Non-stationary inversion of seismic data for fracture compliances in azimuthally anisotropic media

Abstract

Fractures and tectonic settings cause azimuthal anisotropy in reservoirs. Recognizing the fracture model from the seismic data is a useful tool for identifying the productive zone in the reservoirs. We applied azimuthal velocity analysis in seismic processing to improve image quality and to estimate anisotropic model parameters. Using azimuthal residual moveout analysis, we predicted the direction of azimuthal anisotropy in the reservoir, and found that the results are consistent with fracture orientations obtained from the image logs in the reservoirs. Bayes’ theorem, and a cascaded procedure in least-squares inversion, matching observed amplitudes to linearized Zoeppritz equations, were used to estimate the elastic moduli in a first step and normal and tangential fracture weaknesses in a second step. We used laboratory experiments on core samples to validate the first step inversion results. We found that the propagation wavelet varied in space and reflection time, and so a library of extracted wavelets in the time-frequency domain was used for seismic inversion. Maps of computed fracture fluid index and the estimated fracture weaknesses help to visualize the role of fractures in reservoir productivity and revealed a consistency with the seismic peak frequency attribute in identifying zones of highly compliant fracture fill. The estimated fracture model demonstrates a good fit with the fractures seen in the available core samples and implies that the fracture fluid index is a useful attribute for determining the productive zones in the reservoir.