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Keywords: neural network
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Proceedings Papers

Paper presented at the SPE Permian Basin Oil and Gas Recovery Conference, May 15–17, 2001
Paper Number: SPE-70041-MS
... lower brushy canyon interval porosity brushy canyon water saturation log analysis machine learning cercion truman correlation coefficient neural network weiss well logging architecture information brushy canyon interval stubb core information spe 70041 balch artificial...
Proceedings Papers

Paper presented at the SPE Permian Basin Oil and Gas Recovery Conference, May 15–17, 2001
Paper Number: SPE-70054-MS
... neural network exploration tool well log risk assessment presentation spe 70054 interface expert system risk reduction online database information prrc nm tech fuzzy logic fuzzy-expert exploration tool risk management artificial intelligence geophysical data risk and uncertainty...
Proceedings Papers

Paper presented at the SPE Permian Basin Oil and Gas Recovery Conference, March 21–23, 2000
Paper Number: SPE-59554-MS
... Abstract At Dagger Draw it is difficult to arrive at reliable estimates of total pore volume in the vuggy dolomitic reservoir. Correlating wire-line logs to core porosity using a multi-layer perceptron neural network (MLP) generated a "ground truth" porosity estimator for the reservoir. Well...
Proceedings Papers

Paper presented at the SPE Permian Basin Oil and Gas Recovery Conference, March 21–23, 2000
Paper Number: SPE-59555-MS
... a multilayer perceptron (MLP) neural network to regress for velocity at each seismic bin. At Nash Draw the wells are confined to the central region of the seismic survey, and conventional geostatistics reliably interpolated depths only in the region defined by well control. The MLP approach used the best three...
Proceedings Papers

Paper presented at the SPE Permian Basin Oil and Gas Recovery Conference, March 23–26, 1998
Paper Number: SPE-39814-MS
..., Roberts County, TX. The analysis uses an artificial neural network (ANN). Specific areas of interest include any controllable/quantifiable aspect of a well's completion and stimulation procedure-including fluid selection, treatment volume, proppant type and volume, pump rates, and perforation distribution...
Proceedings Papers

Paper presented at the SPE Permian Basin Oil and Gas Recovery Conference, March 23–26, 1998
Paper Number: SPE-39805-MS
..., the optimal transform method, and a neural network, best reproduce the input-output response. As expected, linear regression works best (in the sense that it reproduces the known function) when nonlinearity is small. Optimal transforms work best for moderate amounts of noise and for nonlinear functions...

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