Estimation of fluid salinity using coseismic electric signal generated by an earthquake

Abstract

SUMMARY The seismoelectric effect is a coupling phenomenon between the seismic wavefield and electromagnetic field caused by the electric double layer in a fluid-saturated porous medium. As seismoelectric signals are sensitive to porous medium properties, such as the water saturation, salinity, porosity and permeability, they have good potential for imaging the structure and estimating underground parameters. In this study, we proposed an inversion method for estimating the salinity using coseismic electric fields generated by electrokinetic effects. The method was established by waveform matching between synthetic and observed coseismic electric signals based on a horizontally layered model. We used an L1 norm measure to construct the regularization term and achieve a high-resolution layer interface. Subsequently, we applied the first-order Taylor expansion to estimate the sensitivity and used logarithm transformation to constrain the range of parameters and reduce the solution space. Finally, we used an iteratively reweighted least-squares method to solve the final Gauss–Newton-type inversion function in each iteration to obtain the model update until the inversion converged. Numerical experiments were conducted to test the resolution, anti-noise ability and stability of the inversion algorithm. These results demonstrate that the proposed method can effectively recover the salinity structure, which broadens the application of seismoelectric effects. We further applied the method to the Mw 6.5 Jiuzhaigou earthquake in 2017 and used the observed coseismic electric field to estimate the salinity and conductivity beneath the station.