Anisotropy: Who cares?
By
Constantine Tsingas1, Don Pham2, Ruben Martinez2, Maurice Gidlow3
(1) PGS
Data
Processing
, London, England (2) PGS Research, (3) PGS
Data
Processing
,
The reservoir characterization process increases the confidence level on the
description of the rock and fluid properties which make up the constituents of
reservoirs, both clastic and carbonate. With the increasing resolution of
seismic
observations and with the use of multi-component acquisition &
processing
technologies, there is a growing awareness that the assumption of
isotropy is often violated. Thus, methods which allow the proper imaging and
reservoir characterization, in the presence of anisotropy, are highly desirable.
In the presentation we will show using synthetic and real
data
examples
various
seismic
data
processing
technologies which incorporate anisotropic
parameters and aim to correct the kinematics and dynamics of the
seismic
wave
propagation in anisotropic media. Time imaging algorithms operating in the pre-
or post-stack domain will show the effect of incorporating not only the NMO
velocity for horizontal reflector (V(0)NMO) but also the anellipticity
coefficient h (eta). Depth imaging algorithms, however, will depict that the
above two parameters are not sufficient to properly position the structures at
the correct spatial and depth locations. In this paper, we will demonstrate that
for a proper prestack depth migration methodology, one needs to incorporate
Thomsen’s parameters e (epsilon) and d (delta) in addition to Vo in order to
obtain the correct travel times required during a PSDM procedure. Also,
traditional AVO theory breaks down in the presence of anisotropy. We will
demonstrate the use of more sophisticated AVO algorithms in the description of
anisotropic reservoirs, as well as isotropic reservoirs with anisotropic
overburden.