HPC19 - 3D Onshore Shallow Velocity Model Building Using Full Waveform Inversion with GPUs and Static Task Distribution

Abstract

Summary Full Waveform Inversion (FWI) can establish an accurate shallow velocity model as a wave-based solution. The accurate velocity model is essential for generating high-fidelity seismic images to find reservoirs. Moreover, its successful implementation on a 3D onshore dataset depends on the quality of low-frequency components of seismic data. A two-stage waveform inversion workflow has been carried out to obtain a high-resolution shallow velocity model on the 3D land dataset to overcome this problem. As a first stage of the workflow, we update the velocity model to minimize the time difference of the first arrivals between field and synthetic data. In the second stage, we perform traveltime-oriented FWI to update the model by minimizing phase differences of seismic events between field and modeled data. Most of the functions used in waveform inversion are written by the compute unified device architecture (CUDA) program language to optimize performances further and reduce computing time. In addition, we switch on the static task distribution to our waveform inversion implementations instead of the dynamic task distribution, which is proven a powerful scheduler in the reverse time migration program.