Albumin
发表于 2025-3-23 10:43:08
An Information Integrated Approach for Reservoir Characterization deterministic mechanism and statistical behavior. The Caianiello neural network method is presented in this paper, including neural wavelet estimation, input signal reconstruction, and nonlinear factor optimization. A joint inversion scheme for porosity and clay-content estimations is established b
reject
发表于 2025-3-23 16:42:36
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难解
发表于 2025-3-23 21:49:26
Oil Reservoir Porosity Prediction Using a Neural Network Ensemble Approachata. The resulting maps may contain varying levels of uncertainty depending on the experience of the interpreter and the availability and quality of seismic and well data..This chapter describes a neural network ensemble approach to the interpolation problem. An interval of seismic data representing
Critical
发表于 2025-3-23 22:56:26
Interpretation of Shallow Stratigraphic Facies Using a Self-Organizing Neural Networkmplish the study, 46 groundwater-monitoring wells were installed at the site. Data collected from the wells included detailed lithologic descriptions from samples and cuttings, and suites of geophysical well logs. Because the quality of the lithologic descriptions was erratic, our approach was to pr
cyanosis
发表于 2025-3-24 06:15:37
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dapper
发表于 2025-3-24 09:56:26
Interpretation of Airborne Electromagnetic Data with Neural Networkseight, with one-dimensional (1-D) horizontally layered homogeneous earth structures. A divide-and-conquer strategy is applied. One ANN is trained to interpret data, which are best described by homogeneous half-space (HHS) models. A second ANN inverts data from horizontally layered half-space models
Obituary
发表于 2025-3-24 12:49:06
978-90-481-6476-9Springer Science+Business Media Dordrecht 2003
纪念
发表于 2025-3-24 15:16:46
Geophysical Applications of Artificial Neural Networks and Fuzzy Logic978-94-017-0271-3Series ISSN 0924-6096
Mercurial
发表于 2025-3-24 21:17:47
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拱形面包
发表于 2025-3-25 01:00:11
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