stage (Yrs

lA .00293 .00200 .0000

2 .00250 .00210 .0020

2A .02250 .01008 .00640

3 .00957 .00424 .00233

4 .00501 .00220 .00124

5 .00256 .00042 .00000

6 .00783 .00357 .00211

6A .01569 .00723 .00394

7 .00156 .00075 .00042

8-10 .00102 .00099 .00064

11 .00000 .00000 .00000

llA .00000 .00000 .00000

84
TABLE 6-A

Regression Analysis Results for 1977 ARC

Region QCIO^BI) b

2 33771 .935569 E-5

3 23463 .537416 E-5

4 32709 .235143 E-5

5 56399 .498198 E-5

6 30905 .359812 E-5

6a 28100 .289454 E-4

7 28895 .288161 E-5

)

00 1 t—

o 14192 .728011 E-5

Finding rates are calculated by taking the derivative of the curve relating

COIP and ciomulatlve drilling, with the appropriate values for Q and b, and the

appropriate cumulative drilling footage.

TABLE 7 -A

Initial Finding Rates

Region Finding Rate

2 .222796

3 .134861

4 .005634

5 .136446

6 .005946

6a .549723

7 .005386

8-10 .006964

85
Table 6-A above represents the regression results using the 1977 ARC estimates

for b. Table 8-A below represents the 1978 estimates for b. Notice that according to the definition provided in the text, Q should be the same in both

years but it is not. The reason for the discrepancy is that DOE modelers requested and received a revised estimate from the U. S. Geological Survey of

regional recovery factors which were applied in turn to undiscovered recovered

r<=<5ources to obtain a revised estimate of ultimate recovery (Q).

TABLE 8-A

Regression Analysis Results for 1978 ARC

REGION

(MMBLS)

Q b

(MET)

CMFT r2

STD ERROR

OF REGRESSION

2 32864 .853892E-5 27024 .928 .203337E-1

3 24138 .677276E-5 28415 .9629 .951448E-2

4 32436 .226398E-5 117003 .9336 .171771E-1

5 54153 .465574E-5 131877 .9743 .247101E-1

6 31026 .362541E-5 175835 .9955 .126080E-1

6A 28924 .311079E-4 15839 .9146 .469749E-1

7 19734 .451420E-5 111447 .9981 .603939E-2

8,9,10 13834 .653296E-5 39890 .9933 .563155E-2

86
Primary Recovery Factors;

These factors originally were based on an engineering judgment on the part of

the National Petroleum Council. Absent any improved information — and no

regularly reported data is available to replace such a judgment — these factors are left unchanged.

TABLE 9-A

Primary Recovery Factors

Region Factor

lA .158

2 .103

2A .101

3 .174

4 .168

5 .130

6 .127

6A .150

7 .134

8-10 .156

11 .180

llA .159

Secondary Recovery Factors ;

Secondary factors similar to the primary factors are used to translate additional oil-in-place to reserves after the requisite time lag. The secondary

factors are based on engineering judgment on the part of the National Petrole

urn Council. In 1976, ICF performed an analysis to see if these factors were

consistent (on a National level) with those that would have been predicted us

Ing Hubbert's factors. First, an initial amount of oil-in-place was

87
calculated using the finding rate for some given amount of exploratory drilling. Then Hubbert's equation was used to calculate how much additional oil

would be discovered in the next five years, and this was compared to the forecasted discovery based on the secondary factors. ICF’s analysis showed no

glaring discrepancies between the two methodologies. Therefore, DOE decided

to continue using the NPC secondary recovery factors.

TABLE 10-A

Secondary Recovery Factors for New Fields

1st Stage 2nd Stage

lA .0115 .0115

2 .1330 .1330

2A .0116 .0116

3 .0730 .0730

4 .0690 .0690

5 .1000 .1000

6 .0150 .0150

6A .0162 .0162

7 .0900 .0900

8-10 .0845 .0845

11 .0330 .0330

llA .0162 .0162

88
Producing Gas/011 Ratios ;

In the initial forecast year, this factor reflects the recent experience of

the total gas produced in each region to the total oil produced in that region. The ratio expected to prevail at the end of the forecast period, however, is fraught with more difficult estimating problems. Basically, it represents an engineering judgment, influenced by the geology of the region (particularly the remaining undiscovered reserves of associated-dissolved gas) and

the likely trends of enhanced recovery techniques and their estimated impacts

on producing gas/oil ratios. The model inputs are shown below.

TABLE 11 -A

Gas /Oil Ratios (in Mcf /Bbl)

Region 1978 1991

lA 265 265

2 462 462

2A 138 138

3 1242 1242

4 522 522

5 951 951

6 1493 1493

6A 814 814

7 1616 1616

8-10 536 536

11 1128 1128

llA 800 800

89
APPENDIX B - COST FACTORS

This Appendix identifies the input data for the economic submodel of MOGSM.

