Below we outline the typical infrastructure options that are used in the Oil & Gas workload deployments shown above for each of the key components.
While it is less complex to have all your resources in the cloud (compute, storage, and visualization), it is not uncommon for our customers to have a hybrid model due to multiple business constraints.Ī typical HPC setup includes a front-end for submitting jobs, a job scheduler or orchestrator, a compute cluster, and a shared storage. Typical Reference Deployments and Infrastructure Optionsīelow we are demonstrating two of the common deployment architectures we see for the O&G workloads. We will share below a few options we have today so you can successfully meet the goals for running your application in Azure. However, we are laying out the Azure service architectures and offerings that we have commonly used in our projects when working with some key O&G customers.įrom our experience, both Reservoir and Seismic workflows typically have similar requirements for compute and job scheduling. However, Seismic workloads challenge the infrastructure on storage with its multi-PB storage requirements (a single seismic processing project may start with 500 TB of raw data, which requires a total of several PBs of long-term storage) and throughput requirements (measured in 100's of GB/s). Azure offers many choices for you, because each business and workload have their unique needs. Just like you would do for planning your on-premises infrastructure, you need to make some key infrastructure choices in the cloud that are based on your workload’s requirements. Now you have decided to run your workload in Azure. The IEEE article here (Section 1.2) presents these benefits in some more detail. The key advantage that the cloud brings is elasticity of resources and low infrastructure management overhead thus allowing our customers to focus on their primary business.
Running Your Oil and Gas Workload in Azure See the figure below for more information about them: We will refer back to these three workflows throughout this article.
The workflows that we will be focusing on in this blog are Seismic Processing and Interpretation, Reservoir Simulation and Modeling, and Computational Chemistry. There are multiple user scenarios and workflows in Oil and Gas that use high-performance computing (HPC) to solve problems and create simulations that require massive amounts of data. We now have a great potential for using the cloud in the Oil and Gas industry, to optimize the business workflows that were previously limited by capacity and older hardware. We have worked with multiple customers running these workloads successfully in Azure. The goal of this blog is to share our experiences running key Oil and Gas workloads in Azure. Credits: Ed Price, Azure CAT HPC Team Goal of this Blog
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