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The AAPG/Datapages Combined Publications Database
AAPG Special Volumes
Abstract
Pyrcz, M. J.,E. Gringarten, P. Frykman, and C. V. Deutsch,
parameters
for geostatistical simulation, in T. C. Coburn, J. M. Yarus, and R. L. Chambers, eds., Stochastic modeling and geostatistics: Principles, methods, and case studies, volume II: AAPG Computer Applications in Geology 5, p.
DOI:10.1306/1063811CA53230
Representative Input
Parameters
for Geostatistical Simulation
Parameters
for Geostatistical Simulation
M. J. Pyrcz,1 E. Gringarten,2 P. Frykman,3 C. V. Deutsch4
1Chevron Energy Technology Company Houston, Texas, U.S.A.
2Earth Decision Houston, Texas, U.S.A.
3Geological Survey of Denmark and Greenland Copenhagen, Denmark
4University of Alberta Edmonton, Alberta, Canada
ABSTRACT
Geostatistical-simulation techniques are increasingly being used to create heterogeneous realizations for flow modeling and to assess uncertainty in hydrocarbon resources and reserves. These geostatistical-simulation techniques reproduce the input statistics within ergodic fluctuations. The input statistics representing various model
parameters
must be computed from data that are representative of the entire domain being modeled. Geostatistical simulation does not accommodate a lack of representativeness in the data. Moreover, the extent to which the input statistics are reproduced depends almost exclusively on the size of the modeling domain relative to the range of spatial correlation; fluctuations in realizations of the full reservoir model do not depend entirely on the uncertainty of the input statistics. It is necessary to explicitly incorporate the uncertainty of the input statistics because they have a much larger and more realistic impact on the uncertainty of the full reservoir model than stochastic fluctuations. The best practices for
determining
representative input values of model
parameters
and quantification of their uncertainty are presented in this chapter.
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