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Predicting well-stimulation results in a gas-storage field in the absence of reservoir data with neural networks. S. Mohaghegh et al. SPE Reservoir Engng., November 1996, 11(4), 268--272.

Methodology is presented that is capable of forecasting the post fracture deliverability on the basis of historical data in Clinton sandstone gas-storage field without detailed reservoir data. Post fracture well deliverability was predicted with approximately 95% accuracy. The neural network developed in this study is in current usage for selection of candidate wells for the hydraulic fracturing in the Clinton sandstone. 9 refs.

Abstract details

Journal title: SPE Reservoir Engineering

Keywords: Computer applications

Subjects: Geophysics, Information technology, Reservoir Engineering, Mechanical Engineering, Energy consumption, Storage, Oil and gas extraction, Oil and gas, Oil, Primary energy production, Hydraulic fracturing, Reservoir engineering