Soft Computing on Reservoir Characterization & Production Forecasting

Language: English

Published by LAP LAMBERT Academic Publishing Feb 2017, 2017

365991777X / 9783659917776

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This item is printed on demand - Print on Demand Titel. Neuware -Production forecasting and reservoir modeling play vital roles in optimal field development plan and management of petroleum reservoirs. This motivates engineers to develop computationally efficient and fast numerical methods capable of constructing history matched reservoir models producing reliable production forecasts. Relatively two new soft computing techniques successfully applied for automatic history matching and production forecasting. The first approach is artificial neural networks (ANN) based modeling, and the 2nd is genetic algorithm (GA) based optimization. A higher-order neural network (HONN) with higher-order synaptic operation (HOSO) architecture that embeds linear (conventional), quadratic (QSO) and cubic synaptic operations (CSO) used for forecasting real field oil production. For automatic history matching problem through reservoir characterization, a global optimization method called adaptive genetic algorithm (AGA) was employed. Adaptive genetic operators of AGA dynamically adjusts control parameters during evolution. The performance of both soft computing methods in achieving fast convergence rate and reduced computational efforts are presented in this book.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 256 pp. Englisch.…

Seller Inventory # 9783659917776

Title
Soft Computing on Reservoir Characterization & Production Forecasting
Author
Chithra Chakra N C
Publisher
LAP LAMBERT Academic Publishing Feb 2017
Publication year
2017
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
365991777X
ISBN 13
9783659917776
Item weight
399 grams
Dimensions
220x150x16 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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