Estimating the initial pressure, permeability and skin factor of oil reservoirs using artificial neural networks

被引:48
作者
Jeirani, Z [1 ]
Mohebbi, A [1 ]
机构
[1] Shahid Bahonar Univ Kerman, Dept Chem Engn, Kerman, Iran
关键词
artificial neural networks; initial pressure; permeability; skin factor; pressure build up test; well test;
D O I
10.1016/j.petrol.2005.09.002
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Artificial neural network, a biologically inspired computing method which has an ability to learn, self-adjust, and be trained, provides a powerful tool in solving pattern recognition problems. In this study, a new approach based on artificial neural networks (ANNs) has been designed to estimate the initial pressure, permeability and skin factor of oil reservoir using the pressure build up test data. Five sets of actual field data in conventional and dual porosity reservoirs have been used to test the results of the neural network. The results from the network are in good agreement with the results from Homer plot. Finally, it is shown that the application of artificial neural networks in a pressure build up test reduces the cost of the test and it is also a valuable tool for well testing. (c) 2005 Elsevier B.V. All rights reserved,
引用
收藏
页码:11 / 20
页数:10
相关论文
共 22 条
[1]  
ALKAABI AU, 1990, JPT MAY, P654
[2]  
ALKNABI AU, 1993, SPE FORMATION EVAL, V8, P233
[3]  
ALLAIN OF, 1990, JPT MAR, P342
[4]  
[Anonymous], P SPE ANN TECHN C EX
[5]  
[Anonymous], 28237 SPE
[6]  
ANRAKU T, 1993, 1993 SPE ANN TECHN C
[7]   Committee neural networks for porosity and permeability prediction from well logs [J].
Bhatt, A ;
Helle, HB .
GEOPHYSICAL PROSPECTING, 2002, 50 (06) :645-660
[8]  
COATS KH, 1967, PRESSURE ANAL METHOD
[9]  
Earlougher R.C.Jr, 1977, Advances in Well Test Analysis
[10]   Porosity and permeability prediction from wireline logs using artificial neural networks: a North Sea case study [J].
Helle, HB ;
Bhatt, A ;
Ursin, B .
GEOPHYSICAL PROSPECTING, 2001, 49 (04) :431-444