Titlebook: Geophysical Applications of Artificial Neural Networks and Fuzzy Logic; William A. Sandham,Miles Leggett Book 2003 Springer Science+Busine

Albumin

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

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難解

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

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

dapper

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

978-90-481-6476-9Springer Science+Business Media Dordrecht 2003

紀(jì)念

Geophysical Applications of Artificial Neural Networks and Fuzzy Logic978-94-017-0271-3Series ISSN 0924-6096

Mercurial

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