The large and demanding oil and gas field requires massive, computationally-intensive simulations for everything from reservoir modeling to drilling application to natural gas extraction. Additional factors including seismic stability, weather patterns, and acoustic emissions also contribute to the complexity of oil and gas analyses.
Running complex simulations are essential to production, however, these analyses are often difficult to execute. For example, a single drilling application model can contain millions of elements for a finite element analysis (FEA). Since many of these analyses are so compute intensive, high-performance computing (HPC) plays a large role in executing simulations that can run for days or weeks. However, due to constrained on-site HPC resources, simulations are often left in long queues and engineers left without the necessary tools to reach optimal designs.
To address these concerns, a leading oilfield service company turned to Rescale. With access to a comprehensive suite of simulation tools and scalable HPC configurations, our customer utilized Rescale’s secure, web-based platform to evaluate acoustic emission properties among different drill bits and drilling scenarios.
All simulations were executed on Rescale using the commercially available software, LS-DYNA. Provided by the Livermore Software Technology Corporation, LS-DYNA is used for computationally complex FEA analyses. Our customer conducted these analyses for the purpose of R&D drilling applications.
The user ran the simulation on three separate configurations, simultaneously, to compare Rescale’s platform performance across several different compute configurations. Identical simulations were executed on 16, 32, and 64 cores, respectively. Upon job submission by the user, the Rescale-powered solver performed as follow:
- All processors were dynamically provisioned within five minutes of job submission
- Results were gathered and delivered for post-processing and analysis
- All computing instances across the cluster were deleted upon completion
When executed on the customer’s 16 core, in-house cluster, the simulation converged in 77 hours. However, Rescale’s platform achieved convergence for the different configurations as follows:
- 16 cores: 67 hours
- 32 cores: 32 hours
- 64 cores: 17 hours
When Rescale ran the simulation on the same number of cores as the customer, it achieved a 13% reduction in compute time, saving roughly an entire workday.
When the customer ran the simulation using 64 cores on the Rescale platform it modeled 180 microseconds of acoustics per case and finished >75% faster than their in-house cluster. The total cost of running the job on Rescale with 64 cores cost the customer only $864, resulting in a total savings of >$6,000 while still reducing convergence time by 60 hours. Additionally, executing the simulation on Rescale revealed previously undiscovered observations about drilling scenarios and enabled our customer to determine an optimal acoustic emissions environment.
This article was written by Ilea Graedel.