Simultaneous inversion of multiple microseismic data for event locations and velocity model with Bayesian inference

We applied Bayesian inference for simultaneous inversion of multiple microseismic data for event locations and velocity models. The traditional method of using a predetermined ve- locity model for event location is subject to large uncertainty if prior information of the velocity model is poor. Our study shows that microseismic data can improve the velocity model, which is usually a major source of location uncertainty. Also, the developed method can quantify the uncertainty of the mi- croseismic location estimation. Its successful application on both synthetic examples and Newberry enhanced geothermal system (EGS) demonstrates its robustness over the traditional least-square traveltime inversion. Comparison with location result of the traditional method shows that we can effectively improve the accuracy of microseismic event location thanks to the improved velocity model