Capability of elastic-wave imaging for monitoring conformance and containment in geologic carbon storage

Abstract

• We have studied the capability of elastic-wave imaging for monitoring conformance and containment in geologic carbon storage, particularly for monitoring secondary CO 2 plumes, using the waveform information of time-lapse multi-component seismic reflection data for the Kimberlina-2 models. We have described the elastic models of different secondary CO 2 plume scenarios and performed elastic-wave modeling and imaging for these models. Our results show that seismic imaging with elastic least-squares reverse-time migration of multi-component data is able to locate the secondary CO 2 plumes at different depths in the Kimberlina-2 model. With noise-free data, the time-lapse seismic images of CO 2 migration scenarios also reveal the growth of the secondary CO 2 plumes with time. We have also demonstrated that elastic-wave imaging using multi-component data can provide the relative magnitude difference in elastic properties caused by the secondary CO 2 plumes. Even with noisy data, seismic imaging using elastic LSRTM is capable of locating early stages of the secondary CO 2 plumes. Seismic noise has more impact on locating the very early stage of the secondary CO 2 plumes than those in the later stages. Our image noise analysis further suggests that the elastic-wave imaging capability decreases for the acquisition geometry with sparser shots/receivers or shorter recording offsets. The image sign-to-noise ratio is approximately proportional to the square root of the total number of seismic traces used for elastic-wave imaging. This relationship can be use to guide seismic monitoring design. Note that it is difficult to use multi-component data to accurately invert for the time-lapse change of an elastic property if its change is much smaller than those of the other elastic properties. We will study how seismic noises can affect the CO 2 detection threshold in the future. Commercial-scale geologic carbon storage requires monitoring for conformance and containment of the injected CO 2 , including secondary CO 2 plumes. Detecting and locating secondary CO 2 plumes are even more challenging than monitoring the primary CO 2 plumes. We study the capability of elastic-wave imaging for monitoring secondary CO 2 plumes with time-lapse multi-component data from 3D elastic models built using the geologic settings of the Kimberlina site located in the San Joaquin Basin, California. In the numerical simulation of CO 2 migration in these time-lapse Kimberlina-2 models, CO 2 migrates from the storage reservoir along a steeply dipping fault and forms secondary CO 2 plumes in formations at different depths. In our study, we extract a 2D slice through the location of the secondary CO 2 plumes to perform elastic-wave modeling and imaging based on numerical simulation to the elastic-wave equation. We use a finite-difference algorithm to generate time-lapse multi-component synthetic elastic-wave reflection data and employ elastic least-squares reverse-time migration to produce images of P- and S-wave velocities and density for various sizes of the secondary CO 2 plumes after CO 2 migration through the fault. Our imaging results show that, for noise-free data, elastic-wave imaging accurately locates the secondary CO 2 plumes at different depths and reveals the growth of the size of the secondary CO 2 plumes with years of CO 2 migration. The relative amplitude differences of seismic images reveal how secondary CO 2 plumes change elastic parameters differently. We further study the capability of elastic-wave imaging for monitoring the secondary CO 2 plumes using noisy synthetic data containing seismic noise extracted from a field surface seismic dataset. We evaluate elastic-wave imaging capability for monitoring secondary CO 2 plumes using different noise levels and different acquisition geometries. Our results demonstrate that elastic-wave imaging is capable of locating secondary CO 2 plumes even with strong noisy data, and a relatively higher signal-to-noise ratio (SNR) is needed to locate (or image) the secondary CO 2 plumes at earlier stages. The imaging capability decreases for sparser or shorter-offset acquisition geometry. Our results indicate that the image SNR is approximately proportional to the square root of the total trace number used for elastic-wave imaging. This relationship can be used to guide whether a denser or longer-offset acquisition geometry is worth the increase of seismic image quality for improving the capability to locate secondary CO 2 plumes. Note that multi-component data can inform us whether the time-lapse change of one elastic property is much smaller than others, but it is difficult to accurately invert for the time-lapse change of an elastic property if its change is relatively much smaller than the changes of the other elastic properties.