# Presentation: 373527

## Non-OPEC Oil Supply Data and Algorithms for SAGE

- prepared for
- Energy Information Administration
- April 13, 2006

## EIA Objectives

- Provide detailed description of conventional oil resource base with ability to investigate alternative resource assumptions
- Develop bottom-up estimates for oil discovery, development and production costs and ability to alter these based on assumptions for future technology
- Create data and algorithms that could go into SAGE to allow price-responsive non-OPEC oil production forecasts
- Data and process should be *understandable*, *traceable* and *verifiable* and updates should be *unburdensome.*

## Scope of EEA Work

- Adapt EEA’s existing World Assessment Unit (WAU) costing model to provide the needed oil resource base and cost information
- Create a standalone (Excel) model of _annual_ world oil production trends based on the WAU economics, historical production, current reserves, resource depletion patterns, oil prices and other factors
- Extract the underlying data and results of the models into data sets and equations that could be used in SAGE
- Write a short report documenting data, methodology and results
- Note: Modifying SAGE is _not_ part of EEA’s work scope for this task

## Project Schedule

- Initial version of World Oil Logistic Model created in February.
- Final version of World Oil Production Model produced at the end of March including oil well accounting.
- Draft final report delivered April 7.
- Final report next week.

## WAU Costing Model

- Created by EEA in 2004
- Undiscovered oil and gas resource base for oil and gas starts with USGS 2000 World Resource Assessment
- Adjustments are made to small fields consistent with field size distributions created by EEA for 2003 NPC gas study for U.S., Canada and Mexico
- WAU model resource costs are based on EEA costing algorithms and consider:
- field size distribution
- location: onshore, offshore water depth
- drilling depth
- finding rate
- financial parameters
- Results are computed by country and assessment unit and can be aggregated by country or region into gas or oil supply curves
- Output from WAU Model for this project will be country-level supply curve segments for crude oil resource base including new fields and growth to existing fields.

## Annual Oil Production Model (WOLM)

- This is a country-level model with annual historical data from 1980 to present and forecasts to year 2100
- Spreadsheet built to easily accommodate annual updates to historical data each year
- Underlying concept of forecast is a “resource depletion model” (akin to Hubert or logistic curve) for which area under production curve is equal to resource base

## Key Relationships for Hubbert or Logistic Curves

**Prod/Cum = Intercept + Slope(Cum)**
**Prod = Intercept(Cum) + Slope(Cum****2****)**
**RB = -Intercept/Slope**
**Slope= (Prod/Cum) / (Cum-RB)**
**Intercept = -Slope(RB)**
***where:***
***Prod=annual production***
***Cum=cumulative production***
***RB=ultimate resource base***
**Note also: Prod = Intercept(Cum) - Intercept(Cum****2****)/RB***** ***

## WOLM Differs from Simpler Depletion Models

- Resource base economics are explicit and vary based on oil prices and technology drivers
- Shape of production curve is endogenous (*see figure*)
- WOLM accounting includes annual reserves additions and wells drilled

## Data Sources for WOLM

- To keep consistent with other EIA models and data series, historical crude oil and NGL production data is from EIA (however some adjustments to to historical nonconventional oil production will have to be made)
- All time cumulative production is from USGS (originally from PetroConsultants) with adjustments and estimates made by EEA for some of the smaller countries.
- Reserves are from EIA also (originally from Oil and Gas Journal.  EEA adjustments removed nonconventional oil reserves.
- Historical producing wells and new oil wells drilled are from O&GJ and World Oil magazines. Unfortunately, data for some countries is sparse.
- Resource base and cost curves come from WAU based on USGS resource assessment with costing algorithms from EEA.  Model user can adjust resource base in Production Model to create alternative scenarios.

## Information Processing and Flow

- USGS
- Resource
- Assessment

- EEA
- Cost
- Algorithms

- Scenario
- Inputs

- Financial
- Assumptions

- Reserves

-  Production
-  History

- Well Data

**WAU **
**Cost Model**

- Country-level
- Crude Oil
- Supply Curves

**Oil **
**Production **
**Model**

- Annual
- Production
-  Forecasts

**SAGE**

**Data and **
**Parameters **
**for Non-OPEC **
**Regions**

## Representation of Supply Curves

**prc1 = price at first point on curve ($20)**
**prc1 = price at second point on curve ($50)**
**prc3 = price at third point on curve ($100)**
**rbf1 = portion resource base economic at first price point**
**rbf2 = portion of resource base economic at second price point**
**rbf3 = portion of resource base economic at third price point**
**These three points on the supply curve are used to develop a continuous equation that gives the economic resource base (as a fraction) as a function of oil price.  The coefficients of that equation are defined as:**
**a3pt = rbf3 - rbf1**
**b3pt = LOG((rbf2-rbf1)/a3pt)/LOG((prc2-prc1)/(prc3-prc1))**
**The supply curve function that finds the economic resource as a function of price (variable “****price****”) is:**
**SCF = rbf1 + a3pt*((****price****-prc1)/(prc3-prc1))^b3pt**

## Example of Supply Curve

## Production as Function of Resource Base and Cumulative Production

**P(t) = (CPL1+PL1) * (PL1/(CPL1*(CPL1-****RBL1****))*((CPL1+PL1) -  ****RBL1****))**
***where:***
***PL1     ******	******	******= prior period production ***
***CPL1    ******	******	******= prior period cumulative production***
***RBL1    ******	******	******= prior period resource base***

## Production in One Equation (substitute supply curve equation for RBL1)

**P(t) = (CPL1+PL1) * (PL1/(CPL1*(CPL1-****(rbf1 + a3pt * ((PRICEL1-prc1)/(prc3-prc1))^b3pt) * RB))*****((CPL1+PL1) - ****(rbf1**
**+ a3pt*((PRICEL1-prc1)/(prc3 - prc1))^b3pt) * RB))**
***where:***
***PRICEL1 ******	******= prior period price ***
***PL1     ******	******	******= prior period production ***
***CPL1    ******	******	******= prior period cumulative production***

## Production Acceleration (Shape Multiplier)

**SM(t)= MAX(MIN(MAX(0,PRICE-Parm1)*Parm2,SM(t-1) +0.005),SM(t-1) -0.005)**
**P(t) *****after shape adjustment***** = P(t) * (SM(t) - SM(t-1))**
***Where:***
***Parm1 = the threshold price above which the shape adjustment is applied ($25)***
***Parm2 = shaping coefficient (0.002)***

## Example Results at Three Oil Price Levels (Billion barrels per year, sum of country-level data)

## Issues for SAGE Implementation

- Representation of upstream technology advances (in supply curves or in SAGE)
- Meaning of production in SAGE period (e.g. average of all years vs. last year)
- New field resource base (e.g. Canada is 2,774 MMbbl vs. NPC estimate of 11,745 MMbbl)
- Growth resource base (WAU world total is 390 ex. US/Can vs. 612 billion barrels for USGS)
- Definitions and base year calibration of production and reserves.
- How to deal with nonproducing areas (e.g. Greenland)