Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: A case study from the Gulf of Mexico

Abstract

Nonrepeatable noise, caused by differences in vintages of seismic acquisition and processing, can often make comparison and interpretation of time‐lapse 3‐D seismic data sets for reservoir monitoring misleading or futile. In this Gulf of Mexico case study, the major causes of nonrepeatable noise in the data sets are the result of differences in survey acquisition geometry and binning, temporal and spatial amplitude gain, wavelet bandwidth and phase, differential static time shifts, and relative mispositioning of imaged reflection events. We attenuate these acquisition and processing differences by developing and applying a cross‐equalization data processing flow for time‐lapse seismic data. The cross‐equalization flow consists of regridding the two data sets to a common grid; applying a space and time‐variant amplitude envelope balance; applying a first pass of matched filter corrections for global amplitude, bandwidth, phase and static shift corrections, followed by a dynamic warp to align mispositioned events; and, finally, running a second pass of constrained space‐variant matched filter operators. Difference sections obtained by subtracting the two data sets after each step of the cross‐equalization processing flow show a progressive reduction of nonrepeatable noise and a simultaneous improvement in time‐lapse reservoir signal.