| A methodology to generate synthetic wireline logs is presented. Synthetic logs can help to analyze the reservoir properties in areas where the set of logs that are necessary, are absent or incomplete. The approach presented involves the use of Artificial Neural Networks, as the main tool, in conjunction with data obtained from conventional wireline logs. Implementation of this approach aims to reduce operation costs to companies.;Development of the neural network model was completed using a General Regression Neural Network, and four wells that included gamma ray, density, neutron, and resistivity logs. Synthetic logs were generated through two different exercises. Exercise one involved four wells for development and training of the network.;After development of the neural network model, synthetic logs with a reasonable degree of accuracy were generated. (Abstract shortened by UMI.)... |
