Seismic Modeling and Migration with Random Boundaries on the NEC SX-Aurora TSUBASA

TL;DR

This paper introduces a novel seismic imaging method using random boundary conditions to reduce storage needs and improve efficiency in reverse time migration, validated on benchmark datasets with promising results.

Contribution

It proposes a new wave equation with random boundary conditions for wavefield reconstruction, reducing storage and computational demands in seismic imaging.

Findings

RTM with wavefield reconstruction outperforms traditional methods in execution time

The approach reduces disk storage requirements significantly

Vector processor implementation simplifies code modifications for large 3D grids

Abstract

Seismic imaging is a computationally demanding and data-intensive activity in the oil and gas industry. Reverse Time Migration (RTM) used in seismic applications needs to store the forward-propagated wavefield (or source wavefield) on disk. Aiming to mitigate the storage demand, we develop an RTM that implements the source wavefield reconstruction by introducing a new wave equation to the problem. We adjust the initial and boundary conditions to take advantage of the properties of random boundary conditions (RBC). The RBC does not suppress unwanted waves coming from the artificial boundary enabling the full wavefield recovery. Besides, it explores low correlations with non-coherent signals due to the random velocities in the boundary. We also develop compiler-guided implementations on a vector processor for seismic modeling and RTM, essential for Least-square Migration, Full Waveform Inversion, and Uncertainty Quantification applications. We test the seismic modeling and RTM on the 2-D Marmousi benchmark and 3-D HPC4E Seismic Test Suite. The numerical experiments show that the RTM which implements the wavefield reconstruction presents the best results in terms of execution time and hard disk demand. Lastly, the vector processor implementation is the one that requires fewer code modifications compared to the optimized baseline versions of the seismic modeling and RTM and GPU implementations, particularly for large 3D grids.