Multi-scale Elastic-Waveform Inversion for Geothermal Reservoir Characterization

Abstract

Accurate subsurface velocity models are crucial for reliable geothermal reservoir characterization. Elastic-waveform inversion (EWI) is a powerful tool for building high-resolution subsurface velocity models with seismic data. However, the exact subsurface velocity model is unknown for a given geothermal field and therefore, conventional single-scale EWI often fails to reconstruct an accurate velocity model. We develop a novel multi-scale EWI method to improve the reliability of velocity inversion. Our new method employs multi-stage filtering in both the data and model domains. We apply a frequency bandpass filter to seismic data, and invert seismic data from a low-frequency band to a high-frequency band. During inversion with each frequency band, we apply the wavelet transform to the velocity inversion result to improve the convergence. We validate our new multi-scale EWI method using synthetic vertical seismic profiling data for an elastic model of Raft River enhanced geothermal system field, and demonstrate that our new method produces more accurate velocity inversion results compared to conventional single-scale EWI.