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 timelapse reservoir signal.

Geophysical monitoring at the Ketzin pilot site for CO 2 storage: New insights into the plume evolution

“…Cross-equalization of post-stack seismic datasets typically includes bandwidth and phase equalization to compensate for different source wavelets, and amplitude balancing to scale the data to the same amplitude (or energy) level (Rickett and Lumley, 2001). The cross-equalized trace is calculated by convolving the input trace with the estimated wavelet operator, to shape and match the reflection data of one survey to another (Ross et al, 1996).…”

Surface-consistent matching filters for time-lapse processing

“…Generally, this cross-equalization process reduces the nonrepeatablity effects in seismic acquisition and processing and produces a better timelapse image (Ross et al, 1996;Rickett and Lumley, 2001). Other time-lapse processing techniques are prestack "parallel" processing and "simultaneous" processing described by Lumley et al (2003) which aim to reduce undesired time-lapse differences without match filtering.…”

A Novel 3D Viscoelastic Acoustic Wave Equation Based Update Method for Reservoir History Matching

“…With the advances in seismic techniques and the enhancements in data processing, reservoir monitoring using time lapse seismic data has become increasingly feasible for a variety of reservoirs. Extensive work has been conducted in better detecting the time lapse changes in the reservoir using seismic techniques [1][2][3][4] and has provided a more detailed understanding of the dynamics in the reservoir as compared to solely using production data. Time lapse seismic data have increasingly been utilized for complementing production data in reservoir history matching, having shown to yield significantly better subsurface parameter estimates and history matches [5][6][7][8] .…”