title: Neural networks in petroleum engineering: a case study.
abstract: A multilayer neural network has been used for deciding which oil reservoir layer has to be perforated. Many network architectures were tested until we found those with the best generalization capability. The network performs better than human experts and its achievements are higher than the historical average in the test area. As in other applications of neural networks, the learning capability improves with more hidden neurons but the generalization does not.
authors.forename: M A
authors.initials: MA
authors.lastname: Vukelic
authors.forename: E N
authors.initials: EN
authors.lastname: Miranda
mesh_terms: D000465:Algorithms; D002616:Chemical Engineering; D055593:Geological Phenomena; D005844:Geology; D006801:Humans; D016571:Neural Networks, Computer; D010578:Petroleum; D011337:Probability Learning
chemical_list: D010578:Petroleum