Statistical Issues in the Assessment of Undiscovered Oil and Gas Resources

Prior to his untimely death, my friend Dave Wood gave me wise counsel about how best to organize a paper that would describe the uses of statistics in oil and gas exploration. A preliminary reconnaissance of the literature alerted me to the enormous range of topics that might be covered. Geology, geophysics with particular attention to seismology, geochemistry, petroleum engineering and petroleum economics-each of these disciplines plays an important role in petroleum exploration and each weaves statistical thinking into its fabric in a distinctive way. An exhaustive review would be book length. Dave and I agreed that a timely review paper of reasonable length would (1) illustrate the range of statistical thinking of oil and gas explorationists; (2) concentrate on topics with statistical novelty, show how statistical thinking can lead to better decision making and let the reader know about important controversies that might be resolved by better use of statistical methods; (3) focus on topics that are directly relevant to exploration decision making and resource estimation. In response to Dave's sensible suggestions, the U. S. Department of Interior's 1989 assessment of U.S. undiscovered oil and gas will be a tour map for a short trip through a large territory of statistical methods and applications. If Dave were here to appraise this review, I know it would be better than it is.

[1]  G. M. Kaufman,et al.  A Probabilistic Model of Oil and Gas Discovery , 1975 .

[2]  F. Agterberg,et al.  Regression models for estimating mineral resources from geological map data , 1980 .

[3]  J. H. Schuenemeyer,et al.  Estimation of the future rates of oil and gas discoveries in the western Gulf of Mexico. Professional paper , 1981 .

[4]  J. Hájek,et al.  Sampling from a finite population , 1982 .

[5]  Daniel Rabinowitz.  Using exploration history to estimate undiscovered resources , 1991 .

[6]  L. Gordon.  Estimation for Large Successive Samples with Unknown Inclusion Probabilities , 1993 .

[7]  J. H. Schuenemeyer,et al.  Estimating Potential for Small Fields in Mature Petroleum Province: Discussion (1) , 1990 .

[8]  T. Postelnicu,et al.  Foundations of inference in survey sampling , 1977 .

[9]  Robert A. Crovelli.  A Comparison of Analytic and Simulation Methods for Petroleum Play Analysis and Aggregation , 1986 .

[10]  Emil D. Attanasi,et al.  Estimates of undiscovered conventional oil and gas resources in the United States; a part of the Nation's energy endowment , 1989 .

[11]  Gordon M. Kaufman,et al.  Are wildcat well outcomes dependent or independent? , 1992 .

[12]  John C. Davis,et al.  Estimating Potential for Small Fields in Mature Petroleum Province , 1989 .

[13]  Donald A. Singer,et al.  Relative efficiencies of square and triangular grids in the search for elliptically shaped resource target , 1975 .

[14]  N. Wrigley,et al.  Graphical diagnostics for logistic oil exploration models , 1986 .

[15]  John C. Houghton,et al.  Use of the truncated shifted Pareto distribution in assessing size distribution of oil and gas fields , 1988 .

[16]  David White.  Assessing Oil and Gas Plays in Facies-Cycle Wedges , 1980 .

[17]  J. Aitchison,et al.  The Lognormal Distribution. , 1958 .

[18]  Emil D. Attanasi,et al.  Lognormal field size distributions as a consequence of economic truncation , 1985 .

[19]  R. McCammon.  Target intersection probabilities for parallel-line and continuous-grid types of search , 1977 .

[20]  F. Demirmen,et al.  The Creaming Method: A Bayesian Procedure to Forecast Future Oil and Gas Discoveries in Mature Exploration Provinces , 1981 .

[21]  B. D. Ripley,et al.  Point Processes for the Earth Sciences , 1988 .

[22]  R. A. Crovelli.  Probability theory versus simulation of petroleum potential in play analysis , 1987 .

[23]  V. Nair,et al.  Statistical Analysis of Oil and Gas Discovery Data , 1988 .

[24]  Gordon. Kaufman,et al.  Statistical decision and related techniques in oil and gas exploration , 1963 .

[25]  R. Stine,et al.  Volume and area of oil fields and their impact on order of discovery , 1980 .

[26]  John H. Doveton,et al.  Probability methods in oil exploration , 1977 .

[27]  P. J. Lee,et al.  Conditional analysis for petroleum resource evaluations , 1983 .

[28]  日野 寛三,et al.  対数正規分布(Lognormal Distribution)のあてはめについて , 1994 .

[29]  C. Chung,et al.  Computer program for the logistic model to estimate the probability of occurrence of discrete events , 1978 .

[30]  L. J. Drew.  Grid-drilling exploration and its application to the search for petroleum , 1967 .

[31]  Giovanni Andreatta,et al.  Estimation of Finite Population Properties When Sampling is without Replacement and Proportional to Magnitude , 1986 .

[32]  Morris Albert Adelman.  Energy Resources in an Uncertain Future: Coal, Gas, Oil, and Uranium Supply Forecasting , 1984 .

[33]  Michael Edward Hohn,et al.  Geostatistics and Petroleum Geology , 1988 .

[34]  P. Bickel,et al.  NONPARAMETRIC INFERENCE UNDER BIASED SAMPLING FROM A FINITE POPULATION , 1992 .

[35]  Robert Haining,et al.  Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95 , 1993 .

[36]  P. J. Lee,et al.  Probabilistic formulation of a method for the evaluation of petroleum resources , 1983 .

[37]  D. J. Forman,et al.  Improved Statistical Method for Assessment of Undiscovered Petroleum Resources , 1985 .

[38]  J. H. Schuenemeyer,et al.  A procedure to estimate the parent population of the size of oil and gas fields as revealed by a study of economic truncation , 1983 .

[39]  Jerrold M. Pachman.  Optimization of Seismic Reconnaissance Surveys in Petroleum Exploration , 1966 .