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IJSTR >> Volume 9 - Issue 12, December 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Novel Applications Of Artificial Intelligence Neural Network In Hydraulic Fracturing

[Full Text]



Karim M. Magdy, Ahmed A. Gawish, Adel M. Salem



Hydraulic Fracturing, Machine Learning, Neural Networks, Productivity Index, Design Optimization



Increasing productivity is a critical target for petroleum industry especially upon increased demand on petroleum products. The primary goal of a hydraulic fracturing treatment is to create a highly conductive flow path to the wellbore that economically increases well production, so Hydraulic frac is one of the major methods used to increase productivity if not the most efficient one. Field containing many wells makes it difficult to choose the most efficient one suitable for high productive frac .There are different screening criteria used, but still there are not sharp efficient, so I try in this research using artificial intelligence neutral networks to create a platform model for selecting the best well candidate for maximum overall productivity of an oil field, study the different affecting parameters on reservoir stimulation and predict the performance and future optimum designs . Artificial intelligence neural network is an information processing system simulating the natural neural system in the human brain. Using it, you can solve many complex petroleum problems that are difficult for traditional models and computing systems. It has shown great potential for generating accurate analysis and results from large amount of historical data that otherwise would seem not to be useful in the analysis. It also can make the best selection for any output relevant to several inputs and calculate the optimum value of it for different cases.



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[2] Shell Stimulation guidelines.
[3] BP Stimulation Study,2000.
[4] Data mining application in the petroleum industry,Round Oak 2003.
[5] Mohaghegh, Shehab “ virtual intelligence application in petroleum engineering “
[6] Neuro Approach to Hydraulic Fracture Treatment design optimization .