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Proceedings Paper

Multiple oil and gas volumetric data visualization with GPU programming
Author(s): Jim Ching-Rong Lin; Cass Hall
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Paper Abstract

In recent years, multi-volume visualization has become an industry standard for analyzing and interpreting large surveys of seismic data. Advances made in computer hardware and software have moved visualization from large, expensive visualization centers to the desktop. Two of the greatest factors in achieving this have been the rapid performance enhancements to computer processing power and increasing memory capacities. In fact, computer and graphics capabilities have tended to more than double each year. At the same time, the sizes of seismic datasets have grown dramatically. Geoscientists regularly interpret projects that exceed several gigabytes. They need to interpret prospects quickly and efficiently and expect their desktop workstations and software applications to be as performant as possible. Interactive, multi-volume visualization is important to rapid prospect generation. Consequently, the ability to visualize and interpret multiple seismic and attribute volumes enhances and accelerates the interpretation process by allowing geoscientists to gain a better understanding of the structural framework, reservoir characteristics, and subtle details of their data. Therefore, we analyzed seismic volume visualization and defined four levels of intermixing: data, voxel, pixel, and image intermixing. Then, we designed and implemented a framework to accomplish these four levels of intermixing. To take advantage of recent advancements in programmable graphics processing units (GPUs), all levels of intermixing have been moved from the CPU into the GPU, with the exception of data intermixing. We developed a prototype of this framework to prove our concept. This paper describes the four levels intermixing, framework, and prototype; it also presents a summary of our results and comments made by geoscientists and developers who evaluated our endeavor.

Paper Details

Date Published: 29 January 2007
PDF: 8 pages
Proc. SPIE 6495, Visualization and Data Analysis 2007, 64950U (29 January 2007); doi: 10.1117/12.698706
Show Author Affiliations
Jim Ching-Rong Lin, Landmark Graphics Corp. (United States)
Cass Hall, Landmark Graphics Corp. (United States)


Published in SPIE Proceedings Vol. 6495:
Visualization and Data Analysis 2007
Robert F. Erbacher; Jonathan C. Roberts; Matti T. Gröhn; Katy Börner, Editor(s)

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