In this report by input data we mean "the set of data elements physically read

in and processed by the computer programs that formally constitute the analysis system” [18, pg. 5]. The data set presented is that corresponding to the

"Series C" forecasts shown in Volume III of the 1978 Annual Report to Congress

[36]. Section V of this report describes how this data is processed. The

data is presented below in the order described in that Section.

B. 1 Return on Investment

The discount rate employed by the model represents what is believed to be the

rate of return that the petroleum industry must earn after tax, on the average

industrywide, to attract capital. The model, however, forecasts in a constant

(or real) dollar environment. Consequently, the rate used should be adjusted

to represent not what the industry would expect nominally (i.e., anticipating

inflation or deflation) but rather what it would expect in a constant dollar

future (i.e., anticipating a zero rate of inflation or deflation).

Finally, the rate used reflects the effects of the capital structure (especially the mix of debt and equity) expected on the part of the industry on the

average. Consequently, the rate reflects a capital structure-weighted expected return, again after the effects of the federal tax code on debt versus equity have been considered.

The derivation of an appropriate rate is a difficult issue. It involves analysis of the performance of companies over time, preferably during a stable

90
period of inflation. This analysis tends to be theoretically-based and handicapped by the lack of clear-cut data, due to, among other things, the large

amount of horizontally and vertically integrated nature of the petroleum

industry.

Finally, it requires two kinds of judgments. The first must deal with how petroleum companies will behave in making their future investment decisions and

how this behavior will reflect on the result of the aforementioned theoretical

analysis. It also requires consideration of whether some major influence in

this decision making behavior has changed systematically since the period from

which the theoretical rate was derived. Examples include fundamental changes

in the risk of the petroleum business (due to market changes, resource changes

or other alterations in the business environment) or in the capital markets

(due to a long term shift in the balance of demand for, and supply of, capital) .

The rate of return chosen is 8 percent.

B.2 Calculating the Cost per Well Depth

A functional relationship between cost of drilling and average well depth is

assumed. To obtain the functional relationship, one first chooses the range

of values that well depth can possibly assume. The smallest value for average

well depth is derived by examining past drilling experience. This low depth

point is obtained from the most recent API Quarterly Review of Drilling Statistics . It is assumed that the largest average well depth is between 14,000

and 16,000 feet (depending on the region). At this point (the largest well

depth) it is assumed that the last oil is discovered in a region (the quantity

of oil discovered can be obtained from the finding rate curve).

91
The curve itself is then contoured to conform with the shape of the finding

rate curve. The source utilized for an estimated distribution by region is

the NPC Report entitled Energy Outlook ; Oil and Gas Supply Availability , page

180.

The lowest value, midpoint, and highest values, respectively, for well depths

for exploration wells, producing wells, and dry development used in the 1978

ARC are shown in Tables IB, 2B, and 3B.

TABLE IB

Well Depth and Cumulative Footage—Initial Year

Region Expl. Dry Producing Dev. Dry Initial Footage

lA 10858 10858 10858 0

*

2 2403 2403 2403 0

2A 5128 5128 5128 0

3 5746 5746 5746 0

4 6389 6389 6389 0

5 4222 4222 4222 0

6 5651 5651 5651 0

6A 8892 8892 8892 0

7 3799 3799 3799 0

8-10 2548 2548 2548 0

11 9000 9000 9000 0

llA 10000 10000 10000 0

92
TABLE 2B

Well Depth and Cumulative Footage for Midpoint of Curve

Region Exp. Dry Producing Dev. Dry Cumulative Footage

lA 12400 13000 12400 70000

2 9850 8150 9850 75000

Ik 10400 10200 10400 50000

3 10000 11650 10000 200000

4 8600 8950 8600 500000

5 7900 8000 7900 500000

6 11700 10800 11700 500000

6A 12650 - 12750 12650 125000

7 8800 8500 8800 500000

8-10 7600 7350 7600 225000

11 13500 15500 13500 500000

llA 12500 12500 12500 70000

93
TABLE 3B

Well Depth and Cumulative Footage for Endpoint of Curve

Region Exp. Dry Producing Dev. Dry Cumulative Footage

lA 15000 15000 15000 140000

2 15000 15000 15000 350000

2A 15000 15000 1500u 100000

3 15000 15000 15000 400000

4 14000 14000 14000 999999

5 15000 15000 15000 999999

6 14000 14000 14000 999999

6A 15000 15000 15000 250000

7 15000 15000 15000 999999

8-10 15000 15000 15000 450000

11 15000 16000 15000 999999

llA 15000 15000 15000 140000

B.3 Drilling Costs, Producing Wells and Dry Holes

The 1976 Joint Association Survey of the U. S. Oil and Gas Producing Industry

Drilling and Equipment Costs Is the data base for estimating drilling costs.

This survey reports the total number of wells, footage drilled, and costs for

oil and gas wells and dry holes in 11 different depth classes.

94
The number of producing oil wells, footage drilled, and cost data were aggregated by region in each of the 11 depth ranges. Then the average depth and

cost per foot for each of the depth classes were calculated and plotted on a

graph. The resulting data points were connected by straight lines, to approximate a cost per foot versus depth curve.

