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Chapter from: SG
42: Applications of 3-D Seismic Data to Exploration and Production
Paul Weimer and Thomas L. David
M. A. Chapin, G. M. Tiller, and M. J. Mahaffie
Published 1996 as
part of Studies in Geology 42
Copyright © 1996 The American Association of Petroleum
Geologists. All Rights Reserved.
*Editorial Note: Page numbers in this digital version
(HTML and PDF) do not correspond to those of the hardcopy.
Otherwise, the two are the same.
Chapter 12: 3-D
Architecture Modeling Using High-Resolution Seismic Data and Sparse Well
Control: Example from the Mars "Pink" Reservoir, Mississippi Canyon Area,
Gulf of Mexico
M. A. Chapin, G. M. Tiller, and M. J.
||Chapin, M. A.,
G. M. Tiller, and M. J. Mahaffie, 3-D architecture modeling using high-resolution
seismic data and sparse well control: example from the Mars "Pink" Reservoir,
Mississippi Canyon Area, Gulf of Mexico, in P. Weimer and T. L.
Davis, eds., AAPG Studies in Geology No. 42 and SEG Geophysical
Developments Series No. 5, AAPG/SEG, Tulsa, p. 123-132.
Most deep-water development
projects are planned using high-quality 3-D seismic data and sparse well
control. Economic considerations require large reservoir volumes to be
drained with relatively few wells. We have used 3-D seismic data to constrain
large-scale, deterministic reservoir bodies in a 3-D architecture model
of Pliocene turbidite sands of the "E," or "Pink," reservoir, Prospect
Mars, Mississippi Canyon Areas 763 and 807, Gulf of Mexico. A geological
interpretation derived from 3-D seismic data and three wells was linked
to 3-D architecture models through seismic inversion, resulting in a reservoir
rock property distribution incorporating all available data. High-resolution
reprocessing of a high-quality marine seismic dataset resulted in the ability
to deterministically map sedimentary reservoir bodies. Distinguishing subtle
stratigraphic shingles from faults was accomplished by detailed, loop-level
mapping and was important to characterize the different types of reservoir
compartments. Seismic inversion was used to detune the seismic amplitude,
adjust the sand-body thickness, and update the rock properties. This modeling
project illustrates how high-quality seismic data and architecture models
can be combined in a pre-development phase of a prospect, in order to optimize
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