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.