Analysis of the resolution of InSAR data inversion and application of the inversion residual to identify shallow hazards

We conducted a study to investigate the sensitivity of InSAR measurement to subsurface strain change and developed an inversion framework to use InSAR data for subsurface surveillance. Using both spatial domain and spatial frequency domain analysis, we demonstrated that the earth behaves as a low-pass filter in its transmission of deformation from the subsurface to the earth’s surface. As a result of this low-pass filtering effect of the earth, the horizontal resolution of InSAR images is roughly equal to the depth of the targeted activity. Therefore, the goal of InSAR data inversion is to recover high spatial-frequency subsurface strains from InSAR measurements. Since changes in the reservoir tend to have a lower spatial-frequency InSAR signature, high spatial-frequency surface displacement can be associated with shallow overburden activities. Based on these insights, we developed an inversion workflow that takes into account both overburden and reservoir strain changes, and applied it to an InSAR dataset from the San Joaquin Valley. Our results showed that an inversion model that only considers strain changes in the reservoir produces large, spatially localized inversion residuals in locations with known shallow overburden activity. A residual analysis revealed that high spatial frequency anomalies in InSAR data can be used to identify shallow activities.