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Statistical Methods for Estimating Petroleum Resources$
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P.J. Lee and Jo Anne DeGraffenreid

Print publication date: 2008

Print ISBN-13: 9780195331905

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195331905.001.0001

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Introduction

Introduction

Chapter:
(p.3) 1 Introduction
Source:
Statistical Methods for Estimating Petroleum Resources
Author(s):

P.J. Lee

, Jo Anne DeGraffenreid
Publisher:
Oxford University Press
DOI:10.1093/oso/9780195331905.003.0007

Petroleum resource evaluations have been performed by geologists, geophysicists, geochemists, engineers, and statisticians for many decades in an attempt to estimate resource potential in a given region. Because of differences in the geological and statistical methods used for assessment, and the amount and type of data available, resource evaluations often vary. Accounts of various methods have been compiled by Haun (1975), Grenon (1979), Masters (1985), Rice (1986), and Mast et al. (1989). In addition, Lee and Gill (1999) used the Michigan reef play data to evaluate the merits of the log-geometric method of the U.S. Geological Survey (USGS); the PETRIMES method developed by the Geological Survey of Canada (GSC); the Arps and Roberts method; Bickel, Nair, and Wang’s nonparametric finite population method; Kaufman’s anchored method; and the geo-anchored method of Chen and Sinding-Larson. Information required for petroleum resource evaluation includes all available reservoir data and data derived from the drilling of exploratory and development wells. Other essential geological information comes from regional geological, geophysical, and geochemical studies, as well as from work carried out in analogous basins. Any comprehensive resource evaluation procedure must combine raw data with information acquired from regional analysis and comparative studies. The Hydrocarbon Assessment System Processor (HASP) has been used to blend available exploration data with previously gathered information (Energy, Mines and Resources Canada, 1977; Roy, 1979). HASP expresses combinations of exploration data and expert judgment as probability distributions for specific population attributes (such as pool area, net pay, porosity). Since this procedure was first implemented, demands on evaluation capability have steadily increased as evaluation results were increasingly applied to economic analyses. Traditional methods could no longer meet the new demands. A probabilistic formulation for HASP became necessary and was established by Lee and Wang (1983b). This formulation led to the development of the Petroleum Exploration and Resource Evaluation System, PETRIMES (Lee, 1993a, c, d; Lee and Tzeng, 1993; Lee and Wang, 1983a, b, 1984, 1985, 1986, 1987, 1990). Since then, new capabilities and features have been added to the evaluation system (Lee, 1997, 1998). A Windows version was also created (Lee et al., 1999).

Keywords:   comparative studies, discovery, expert judgment, feedback mechanism, geochemical studies, hydrocarbon, net pay, porosity

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