TY - JOUR
T1 - Numerical Modeling of Anisotropic Elastic-Wave Sensitivity Propagation for Optimal Design of Time-Lapse Seismic Surveys
AU - Gao , Kai
AU - Huang , Lianjie
JO - Communications in Computational Physics
VL - 1
SP - 442
EP - 458
PY - 2020
DA - 2020/05
SN - 28
DO - http://doi.org/10.4208/cicp.OA-2018-0192
UR - https://global-sci.org/intro/article_detail/cicp/16851.html
KW - Anisotropy, elastic-wave sensitivity, time-lapse seismic monitoring.
AB - <p style="text-align: justify;">Reliable subsurface time-lapse seismic monitoring is crucial for many geophysical applications, such as enhanced geothermal system characterization, geologic
carbon utilization and storage, and conventional and unconventional oil/gas reservoir
characterization, etc. We develop an elastic-wave sensitivity propagation method for
optimal design of cost-effective time-lapse seismic surveys considering the fact that
most of subsurface geologic layers and fractured reservoirs are anisotropic instead
of isotropic. For anisotropic media, we define monitoring criteria using qP- and qS-wave sensitivity energies after decomposing qP- and qS-wave components from the
total elastic-wave sensitivity wavefield using a hybrid time- and frequency-domain
approach. Geophones should therefore be placed at locations with significant qP- and qS-wave sensitivity energies for cost-effective time-lapse seismic monitoring in an
anisotropic geology setting. Our numerical modeling results for a modified anisotropic
Hess model demonstrate that, compared with the isotropic case, subsurface anisotropy
changes the spatial distributions of elastic-wave sensitivity energies. Consequently,
it is necessary to consider subsurface anisotropies when designing the spatial distribution of geophones for cost-effective time-lapse seismic monitoring. This finding
suggests that it is essential to use our new anisotropic elastic-wave sensitivity modeling method for optimal design of time-lapse seismic surveys to reliably monitor the
changes in subsurface reservoirs, fracture zones or target monitoring regions.</p>