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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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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 17 June 2021

More about Discovery Process Models

More about Discovery Process Models

Chapter:
(p.61) 4 More about Discovery Process Models
Source:
Statistical Methods for Estimating Petroleum Resources
Author(s):

P.J. Lee

, Jo Anne DeGraffenreid
Publisher:
Oxford University Press
DOI:10.1093/oso/9780195331905.003.0010

In Chapter 3 we discussed the concepts, functions, and applications of the two discovery process models LDSCV and NDSCV. In this chapter we will use various simulated populations to validate these two models to examine whether their performance meets our expectations. In addition, lognormal assumptions are applied to Weibull and Pareto populations to assess the impact on petroleum evaluation as a result of incorrect specification of probability distributions. A mixed population of two lognormal populations and a mixed population of lognormal, Weibull, and Pareto populations were generated to test the impact of mixed populations on assessment quality. NDSCV was then applied to all these data sets to validate the performance of the models. Finally, justifications for choosing a lognormal distribution in petroleum assessments are discussed in detail.

Keywords:   basin, density function, economic analysis, field/fields, gamma distribution, law of proportionate effect, log pool size, matching process

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