Kristoffer Walker, Chevron
Borehole acoustic logging involves measuring the elastic properties of the Earth with tools that move through the borehole as part of a drilling pipe or via a wire. A source transmits an acoustic wave into the borehole fluid and excites wave modes that are recorded by a receiver array on the same tool. Computational modeling of borehole acoustic wavefield propagation has greatly improved our understanding of this physics, which has resulted in fit-for-purpose algorithms to measure properties of the Earth.
Traditionally borehole acoustic wavefield modeling is carried out on HPC clusters. That protocol of parallelizing computations works well for many problems. However, it comes at the cost of: developing and maintaining codes that are harder to debug; having performance limited by network communication speeds; sharing cluster resources with others; needing a queue system that is separate from your modeling software to manage jobs; and most importantly, using an HPC cluster.
Chevron has addressed this problem by using MATLAB’s rich and user-friendly GUI development features, embracing cloud-based distributed computing technologies, and utilizing advances in computational hardware and compilers. Specifically, we developed a shared memory wavefield simulation code that capitalizes on cache blocking, enabling us to achieve cluster speeds on a single multi-processor virtual machine. We created a MATLAB GUI infrastructure for the entire system spanning model creation, job management, data analysis, and results archiving. Our program represents a “cluster in a box”, and generates results by spinning up only the computational resources it needs for the job, greatly reducing the total cost relative to using a physical cluster due to the pay-as-you-go cloud-based cost structure. For us the value proposition of using MATLAB is simply that is makes us agile, allowing us to accelerate our growing of capabilities and delivery of results faster than any of the other alternatives.
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