APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR POROSITY PREDICTION OF S10 RESERVOIR IN SEME OIL FIELD
Publish place: Third International Conference on New Approaches in Science, Engineering and Technology
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
NSOECE03_079
تاریخ نمایه سازی: 28 اسفند 1394
Abstract:
Artificial intelligence techniques and neural networks in particular, have been increasingly applied in solving complex nonlinear problems from relatively few data. Burial depth, thickness, lithology and sandstone-to-reservoir ratio which are four fundamental factors determining porosity distribution of the reservoir system have been selected to build the neural network. This paper presents the findings of the application of Back propagation Artificial Neural Networks (ANN) for predicting porosity values of S10 reservoir in the Seme oil field of Benin Republic. Porosity values derived from core samples are used as target data in the ANN to train the network. Excellent matching of the core data and predicted values shows that the ANN approach is reliable and could be efficiently applied in reservoir modeling and characterization
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Authors
Iniko Bassey
Department of Petroleum Engineering, Kuban State University of Technology, Russia
Reza Masoomi
Department of Petroleum Engineering, Kuban State University of Technology, Russia
Innocent Ugbong
Department of Cadastre and Geo-Engineering, Kuban State University of Technology, Russia
Ehsan Shekoohizadeh
Department of Petroleum Engineering, Marvdasht Branch, Islamic Azad University, Marvdast, Iran
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