Abstract
About 10% of all ‘supercomputers’ have been delivered to the oil industry. Its two big computational tasks are seismic data processing (to deduce underground geological structures from surface-based probing with elastic waves), and reservoir modeling (to simulate the flows within a producing field, in order to optimize the amount of hydrocarbons that can be recovered). Both tasks are extremely CPU- and, for seismic modeling, also I/O intensive. Trying to forecast the future is always chancy, and especially so for parallel computing. To stay on a somewhat safe ground, we will focus on the two main tasks just mentioned, and on the computational demands they entail. A change of direction towards large-scale parallelism is well on the way in the former area, but held back a few years in the latter (mainly by coding complexities).
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© 1996 Springer-Verlag Berlin Heidelberg
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Fornberg, B. (1996). The prospect for parallel computing in the oil industry. In: Waśniewski, J., Dongarra, J., Madsen, K., Olesen, D. (eds) Applied Parallel Computing Industrial Computation and Optimization. PARA 1996. Lecture Notes in Computer Science, vol 1184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62095-8_28
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DOI: https://doi.org/10.1007/3-540-62095-8_28
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Online ISBN: 978-3-540-49643-4
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