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Abstract
Torres-VerdÃn, C., A. Grijalba-Cuenca, and H. W. J. Debeye,
inversion
and conventional geostatistical-simulation practices for reservoir delineation, 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:10.1306/1063816CA53235
A Comparison between Geostatistical
Inversion
and Conventional Geostatistical-simulation Practices for Reservoir Delineation
Inversion
and Conventional Geostatistical-simulation Practices for Reservoir Delineation
C. Torres-Verd
n,1 A. Grijalba-Cuenca,2 H. W. J. Debeye3
1The University of Texas at Austin Austin, Texas, U.S.A.
2The University of Texas at Austin Austin, Texas, U.S.A.; present address: Occidental Petroleum Corporation, Houston, Texas, U.S.A.
3Fugro-Jason Rotterdam, The Netherlands
ACKNOWLEDGMENTS
The authors express their deepest appreciation to Repsol-YPF for providing the comprehensive
data
set used to construct the field examples described in this chapter. A note of special gratitude goes to Baker Atlas, Halliburton, and Schlumberger, sponsors of the Center of Excellence in Formation Evaluation at the University of Texas at Austin, for their partial funding of this work. Thanks are extended to Fugro-Jason for a generous donation of its complete line of software to the University of Texas at Austin and used to perform the work described in this chapter. Sagar Ronghe and two anonymous reviewers provided valuable constructive comments that improved the first version of the chapter.
ABSTRACT
Geostatistical
inversion
provides a quantitative way to integrate the high vertical resolution of well logs with the dense aerial coverage of poststack three-dimensional
seismic
amplitude
data
. A systematic field study is presented in this chapter to understand the relative merits of geostatistical
inversion
over standard geostatistical-simulation procedures that do not make explicit use of three-dimensional
seismic
amplitude
data
. It is shown that, by making quantitative use of the poststack
seismic
amplitude
data
, geostatistical
inversion
considerably reduces the space of stochastic realizations that honor both the well-log
data
and the spatial semivariograms. Sensitivity analysis also shows that geostatistical
inversion
remains less affected by a perturbation of semivariogram parameters than standard geostatistical simulation. Tests of cross-validation against well-log
data
show that geostatistical
inversion
yields additional information over the average trends otherwise obtained with stochastic simulation. In the vicinity of existing wells, geostatistical
inversion
can potentially infer vertical variations of resolution similar to that of well logs and, at worst, of vertical resolution equal to that of the
seismic
amplitude
data
at locations distant from wells. A drawback of geostatistical
inversion
is the need to convert well-log
data
from depth to
seismic
traveltime. In addition, geostatistical
inversion
may be rendered computationally prohibitive when applied to large
seismic
and well-log
data
sets.
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