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Torres-Verdín, C., A. Grijalba-Cuenca, and H. W. J. Debeye,
A Comparison between Geostatistical Inversion and Conventional Geostatistical-simulation Practices for Reservoir Delineation
C. Torres-Verdn,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
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.
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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