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The AAPG/Datapages Combined Publications Database
AAPG Bulletin
Abstract
AAPG Bulletin, V.
DOI: 10.1306/0504171620517153
Combining seismic reservoir characterization workflows with basin modeling in the deepwater Gulf of Mexico Mississippi Canyon area
Wisam H. AlKawai,1
Tapan Mukerji,2
Allegra Hosford Scheirer,3
and Stephan A. Graham4
1Department of Geological Sciences, Stanford University, 450 Serra Mall, Bldg. 320, Rm.118, Stanford, California 94305; [email protected]
2Department of Earth Resources Engineering and Department of Geophysics, Stanford University, 367 Panama Street, Stanford, California 94305; [email protected]
3Department of Geological Sciences, Stanford University, 450 Serra Mall, Bldg. 320, Rm.118, Stanford, California 94305; [email protected]
4Department of Geological Sciences, Stanford University, 450 Serra Mall, Bldg. 320, Rm.118, Stanford, California 94305; [email protected]
ABSTRACT
In this study, we explore the value added by application of basin modeling to seismic reservoir characterization in a structurally complex area. We focus on the Thunder Horse minibasin in the Gulf of Mexico. First, we build a two-dimensional basin model along the strike direction of the main structure in the area to investigate differences in pressure and thermal histories. The results suggest differences in both histories across the study area, and these differences can be reasonably assessed by basin modeling even with a single well calibration. We combine basin modeling results with rock physics
models to build a training data set of seismic impedance derived lithofacies. The training data set thus captures spatial trends in the desired property beyond available well data. In addition, we demonstrate how to improve the seismic inversion results by integrating the basin modeling insights with limited well data. Our new workflow combining basin modeling output with rock
physics
and impedance-based lithofacies prediction significantly improves the predicted spatial distribution of reservoir lithofacies in the scenarios of spatially limited well control.
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