Event-driven workflows for large-scale seismic imaging in the cloud

Abstract

Cloud computing has seen a large rise in popularity in recent years and is becoming a cost effective alternative to on-premise computing, with theoretically unlimited scalability. However, so far little progress has been made in adapting the cloud for high performance computing (HPC) tasks, such as seismic imaging and inversion. As the cloud does not provide the same type of fast and reliable connections as conventional HPC clusters, porting legacy codes developed for HPC environments to the cloud is ineffective and misses out on an opportunity to take advantage of new technologies presented by it. We present a novel approach of bringing seismic imaging and inversion workflows to the cloud, which does not rely on a traditional HPC environment, but is based on serverless and event-driven computations. Computational resources are assigned dynamically in response to events, thus minimizing idle time and providing resilience to hardware failures. We test our workflow on two large-scale imaging examples and demonstrate that cost-effective HPC in the cloud is possible, but requires careful reconsiderations of how to bring software to the cloud.

An Event-Driven Approach to Serverless Seismic Imaging in the Cloud

“…Another example is Osokey [12], a company offering fully cloud-native and serverless software for seismic data visualization and interpretation. In a previous publication, we have adapted these concepts for seismic imaging and introduced a fully cloud-native workflow for serverless imaging on AWS [13]. Here, we describe the implementation of this approach on Azure and present a 3D imaging case study.…”