Prediction of Formation Fracture Pressure Based on Grey Artificial Neural Network Logging

doi:10.3863/j.issn.1000-2634.1996.04.001

Abstract

Abstract: Of the mew information processing techniques, both grey mode and artificial neural network mode can be used to solve the problems of pattern- recognition and parameter calculation in fine log interpretation and reservoir description. On the basis of GM(U,N)mode and BPANN mode, this paper introduces an improved method (GMUNBPANN) to estimate parameter, and then analyzes the feasibibity of formation fracture pressure prediction by using well logging data. Taking the central gas field in H basin as an example, we have built a special grey BPANN mode to calculate the rock fracture pressure of Ahihezi andd Majiagou formation by making full use of test data and log information, and applied it successfully to 25 oil-gas wells. The result shows that this method is easy, practical and can make an accurate prediction, thus providing a new approach for the prediction of formation fracture pressure from well logging curves.

Key words: Mode, Logging neural network, Formation fracture pressure

CLC Number:

P631.81

Xia Hong-quan TAN De-hui et al. Prediction of Formation Fracture Pressure Based on Grey Artificial Neural Network Logging[J]. 西南石油大学学报(自然科学版), 1996, 18(4): 1-8.

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URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.3863/j.issn.1000-2634.1996.04.001

http://journal15.magtechjournal.com/Jwk_xnzk/EN/Y1996/V18/I4/1

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Prediction of Formation Fracture Pressure Based on Grey Artificial Neural Network Logging

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