Abstract
Previous studies examining the relationship between the groundwater table and seismic velocities have been guided by empirical relationships only. Here, we develop a physics-based model relating fluctuations in groundwater table and pore pressure with seismic velocity variations through changes in effective stress. This model justifies the use of seismic velocity variations for monitoring of the pore pressure. Using a subset of the Groningen seismic network, near-surface velocity changes are estimated over a four-year period, using passive image interferometry. The same velocity changes are predicted by applying the newly derived theory to pressure-head recordings. It is demonstrated that the theory provides a close match of the observed seismic velocity changes.
Highlights
Remote Sens. 2021, 13, 2684. https://Seismic waves contain information about the subsurface; for instance, subsurface seismic properties such as shear modulus and density can be derived from observations of wave propagation
Using data collected in Groningen, the Netherlands, we validate this relationship, and show that it enables us to monitor near surface changes in pore pressure using passive image interferometry
To validate the relationships derived in the previous section, we model surface-wave velocity changes based on pressure-head measurements and compare their results to independent measurements obtained with passive image interferometry
Summary
Seismic waves contain information about the subsurface; for instance, subsurface seismic properties such as shear modulus and density can be derived from observations of wave propagation. The cross-correlation result using, e.g., a day’s worth of data, is compared with a reference Green’s function to obtain the relative change in seismic velocity This technique has been applied to find volcanic precursors [3], to monitor stress changes [4], ensure the safety of civil structures [5], and to monitor groundwater tables [6]. Using the same dense array of 417 stations, a novel implementation of passive image interferometry was tested [19] Following heavy rain, they found a velocity reduction that propagates downward with time. This study provides a physics-based model connecting fluctuations in the pore pressure and vertical compressional stress to seismic velocity variations through changes in effective stress. Using data collected in Groningen, the Netherlands, we validate this relationship, and show that it enables us to monitor near surface (i.e., top 500 m) changes in pore pressure using passive image interferometry
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