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Erschienen in:
Intelligent Data Analysis Techniques—Machine Learning and Data Mining Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Application of Artificial Neural Networks in Geoscience and Petroleum Industry

verfasst von : Rahman Ashena, Gerhard Thonhauser

Erschienen in: Artificial Intelligent Approaches in Petroleum Geosciences

Verlag: Springer International Publishing

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Abstract

It has been shown that artificial neural networks (ANNs), as a method of artificial intelligence, have the potential to increase the ability of problem solving to geoscience and petroleum industry problems particularly in case of limited availability or lack of input data. ANN application has become widespread in engineering including geoscience and petroleum engineering because it has shown to be able to produce reasonable outputs for inputs it has not learned how to deal with. In this chapter, the following subjects are covered: artificial neural networks basics (neurons, activation function, ANN structure), feed-forward ANN, backpropagation and learning (perceptrons and backpropagation, multilayer ANNs and backpropagation algorithm), data processing by ANN (training, over-fitting, testing, validation), ANN and statistical parameters, an applied example of ANN, and applications of ANN in geoscience and petroleum Engineering.

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Vorheriges Kapitel Genetic Programming Techniques with Applications in the Oil and Gas Industry
Nächstes Kapitel On Support Vector Regression to Predict Poisson’s Ratio and Young’s Modulus of Reservoir Rock
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Fußnoten
1
A neural network without hidden layer(s).
 
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Metadaten
Titel
Application of Artificial Neural Networks in Geoscience and Petroleum Industry
verfasst von
Rahman Ashena
Gerhard Thonhauser
Copyright-Jahr
2015
Buch
Artificial Intelligent Approaches in Petroleum Geosciences

Print ISBN: 978-3-319-16530-1

Electronic ISBN: 978-3-319-16531-8

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-16531-8_4