The average cost per foot in a region, however, is not equal to the cost per

foot at the average depth, due to the disproportionately high cost of deep

wells. To adjust for this difference, both the average cost per foot and the

cost per foot at the average depth were calculated and the difference between

the two results was added to each point of the curve. The same procedure was

used to develop dry hole costs.

To incorporate real cost increases since 1975, the Independent Petroleum Association of America (IPAA) Cost Study Report of May 8-10, 1977 and the October 1977 update were used. These contain cost indices for depth adjusted

drilling costs for 1973 to 1976 and estimates of cost increases in 1977. They

show an increase of 8.3 percent from 1975 to 1976, and a projected increase of

8.7 percent for 1976 to 1977. The GNP deflators over these time periods as

obtained from the December 1977 Annual Survey of Oil and Gas (MA-1315(76)-1)

are: 1.03 for the last half of 1975, 1.0495 for 1976, and 1.027 for the first

half of 1977. Thus the real cost increase from 1975 to 1977 is 6.00 percent.

All drilling cost values are adjusted by this factor. The cost data used for

producing wells and dry holes in the model is presented in Table 4-B.

95
PCS Drilling Costs ;

Offshore drilling cost calculations varied between regions. Region la calculations were based on cost estimates published In the Cook. Inlet and Gulf of

Alaska Environmental Impact Statements. The costs per foot for 6A are the

same for oil and gas and were calculated by the following procedure.

1. Total exploratory and developmental footage was calculated

by multiplying the numbers of wells published In the Environmental Impact Statements by average well depth.

2. Total drilling and platform costs were obtained from the

Environmental Impact Statements on Offshore Leasing Sales.

3. Success ratios were used to split dry and producing wells.

4. Dry and producing costs per foot were calculated by dividing

total costs by total footage.

5. These "mld-polnt" values for dry and producing costs per foot

were scaled according to cost curves for Region 6A.

Regions 2A and llA calculations were based on cost factors designed by the NPC

and published In Ocean Petroleum Resources . These factors scale Region 6A

costs to reflect various local conditions In offshore regions. These factors

were applied after resources In 2A and llA were divided Into water depth categories of 200 meter and 500 meters. The cost factor for 2A Is 6A x 1.25. For

llA, the cost factor Is 6A x 1.8.

96
TABLE ^

Drilling Costs Per Foot by Depth Bracket

Region lA

Producing Dry

Depth Wells Holes

10858 281.78 239.51

11250 307.86 261.68

13750 411.76 350.00

16250 518.77 440.95

Region 2A

Producing Dry

Depth Wells Holes

5128 87.55 74.38

6250 100.54 85.46

8750 146.68 124.68

16250 370.54 314.96

Region 4

Producing Dry

Depth Wells Holes

6389 39.46 23.94

8750 56.13 34.05

11250 84.16 51.06

16250 141.81 86.03

Region 6

Producing Dry

Depth Wells Holes

5651 37.84 33.63

6250 40.65 36.13

8750 59.30 52.70

16250 149.81 133.14

Region 7 Producing Dry

Depth Wells Holes

3799 29.52 21.79

4375 29.60 21.85

6250 37.77 27.88

16250 139.21 102.76

Region 1

1

Producing Dry

Depth Wells Holes

9000 67.77 49.63

11250 96.77 70.87

13750 129.43 94.79

16250 163.06 119.41

Region 2

Producing Dry

Depth Wells Holes

2403 47.85 35.76

3125 49.91 37.30

4375 50.22 37.53

16250 236.17 176.50

Region 3

Producing Dry

Depth Wells Holes

5746 43.20 30.61

6250 45.87 32.50

8750 66.91 47.41

16250 169.04 119.78

Region 5

Producing Dry

Depth Wells Holes

4222 27.81 22.65

4375 27.83 22.67

6250 35.51 28.92

16250 130.88 106.60

Region 6A

Producing Dry

Depth Wells Holes

8892 102.57 88.92

11250 175.92 149.53

23750 235.29 200.00

16250 296.44 251.97

Region 8-10

Producing Dry

Depth Wells Holes

2548 22.95 19.28

3125 23.73 19.94

4375 23.88 20.06

16250 112.30 94.35

Region llA

Producing Dry

Depth Wells Holes

10000 211.17 179.49

11250 263.88 224.30

13750 352.93 299.99

16250 444.65 377.95

97
B.5 Offshore Escalation Factor

Offshore drilling costs increase not only due to drilling progressively deeper

wells, but also due to drilling in progressively deeper water. To account for

increased costs occasioned by drilling in deeper water, the model uses a 2

percent annual escalation in offshore drilling costs, or a 34.6 percent increase over the fifteen year forecast period.

B.6 Initial Exploratory Footage

This initial data is derived from the API Quarterly Review of Drilling Statistics . It provides statistics on 1976 successful oil well footage, successful

gas well footage, and dry hole footage. Dry hole footage was allocated to oil

and gas on the basis of successful oil and gas footage. The 1976 total exploratory footage figure (including dry hole allocation) is 21,160,364 feet

for oil.

