Lightning Talk : Acceleration of Reservoir Navigation With Edge Parallel Computing

Summary Real-time mapping of formations, detection of structural anomalies and evaluation of near-well reservoir properties can be achieved through logging while drilling (LWD). Hydrocarbon deposits have typically a quasilayered structure, however, complex situations with strong 3-D features like faults or salt domes are becoming increasingly common. Here, we extend the Green's function methodology to compute fully 2–3D scalar wave fields. This finds application in elastodynamic forward and inverse scattering, where often times, as a first approximation, elastic coupling between P- and S-waves is ignored. However, we anticipate that our computational approach will equally benefit borehole acoustics (e.g., LWD borehole acousto-elastodynamic scattering), reservoir acoustics (e.g., distributed acoustic sensing) and reservoir seismics (e.g., surface seismic survey and vertical seismic profiling) applications. In this paper, we explore fully multi-dimensional geological models and accelerate the physics simulations with edge parallel computing. Along the road, high-performance LWD navigation can achieve safe, fast and confident well placement. We developed highly efficient and scalable computational means for modeling acoustic responses in multi-dimensional reservoir. The results demonstrate nearly 2 orders of magnitude acceleration for small-to-medium problems through edge computing. Multi-physics LWD, inverse reservoir mapping and monitoring as well as variety of AI/ML tasks can benefit from our platform-agnostic approach.