Modified GMDH networks for oilfield production prediction

Jia Guo; Wei Huang; Qiong Mao; Xudong Wang; Xinying Wang; Tao Song

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자료유형: 학술저널

저자정보: Jia Guo (PetroChina Huabei Oilfield Company) Wei Huang (PetroChina Huabei Oilfield Company) Qiong Mao (PetroChina Huabei Oilfield Company) Xudong Wang (PetroChina Huabei Oilfield Company) Xinying Wang (PetroChina Huabei Oilfield Company) Tao Song (PetroChina Huabei Oilfield Company)

저널정보: 한국자원공학회 Geosystem Engineering Geosystem Engineering Vol.21 No.4

발행연도: 2018.1

수록면: 217 - 225 (9page)

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The self-organizing Group Method of Data Handling (GMDH) functional network is effective in predicting oilfield production. During operation the division of data sample depending on artificial classification cannot lead to global optimum in great probability and the variables are probably eliminated early in the iterative process in traditional GMDH algorithm. Recent years, GMDH model has been improved through many artificial intelligent models, but few people take the optimization of the model structure into account. In this paper, different training and testing set grouping and the effects of variables transmission were studied. The modified GMDH algorithm was optimized using the original variables preservation method and the random sample method, which was applied to the oilfield production forecasting simulation. The results of the modified GMDH algorithm, the traditional GMDH algorithm, ANNs and the empirical equations for predicting annual oil production were compared. The simulative results indicated that the modified GMDH model was the best tool for data-fitting with lowest error (RMSE = 13.9440, MAPE = 0.1121 and SI = 0.0378) and highest accuracy (R = 0.9984).

참고문헌 (33)

참고문헌 신청

Abdel-Aal, R. E. / 2009 / Constructing optimal educational tests using GMDH-based item ranking and selection / Neurocomputing 72(4-6):1184~1197

Abdolrahimi, S. / 2014 / Prediction of partition coefficients of alkaloids in ionic liquids based aqueous biphasic systems using hybrid group method of data handling (GMDH) neural network / Journal of Molecular Liquids 191(2):79~84

Ahmadi, M. A. / 2013 / Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir / Applied Soft Computing 13(2):1085~1098

Ahmadi, M. A. / 2013 / Combing artificial neural network and unified particle swarm optimization for oil flow rate prediction: Case study / Neural Computing and Applications 23(2):565~565

Amanifard, N. / 2008 / Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks / Energy Conversion & Management 49(10):2588~2594

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