B.7 Total to Exploratory Drilling Ratio

The total to exploratory drilling ratio is a measure of the development program which is occasioned by a discovery. To calculate such a ratio, an initial intercept is chosen by observing actual experience over recent years.

Since pools found will be increasingly smaller and have deteriorating reservoir structure, reserves per developmental well will not remain constant, but

must decrease over time. A lognormal relationship was assumed and the different intercepts were calculated based on more recent data. Table 5B presents

the total to exploratory drilling at a variety of cumulative footage points.

98
The data source for the initial total to exploratory drilling ratio is the

latest API Quarterly Review of Drilling Statistics for the United States .

Total exploratory and total developmental drilling footage is calculated by

allocating dry footage according to the ratio of successful oil to gas footage

drilled.

TABLE 5B

Total to Exploratory Drilling Ratio

Region lA

Cumulative

T/E Footage

3.15 0

3.15 240

3.14 650

3.12 1700

3.08 4700

2.90 16000

1.00 140000

Region 3

Cumulative

T/E Footage

3.76 0

3.75 1900

3.72 5200

3.66 14200

3.49 38600

3.04 105000

1.00 400000

Region ^

Cumulative

T/E Footage

6.30 0

6.26 2800

6.18 7700

5.98 21000

5.44 57000

3.63 175000

1.00 350000

Region 4

Cumulative

T/E Footage

2.89 0

2.86 13700

2.82 37300

2.70 101500

2.37 275900

1.47 750000

1.00 999999

Region 2A

Cumulative

T/E Footage

2.98 0

2.96 1000

2.93 2700

2.83 7400

2.58 20200

1.89 55000

1.00 100000

T/E

Region 5

Cumulative

Footage

5.68 0

5.65 6400

5.60 17400

5.46 47400

5.08 128800

4.04 350000

1.00 999999

99
Region 6 Region 6A Region 7

Cumulative Cumulative Cumulative

T/E Footage T/E Footage T/E Footage

3.08 0 4.98 0 5.99 0

3.05 12800 4.96 1200 5.96 6900

3.01 34900 4.93 3200 5.90 18700

2.88 94700 4.84 8800 5.74 50800

2.54 257500 4.60 23900 5.30 138000

1.62 270000 3.95 650000 4.12 379000

1.00 999999 1.00 250000 1.00 999999

Region 8-10 Region 11 Region llA

Cumulative Cumulative Cumulative

T/E Footage T/E Footage T/E Footage

4.99 0 2.29 0 8.47 0

4.96 3500 2.29 1100 8.43 700

4.91 9500- 2.28 3000 8.38 1700

4.76 25700 2.27 8100 8.22 4700

4.37 69900 2.23 22100 7.78 12900

3.31 190000 2.12 60000 6. 60 35000

1.00 450000 1.00 450000 1.00 140000

B.8 Exploratory and Developmental Dry Hole Fraction

The data source is the API drilling statistics previously cited. Dry hole

footage is allocated to oil or gas drilling according to the ratio of successful oil or gas drilling to total successful gas drilling. The dry hole fraction is the proportion of total, developmental, or exploratory drilling represented by the allocated amount of dry hole drilling, or allocated dry holes

divided by total exploratory or total developmental drilling. These are shown

in Table 6B.

100
TABLE 6B

Exploratory and Developmental Dry Hole Fraction

Region

Exploratory

D/H Fraction Developmental

lA .891 .048

2 .648 .055

Ik .733 .074

3 .784 .120

4 .748 .253

5 .695 .151

6 _ .767 .263

6A .942 .443

7 .702 .289

8-10 .731 .127

11 .908 .357

llA .785 .244

101
3.9 Intangible Drilling Write-Off

Similar to the factor for accelerating depreciation, the intangible drilling

write-off factor represents industry experience regarding the shares of successful well expenditures which are expensed rather than capitalized. The

original National Petroleum Council factor was derived from the experience of

companies, Chase !ianhanntan Bank data, and expert counsel. Altering their

factor would have required a comparable analysis.

TABLE 7B

Intangible Drilling Factors

Oil .70

Gas .73

B.IO Plant Investment

The National Petroleum Council originally estimated initial gas plant investment regionally, among other things from Chase Manhattan Bank data. Since the

model is not particularly sensitive to these inputs, these original estimates

are left unchanged.

With respect to new gas plant investment, the National Petroleum Council developed an engineering estimate of the processing capacity required per thousand cubic foot-increment of gas plant production and the cost per unit of additional capacity. It was based on a judgment that gas plant investment would

102
be $30 for each incremental MCF per day of nonassociated gas, and $175 for

each incremental MCF per day of associated-disolved gas; and that 93.5 percent

of marketed gas is processed (except in Region 6 where only 75 percent of marketed gas is processed).

B.ll Tax Rate

Tax rate on corporate income (including 2 percent state tax) is 50 percent.

