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Case Study: GigaViz Cluster-based Attribute Computation Promotes Shell's Workflows on Large 3D Seismic Data Volumes
"GigaViz, through its application protocol interface API, allowed us to run our proprietary attributes in parallel, improving the interpretation process for large datasets."
Ru Smith
Project Manager
Seismic Interpretation R&D
Shell International E&P
Rijswijk, Netherlands
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Challenge
Enable proprietary attributes for large seismic data volumes to be run in parallel on the desktop.
Solution
Used the GigaViz system—a scaleable, cluster-based visualization, interpretation, and attribute analysis software—to improve interpretation performance.
Results
Enhanced in-house semiautomated workflows critical to rapid understanding of huge data volumes.
Improve interpretation performance
The key challenge in seismic interpretation is to extract as much information as possible from 3D seismic volumes in a time-efficient manner. Seismic attributes play a key role in unlocking hidden information from seismic data. Shell's internally developed seismic attributes, the VOICE filters, create a differentiating proprietary tool in Shell's seismic interpretation workflow.
But as seismic volumes grow larger, the time used to calculate these attributes becomes a limiting factor in the widespread use and deployment of critical attribute-enabled workflows. In addition, 3D visualization of large seismic volumes is important in parameter selection and quality control during the attribute generation process. Until now, visualization of large volumes has been restricted to specialized visualization workrooms.
To improve performance, Shell investigated attribute generation using innovative parallel processing computational techniques. This new solution would enable large volumes to be seen on the desktop, eliminating the need for the interpreter to relocate from the conventional workroom or hardware. Also, this solution would offer the required scalability, due to the ability to expand cluster-based systems as volumes grew and multiplied during the seismic interpretation cycle.
Enable optimal use of hardware and remote collaboration
Shell chose the GigaViz system—a scalable, cluster-based visualization, interpretation, and attribute analysis software—to investigate new ways of improving interpretation performance on large 3D seismic surveys. The GigaViz system is a client server-based application that can run on a conventional personal computer, receiving displays from a Linux-based cluster server. The server stores the data and computes all tasks.
As datasets get larger, the cluster size or number of nodes can be increased to accommodate the data, without forfeiting performance. Using the GigaViz application program interface (API), Shell programmers included the proprietary seismic VOICE attributes to be launched from within the system. This launch enabled VOICE attribute computations to use all available CPUs on the Linux cluster, easily outperforming the traditional single CPU approach.
Shell tested the flexible client-server architecture of the system on a multiregional collaboration project. Geoscientists in Aberdeen and Houston accessed the server on a cluster located in the Netherlands to display, process, and interpret a large dataset. The approach allowed optimal use of available hardware, ensuring that processing power was available for fast computation of attributes, visualization, and horizon interpretation, while enabling remote collaboration.
Gain new insight into large datasets
By using the GigaViz system and Linux clusters, Shell researchers were able to display parallel proprietary attributes, enhancing in-house semiautomated workflows critical to rapid understanding of huge data volumes. Previously, the 3D visualization of such large data volumes had been possible only in dedicated facilities. The GigaViz system, together with the Shell plug-ins, provided new insight into large complex dataset analysis.
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