Elastic geometric-mean reverse time migration for source imaging

Abstract

Passive source location is a fundamental problem in earthquake seismology and reservoir characterization with fluid injection. It has been shown that geometric-mean reverse time migration (GmRTM) can produce source images with improved resolution and fewer migration artifacts than conventional time-reversal imaging in acoustic media. However, the acoustic assumption often requires data windowing and polarity correction when we apply it to the elastic data, which involves manual efforts and introduces uncertainties. Therefore, we have extended this crosscorrelation-based GmRTM imaging method to elastic media. Back-propagation and Helmholtz decomposition are conducted individually for each receiver wavefield, after which we apply zero-lag crosscorrelations over the decoupled P or/and S wavefields to obtain the corresponding P-, S-, and PS-source images. Considering the influences of random noise, anisotropy, and interferences from multiple sources, we test the proposed elastic GmRTM method on a synthetic example with a layered model and determine its advantages over other imaging conditions (e.g., time-reversal imaging). The method is further validated using another synthetic test based on the elastic Marmousi model and a field-data example from Oklahoma.