Thus, the tax rate factor is .50.

B.12 Ad-Valorem and Production Taxes

These rates are derived from the actual tax rates prevailing in the states included in each region. The nominal rates of each state are weighted by the

fraction of total regional production expected from each. This weightedaverage, then, is the regional ad-valorem and production tax factor.

TABLE 8B

Region Oil Gas

8-10

11

llA

lA

2

2A

3

4

5

6

6A

7

.000 .000

.080 .080

.000 .000

.0714 .0704

.0828 .0791

.0818 .1055

.0965 .1377

.000 .000

.0710 .0825

.0403 .0729

.0700 .0700

.0000 .0000

103
B.13 Royalty Rates

Royalty rates are derived in a fashion similar to ad-valorem and production

taxes. The basis, however, is confined mainly to rates charged for new properties on state lands. The model uses royalty rates of 12.5 percent onshore

and 16.7 percent offshore.

TABLE ^

Royalty Rates

Onshore 12.5

Offshore 16.7

B.14 Initial Oil Wells

Initial oil wells describe the number of oil wells operating at the beginning

of the forecast period. The source for this data is World Oil Well Count pub'

llshed in the 2/15/78 issue.

TABLE lOB

Initial Oil Wells - 1977

Region Wells

lA 291

2 37910

2A 6089

3 3873

4 17477

5 114315

6 83938

6A 4183

7 128343

8-10 111800

11 23

llA 0

104
B.15 Operating Costs Per Well

Operating costs per well come from Oil and Gas Replacement Cost ; Development

and Production report prepared by Gruy Federal, Inc. This report gives operating costs as a function of depth for 24 different regions. The depths used

were the average depths of producing oil wells (Table 3B, discussed earlier)

derived from the 1976 API Drilling Statistics. Gruy regions were collapsed

into NPC regions by averaging the operating costs weighted by the number of

producing wells in each Gruy Region. The resultant operating costs are shown

below in Table IIB.

TABLE IIB

Oil Well Operating Costs

Region Yearly Cost/Well Secondary Operating Costs (Cents/Barrel)

lA 526062 189

2 4900 127

2A 92588 127

3 7604 55

4 9736 55

5 5833 55

6 7232 55

6A 67310 127

7 4508 55

8-10 4985 55

11 15434 55

llA 143641 127

105
B.16 Overhead Expenses

Exploration and production overhead costs are derived from the Joint Association Survey as a function of drilling and producing costs, as follows: G&A

overhead allocated to exploration, development, and production was summed, and

divided by the sum of drilling, equipping, and production direct costs.

Overhead factor = Annual Overhead Costs = .175

Annual Drilling and Producing Costs

B.17 Geological and Geophysical Expenses

These costs are estimated as a function of drilling and producing costs. The

derivation is based upon data from the Joint Association Survey of the U. S.

Oil and Gas Producing Industry (JAS). Geological and Geophysical Expenditure;

Contributions Toward Test Wells; Land Department, Leasing, and Scouting Expenditures; and Other Exploratory Expenditures from the 1975 JAS were summed, and

divided by the sum of drilling, equipping, and production direct costs. The

Geological and Geophysical Cost Factor (GGCF) used in the 1978 ARC report =*

. 102 .

Since the model computes minimum acceptable prices for new wells, and to avoid

overburdening the new fields with the total geological and geophysical expense, (since producing and new fields both are responsible for these costs),

the costs reported are allocated between existing wells and new wells as follows :

106
D = Annual Drilling Costs + Producing Costs

New Wells — New Field G&G factor = G&G expense x .75 = .0765

D

Existing Wells — Old Field G&G factor = G&G expense x .25 = .0255

D

B. 18 Lease Equipment Expense

This cost factor is derived from the Joint Association Survey, as a function

of drilling and equipment costs, as follows.

Lease equipment factor = Annual Lease Equipment Costs = .310

Annual Drilling and Equipment Producing Costs

Consistent with geological and geophysical expense, lease equipment costs must

be adjusted to avoid overburdening new wells with total lease equipment expenditures. Costs typically are allocated between existing fields and new fields

as follows:

C = Annual Drilling and Equipment Producing Well Expenditures

New Wells — New Well Lease Equipment = 0.75 x 0.310 x C = 0.233 x C

Existing Wells — Existing Field Lease Equipment = 0.25 x 0.310 x C =

0.078 X C

107
B.19 Project Lives

The project lives used in the model represent the anticipated economic lives,

on average industrywide, of various broad classes of projects in different

geographical regions. In general, rather long lives are typical (see Table

12B). The typical combination of relatively long lives (say, at least 25

years) and relatively high discount rates (say, at least 8 percent) make the

model results insensitive to changes in these project life estimates.

TABLE 12B

Project Lives

Primary Oil

Secondary Oil

Tertiary Oil

New Gas

Old Gas

30 years

25 years

20 years

30 years

30 years

B.20 Factor for Accelerating Unit of Production Depreciation

This factor originally was estimated by the National Petroleum Council based

on Chase Manhattan Bank data and tax counsel. Alteration of these factors

would have required a similar analysis; first, of the tax code; second, of

the impact on illustrative projects with regard to depreciation; and, lastly,

a review of company data.

