Well-Driven Seismic
Processing and
Reservoir Characterization
By
Stephen Patrick Morice1, Stefano Volterrani2, Tarek Nafie2, Ayman Shabrawi2
(1) WesternGeco, Gatwick Airport, United Kingdom (2) WesternGeco, Cairo, Egypt
Our “Well-Driven” approach to surface-seismic
processing integrates borehole
data
throughout the processing sequence to achieve accurate depth images with
enhanced resolution, and constrained reservoir attributes from the
seismic
and
well
data
.
Borehole data
are used to guide pre- and post-stack
seismic
processing
testing by quantifying the match between migrated test volumes and the synthetic
seismogram or VSP corridor stack (e.g. Poggiagliolmi, 1998; Scott et al., 1999).
Attributes based on the correlation between well
data
and the
seismic
data
at
the well location, and on characteristics of the extracted wavelet provide
objective criteria for processing parameter selection.
Intrinsic processing parameters are derived from analysis of VSP and log
data
. An Earth model of P- and S-wave velocities, densities, attenuation and VTI
anisotropy is built at the well location and extended over 2D or 3D. The model
is used to drive offset-dependent attenuation compensation, geometric spreading
corrections, demultiple operators, long-offset move-out corrections,
ray-trace-based muting, travel-time tables for pre-stack depth migration and AVO
analysis (Leaney et al., 2001).
Crucial to our method is appropriate conditioning of well data
. Sonic and
density curves are edited using a multi-well regression scheme through
interactive, iterative calibration to VSP and surface-
seismic
data
.
With the seismic
data
processing sequence optimized to the borehole
data
, we
may proceed with greater confidence into
seismic
interpretation
and the
derivation of reservoir attributes through calibration and classification of
seismic
attributes with petrophysical and rock-physical borehole
data
. This
paper describes our borehole-integrated processing and reservoir
characterization methodology, showing examples from several recent projects.