Prediction of reservoir parameters in gas hydrate sediments using artificial intelligence (AI): A ca...
Prediction of reservoir parameters in gas hydrate sediments using artificial intelligence (AI): A case study in Krishna–Godavari basin (NGHP Exp-02)
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New Delhi: Springer India
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English
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New Delhi: Springer India
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The estimation of accurate reservoir parameters is essential for conventional and non-conventional hydrocarbon prospects. An artificial neural network has been developed to predict the reservoir parameters (porosity and saturation of gas hydrates) in a silty-sand, sandy-silt and pelagic-poor clay reservoir at two neighbour wells using the petrophys...
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Prediction of reservoir parameters in gas hydrate sediments using artificial intelligence (AI): A case study in Krishna–Godavari basin (NGHP Exp-02)
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TN_cdi_proquest_journals_2919731020
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2919731020
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ISSN
2347-4327,0253-4126
E-ISSN
0973-774X
DOI
10.1007/s12040-019-1210-x