108
TABLE 13B

Factors for Accelerating Depreciation on UPO Basis

1977 1980 1988 1991

Oil 1. 171 1.121 1.072 1.070

Gas 1.171 1.121 1.072 1.070

B.21 Tax Credit Rate

A tax credit rate of .10 was used for the period 1977 through 1980. From 1981

on, .07 was used.

B.22 Secondary Investment Factors

Secondary investment factors are derived from the National Petroleum Council’s

Oil and Gas Availability , which based its figures on extensive operator polling. They set the Investment at 25jd per barrel for onshore regions and

per barrel offshore. Onshore costs were expected to triple to 75«‘/barrel and

offshore to double to $ 1.00/barrel over the 15-year time span of the original

NPC model. These factors have been inflated by the GNP deflator and are shown

in Table 14B.

109
TABLE 14B

f

f

Secondary Investment Cost Factors

1977 2006

lA 1.06 2. 11

2 .35 1.06

2A .70 1.41

3 .35 1.06

4 .35 1.06

5 .35 1.06

6 .35 1.06

6A .35 1.06

7 .35 1.06

8-10 .35 1.06

11 .35 1.06

llA .70 1.41

B.23 Secondary/Tertiary Operating Costs

These data are incremental to the normal well operating cost and are applied

to secondary and tertiary projects in each of the regions.

The model inputs for secondary operating costs are based on estimated averages

prepared by LaRue, Moore, and Schafer. Their research concluded that incremental operating costs of secondary recovery in uncomplicated onshore areas

was estimated to be about $ .55 per barrel. In offshore areas and onshore

California the estimated operating cost per secondary barrel was $1.27 and in

Alaska $1.89.

I

110
TABLE 15B

Secondary Operating Costs

Region Secondary Operating Cost

lA

2

2A

3

4

5

6

6A

7 8-10

11

llA

1.89

1.27

1.27

.55

.55

.55

.55

1.27

.55

.55

.55

1.27

111
APPENDIX C

DISCOUNTED CASH FLOW CALCULATIONS

o Assume production in any period is proportional to reservoir pressure (P^)

qt = Ki * Pf

o Assume reservoir pressure declines with cumulative production (Q^):

Pt “ Po - (K2 * Qc)-

o Then = Ki(PQ-K2Qt)

o Differentiating with respect to time we get

dqt

= - (Ki * K2> dQt

dt dt

o Now, since by definition of cumulative production

dQt

= ^t

dt

o We set a = Kx * K2 (discussed in the text as the decline rate)., to get

dqt -1 dqt

-aqt = or q^ = dt a dt

Solving this differential equation yields

q = qo6

o The present-value-equivalent factor for a continuous stream of payments

(discount rate = r)^^;

t PVE = / e"^^dt

0

^^In the text, the discount rate is denoted DR.

112
o The present value equivalent production (Qg):

Qe = <lo / e“(^+^)tdt = qo

* a+r

0

o Minimum acceptable price (p^) makes net present value — revenues less

operating costs — equal the investment (Ig) necessary to prove reserves

(R) and establish initial production (qo) and decline rate (a).

o Revenues

:

— annual revenues - Pt * — present value equivalent: P * Qe (p constant)

o Two classes of operating costs: — Approximately constant per year (e.g.,, producing well expense)

- annual costs:

- present value equivalent: Kg = K* l-e~^^ (K-constant)

r — Approximately proportional to production (e.g., royalties)

- annual costs: = b * q^ (b = unit cost per unit production)

- present value equivalent: Cg = b * Qg

o Minimum acceptable price (MAP)

:

Ig - PVE (Revenues - Costs) = (MAP * Qg) - Kg - Cg

Where:

Ig Kg + Cg investment portion

MAP = + 2

= Qg Qg annual cost portion

113
REFERENCES

1. Arps, J. J. and Roberts, T. G. (1958), "Economics of drilling for

cretaceous oil production on the east flank of the Denver-Julesberg

Basin," Bulletin A« A« P. G. , 2549-2566.

2. American Petroleum Institute (1978), Quarterly Review of Drilling

Statistics for 1977 , March 1978.

3. American Petroleum Institute (1978), Reserves of Crude Oil, Natural Gas

Liquids, and Natural Gas in the United States and Canada , May 1973.

4. American Petroleum Institute, Independent Petroleum Association, and

Midcontinental Oil and Gas Association (1976), Joint Association Survey

of the Oil and Gas Producing Industry , December 1976.

5. Barouch, E. and Kaufman, G. (1976), "Probabilities modelling of oil and

gas discovery," Energy; Mathematics and Models , ed. Roberts, F. S.

,

133-150.

6. Barouch, E. and Kaufman, G. (1977), "Mathematical aspects of production

and distribution of energy," Symposium in Applied Mathematics XXI , Providence, R. I. , American Mathematical Association.

