QUANTIFICATION AND PREDICTION OF CARBONATE ROCKS DIAGENESIS FROM WELL LOGS AND CORE DATA BY ARTIFICIAL NEURAL NETWORK
Samar Saied Abdelrady Shahat Hawary;
Abstract
The application of artificial neural networks (ANNs) is used successfully to generate a numerical scale for diagenesis quantification from 0 to 10 with specified particular range for each type of diagenesis. It enhances identifying the rock typing and generated a link between geological and reservoir modeling. Also, a mathematical correlation is generated to directly predict the quantification of diagenesis in carbonate rocks in the study area.
Other data
| Title | QUANTIFICATION AND PREDICTION OF CARBONATE ROCKS DIAGENESIS FROM WELL LOGS AND CORE DATA BY ARTIFICIAL NEURAL NETWORK | Other Titles | التقييم الكمى لتحورات الصخور الجيرية والتنبؤ بها من معلومات تسجيلات الآبار واللباب الصخرى عن طريق الشبكات الاصطناعية العصبية | Authors | Samar Saied Abdelrady Shahat Hawary | Issue Date | 2019 |
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