Abstract
Seismic waveform inversion can be an important tool for reservoir characterization because high-resolution (within the seismic-frequency band) images of elastic parameters are obtainable from good quality seismic data. A detailed description of the velocity field with both high- and low-frequency variations is essential for delineating elastic properties of the medium for direct detection of hydrocarbon, lithologic discrimination, and estimation of fluid contents. Conventionally, amplitude-variation-with-offset (AVO) analysis determines fractional changes in P-impedance and Poisson's ratio from a linear fit of normal-moveout (NMO) corrected P-reflection amplitude to a two- or three-term approximation of reflection coefficients. Although, AVO analysis gives a useful estimation of elastic properties of the subsurface from AVO attributes, its limitation is well recognized; for example, it deals with “primaries only” models and is inadequate to account for mode-converted waves and internal multiples. In spite of several sources of error (such as random and coherent noise and a 1D earth-model assumption), a prestack seismic waveform inversion is generally desirable for more accurate mapping of the variation of the elastic properties of the subsurface. However, practical implementation of such an inversion scheme on a routine basis becomes discouragingly difficult as (1) the inverse problem is highly nonlinear, (2) the error function (a measure of data misfit in general) possesses multimodality, (3) the inverse problem is extremely computer intensive, and (4) inversion needs better data acquisition systems and data processing steps to preserve true amplitude in order to get precise estimates of elastic properties of the medium. Recently, Sen and Roy (2003) developed a regularized gradient-descent–based waveform inversion algorithm that is highly robust and addresses many of the problems encountered in wavefrom inversion. This paper is a sequel to that paper in that we demonstrate the applicability of the technique to a field data set from a gas field in the Gulf …
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