7. Bloomfield, P. , Deffeyes, K. S. , Watson, G. S. , Benjamin!, Y. and Stine,

R. A. (1979), "Volume and Area of Oilfields and Their Impact on Order

of Discovery," February 1979. Departments of Statistics and Geology,

Princeton University, Princeton, N. J.

8. Bloomfield, P. , Hudson, M. , Kim, K. and Watson, G. S. (1979), "The Use of

the Lognormal Distribution in Estimating Crude Oil Resources," February 1979, Department of Statistics and Geology, Princeton University,

Princeton, N. J.

9. Cram (1971), American Association of Petroleum Geologers Memoir 15.

10. Celiano, R. , Limaye, D. R. , and Hu, D. S. (1978), A Comparative State-ofthe-Art Assessment of Gas Supply Modeling , EPRI EA-201, prepared by

Mathtech, Inc. for the Electric Power Research Institute, 3412 Hillview

Ave. , Palo Alto, California 94304, June 1978.

11. Celiano, R. , Fallah, M. H. , and Limaye, D. R. (1978), A Comparative

State-of-the-Art Assessment of Oil Supply Modeling , EPRI EA-1609,

prepared by Mathtech, Inc. for Electric Power Research Institute,

3412 Hillview Ave., Palo Alto, California 94304, June 1978.

12. Everett, C. G. , "Description of Method Used to Forecast Domestic Gas

Supply," undated note.

13. Everett, C. G. , "Description of Method Used to Forecast Domestic Oil and

Gas Supply," undated viewgraphs of Oil and Gas Supply Model.

114
14. Everett, C. G. "Model Documentation Summaries," memorandum for George

Lady, dated September 28, 1978.

15. Gass, S. , Hoffman, K. L. , Jackson, R. H. F. , Joel, L. S. , and Saunders,

P. B. (1980), Interim Report on Model Assessment Methodology; Documentation Assessment , NBSIR 80-1971, National Bureau of Standards,

Washington, D. C. 20234.

16. Harris, C. M. and Hirshfeld, D. S. (1980), System Sensitivity and Stability, I; Model Validation, Simulation, and Sensitivity , " Final

Report for NBS contract NB79NAAA6747 , Distribution by Richard H. F.

Jackson, National Bureau of Standards, Washington, D. C. 20234.

17. Hayes, Earl T. (1979), "Energy Resources Available to the United States,

1985-2000," Science Magazine 203, January 1979, 233-239.

18. Hirshfeld, D. S. , Investigation of Underlying Data; Midterm Oil and Gas

Supply Model , Final report for NBS contract NB79NAA3034, Distribution

by Richard H. F. Jackson, National Bureau of Standards, Washington,

D. C. 20234.

19. Hubbert, N. K. (1574), "U. S. energy resource, a review as of 1972, part

1

, " in A National Fuel and Energy Policy Study: U. S. 93rd Congress , 2nd Session, on Interior and Insular Affairs, Serial number 93-40.

20. Independent Petroleum Association of America, Cost Study Report, May 8,

1977.

21. Kaufman, G. , Balcer, Y. , and Kruyt, D. (1975), "A probabilistic model of

oil and gas discovery," in Studies in Geology No. 1, Methods of Estimating the Volume of Undiscovered Oil and Gas Resources , 113-142.

22. La Rue, Moore, and Shafer, unpublished report prepared for the Department

of Energy.

23. Lewin and Associates (1976), The Potential Economics of Enhanced Oil

Recovery .

24. Meyer, L. S. , Bell, K. L. , and Perwin, E. S. (1979), "On the Use of Crude

Oil Initial Production Statistics to Estimate Ultimate Production,"

February 1979, Departments of Statistics and Geology, Princeton University, Princeton, N. J.

25. Meyer, L. S. , Silverman, B. , Zeger, S. L. , and Bruce, A. G. , "Modelling

the Rates of Domestic Crude Oil Discovery and Production," February

1979, Departments of Statistics and Geology, Princeton University,

Princeton, N. J.

26. McKelvey, V. E. (1973), "Mineral resource estimates and public policy,"

in Brost, D. A. and Pratt, W. P. , eds. United States Mineral Resources , U. S. Geological Survey Paper 820, pp. 9-19.

115
27. National Petroleum Council (1972), United States Energy Outlook.

28. National Petroleum Council (1973), United States Energy Outlook; Oil

and Gas Availability .

29. National Petroleum Council (1974), Ocean Petroleum Resources .

30. National Petroleum Council, U. S. Oil and Gas Supply; Computer Program

Documentation , NPC 1971; modified in 1975 by ICF, Inc.

31. Oil and Gas Journal (a periodical), many 1977 issues.

32. Office cf Energy Information, Project Independence Evaluation System

(PIES) Documentation , Volumes IV-XI, September 1976.

33. Office of Energy Information, Midterm Oil and Gas Supply Modeling System

Description , Technical Report, TM/ES/79-65, November 1978.

