Lithologic Reservoirs ›› 2011, Vol. 23 ›› Issue (1): 98-102.doi: 10.3969/j.issn.1673-8926.2011.01.017

Previous Articles     Next Articles

Permeability prediction method based on improved BP neural network

YANG Jian1， YANG Chengbo2， ZHANG Yan1， CUI Ligong3， WANG Longfei4   

  1. （1. Research Institute of Exploration and Development， Southwest Oil-Gas Field Company， Sinopec， Chengdu 610081， China； 2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation， Southwest Petroleum University， Chengdu 610500， China； 3. Research Institute of Geologic Exploration and Development， Chuanqing Drilling & Exploration Corporation， CNPC， Chengdu 610051， China； 4. Research Institute of Petroleum Engineering Technology， Zhongyuan Oilfield，
    Sinopec， Puyang 457001， China
  • Online:2011-02-20 Published:2011-02-20

PDF (PC)

775

Abstract:

The traditional BP algorithmhas slowconvergence rate, and is easy to fall into local minimum. It is improved based on Kozeny-Carman equation and the study of Yang Zhengming, and a three-layer feedforward BP neural network model for permeability prediction is established bymeans ofMATLAB neural network toolbox. The simulation training of the improved neural network model is carried out. The result shows that the improved model has faster convergence rate and higher accuracy. The values predicted by the model are consistent with the laboratory test values, and the relative error is less than 10%, so it can completelymeet the accuracy demand ofwell site.

Key words: plateau composite basin, multi-source hydrocarbon generation, compound accumulation, exploration theory

［1］ 吴新根，葛家理.应用人工神经网络预测油田产量［J］.石油勘探与开发，1994，21（3）：75-78.
［2］ 刘全新，方光建.利用模拟退火算法实现地震叠前反演［J］.岩性油气藏，2010，22（1）：87-92.
［3］ 周彩兰，刘敏.BP 神经网络在石油产量预测中的应用［J］.武汉理工大学学报，2009，31（3）：125-129.
［4］ 邓勇，杜志敏，陆燕妮.遗传算法结合神经网络在油气产量预测中的应用［J］.数学的认识与实践，2008，38（15）：118-123.
［5］ 飞思科技产品研发中心.MATLAB 6.5 辅助神经网络分析与设计［M］.北京：电子工业出版社，2003：65-72.
［6］ 党建武.神经网络技术及应用［M］.北京：北京铁道出版社，2000：103-112.
［7］ 刘全新，高建虎，董雪华.储层预测中的非线性反演方法［J］.岩性油气藏，2007，19（1）：81-85.
［8］ 张立明.人工神经网络的模型及其应用［M］.上海：复旦大学出版社，1993：32-36.
［9］ 杨华民，王文成.一种BP 改进算法［J］.微型计算机，1997，17（2）：53-54.
［10］ 王静伟.BP 神经网络改进算法研究［J］.中国水运，2008，18（1）：157-158.
［11］ 何更生.油层物理［M］.北京：石油工业出版社，1994：5-8.
［12］ 杨正明，姜汉桥，周荣学.用核磁共振技术测量低渗含水气藏中的束缚水饱和度［J］.石油钻采工艺，2008，30（3）：59-60.
［13］ 孙勤华，刘晓梅，刘建新，等.利用波形分析技术半定量预测塔中碳酸盐岩储层［J］.岩性油气藏，2010，22（1）：101-103.
［14］ 杨理践，刘金凤，高松巍.BP 神经网络在原油三相计量中的应用［J］.油气田地面工程，2008，27（12）：18-19.
［15］ 汤文生，合烨，陈小安.基于BP 神经网络和遗传算法的硫化工艺参数优化［J］.橡胶工业，2008，55（2）：105-106.
［16］ 陈永波，雍学善，刘化清.沉积体系域控制下的岩性油气藏预测方法研究及应用———以鄂尔多斯盆地北部中生界延长组岩性油气藏为例［J］.岩性油气藏，2007，19（2）：62-66.
［17］ Goda H M，Maier H R，Behrenbruch P. The development of an optimal artificial neural network model for estimating initial water saturation-Australian reservoir［R］. SPE 93307，2005：312-314.
［18］ 楼顺天，施阳.基于 MATLAB 的系统分析与设计———神经网络［M］.西安：西安电子科技大学出版社，1999：10-14.
[1] YUAN Jianying， FU Suotang， CAO Zhenglin， YAN Cunfeng，ZHANG Shuichang， MA Dade. Multi-source hydrocarbon generation and accumulation of plateau multiple petroleum system in Qaidam Basin [J]. Lithologic Reservoirs, 2011, 23(3): 7-14.
[2] YANG Guochen，YU Bingsong. Development status of exploration of subtle hydrocarbon traps [J]. Lithologic Reservoirs, 2008, 20(3): 6-11.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] WEI Qinlian, ZHENG Rongcai, XIAO Ling,WANG Chengyu, NIU Xiaobing. Influencing factors and characteristics of Chang 6 reservoir in Wuqi area, Ordos Basin[J]. Lithologic Reservoirs, 2007, 19(4): 45 -50 .
[2] WANG Dongqi, YIN Daiyin. Empirical formulas of relative permeability curve of water drive reservoirs[J]. Lithologic Reservoirs, 2017, 29(3): 159 -164 .
[3] LI Yun, SHI Zhiqiang. Study on fluid inclusion of tight sandstone reservoir of Upper Triassic Xujiahe Formation in central Sichuan Basin[J]. Lithologic Reservoirs, 2008, 20(1): 27 -32 .
[4] JIANG Ren, FAN Tailiang, XU Shouli. Concept and techniques of seismic geomorphology[J]. Lithologic Reservoirs, 2008, 20(1): 33 -38 .
[5] ZOU Mingliang, HUANG Sijing, HU Zuowei, FENG Wenli, LIU Haoniannian. The origin of carbonate cements and the influence on reservoir quality of Pinghu Formation in Xihu Sag, East China Sea[J]. Lithologic Reservoirs, 2008, 20(1): 47 -52 .
[6] WANG Bingjie, HE Sheng, NI June, FANG Du. Activity analysis of main faults in Qianquan area, Banqiao Sag[J]. Lithologic Reservoirs, 2008, 20(1): 75 -82 .
[7] CHEN Zhenbiao, ZHANG Chaomo, ZHANG Zhansong, LING Husong, SUN Baodian. Using NMR T2 spectrum distribution to study fractal nature of pore structure[J]. Lithologic Reservoirs, 2008, 20(1): 105 -110 .
[8] ZHANG Houfu, XU Zhaohui. Discussion on stratigraphic-lithologic reservoirs exploration in the aspect of the research history of reservoirs[J]. Lithologic Reservoirs, 2008, 20(1): 114 -123 .
[9] ZHANG Xia. Cultivation of exploration creativity[J]. Lithologic Reservoirs, 2007, 19(1): 16 -20 .
[10] YANG Wuyang, YANG Wencai, LIU Quanxin, WANG Xiwen. 3D frequency and space domain amplitude-preserved migration with viscoelastic wave equations[J]. Lithologic Reservoirs, 2007, 19(1): 86 -91 .
TRENDMD:

Copyright © 2018 Lithologic Reservoirs

Support by Beijing Magtech support@magtech.com.cn