34. Office of Energy Information, Midterm Oil and Gas Supply Modeling System;

User Guide, EM/ES/79-Draf t , July 1979.

35. Office of Energy Source Analysis, Oil and Gas Supply Curves for the

Administrator's Annual Report, DOE/EIA, September 1978.

36. Office of Energy Information, Medium-Run Oil and Gas Supply Model, 1977

37.

Update, Research Memorandum 78-015, December 1977.

Office of Energy Information, Oil and Gas Midterm Supply Model; Method38.

ology Description, draft of Technical Memorandum.

Office of Energy Information, Alaskan Hydrocarbon Model; Methodology

Description.

39. Office of Energy Information, Alaskan Hydrocarbon Model; Methodology

Description, Appendix 1, Data Documentation.

40. Office of Energy Information, Alaskan Hydrocarbon Model; Guide to Model

41.

Application, draft document.

Office of Energy Information, Alaskan Hydrocarbon Model; User Guide,

42.

draft docviment.

Office of Energy Information, Alaskan Hydrocarbon Model; Systems Guide,

43.

draft document.

Office of Energy Information, Enhanced Oil Recovery; Model Methodology

Description , draft document.

44. Office of Energy Information, Enhanced Oil Recovery; User Guide .

45. Office of Energy Information, Enhanced Oil Recovery; Systems Guide .

46. Office of Integrative Analysis, The Integrating of the Project Independence Evaluation System, Vol. I-V, draft report.

116
47. Schanze, Jr., J. J., "Oil and Gas Resources—Welcome to Uncertainty,”

Resources; Resources for the Future , Special Issue No. 58, March 1978.

48. U. S. Bureau of Mines, Report on Withdrawals and Deposits of Natural Gas

in the United States , February 1978.

49. U. S. Bureau of the Census, Annual Survey of Oil and Gas , Technical

Report MA13K(76)-1, December 1977.

50. U. S. Department of the Interior, Bureau of Land Management, Environmental Impact Statements on Offshore Leasing Sales . Documents on Sales

Numbers; 32-51, Cl, and 44, 1973-1976.

51. U. S. Geological Survey Circular 725.

52. World Oil (a periodical), February 15, 1978.

117
L .1

* W no ? rcwniJt .••nipK

::S "£?1 >*»c coja<« t|^

~ JLnijj^ ,Buer»0 ods io UM - • itl VJMtoU

’’ • '• . -7 I'i?, Inc.

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_IlL*_J’£24S£jLil
MBS-114A (REV. 9-78)

U.S. DEPT. OF COMM.

BIBLIOGRAPHIC DATA

SHEET

1. PUBLICATION OR REPORT NO. NBSIR 80-2044 (DoE)

2. Gov't Accession No. 5. Peciptent' 4 Accession No,

^

,

' y v''.

4. TITLE AND SUBTITLE

An Annotated Restatement of the Midterm Oil and Gas

Supply Modeling System Methodology

5. PuDiication Date July 1980

6. Performing Organization Code

7. AUTHOR(S)

Karla L. Hoffman and Lambert S. Joel

8. Performing Organ. Report No.

9. PERFORMING ORGANIZATION NAME AND ADDRESS

NATIONAL BUREAU OF STANDARDS

DEPARTMENT OF COMMERCE

WASHINGTON, DC 20234

10. Projecf/Task/Work Unit No.

11. Contract/Grant No.

12. SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS rsfree^, City, state, ZIP)

DoE

13. Type of Report & Period Covered

NBSIR

14. %»nsoftf]g Agency Code

15. SUPPLEMENTARY NOTES

I

I Document describes a computer program; SF-185, FIPS Software Summary, is attached.

16. ABSTRACT (A 200-word or leas (actual summary of moat sighidcant information. If document includes a significant bibliography or

literature survey, mention it here.) The Midterm Oil and Gas Supply Modeling System (MOGSM) is a computer model based on economic and engineering factors, that projects yearly domestic oil and natural gas

production over a 30-year period. This document describes the methodology used to

produce those curves. The Oil Supply Model consists primarily of three interconnected submodels : a Drilling

Submodel that projects regional exploratory drilling on the basis of information about

the economic gradations of the resource base, the level of future expected prices, and

various constraints to exploratory drilling activity; a Resource Submodel that derives

annual regional production quantities based on exploratory drilling, the prospects for

finding oil, the intensity of development, the fraction of oil-in-place (OTP) which

can be recovered by either primary or secondary methods, and the fraction of proved

reserves which can be produced each year; and an Economic Submodel that calculates a minimum acceptable price for each year's quantity of reserves proved.

The Gas Supply Model produces supply projections for non-associated natural gas and

its coproducts and is identical to the Oil Supply Modeling System with two exceptions

:

gas finding rates are estimated as a function of total drilling (exploratory and

developmental); and the Gas Supply Model has disaggregated the Eastern states into two

regions

.

17. KEY WORDS (six to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name;

separated by semicolons)

Assessment; energy modeling; oil and gas modeling; reservoir analysis; supply

modeling; validation.

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