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复杂岩性储层参数评价中神经网络技术的应用
引用本文:杨立强,王志章,熊琦华. 复杂岩性储层参数评价中神经网络技术的应用[J]. 地球物理学进展, 2003, 18(1): 44-48
作者姓名:杨立强  王志章  熊琦华
作者单位:1. 中国科学院地质与地球物理研究所,北京,100029
2. 石油大学,北京,北京,102249
基金项目:中国科学院知识创新重大项目 (KZCX1 SW 1 8)资助
摘    要:在复杂岩性储层中,储层四性关系比较复杂,表现为非线性,用传统的方法已经难以解决这类问题,为此引入了目前比较流行的人工神经网络技术、在前人基础上,以SN油田9井区为例进行储层研究工作,该区非均质性比较强,经对该区364口井常规到井资料进行储层参数重新解释,并做平面展布,与实际资料吻合较好。由此表明,神经网络技术在解决非线性问题上表现出了较大的优越性,值得我们做进一步的研究工作。

关 键 词:储层 神经网络 测井解释
文章编号:1004-2903(2003)01-0044-05
修稿时间:2002-07-15

Application of neural network in logging interpretation
YANG Li qiang ,WANG Zhi zhang ,XIONG Qi hua. Application of neural network in logging interpretation[J]. Progress in Geophysics, 2003, 18(1): 44-48
Authors:YANG Li qiang   WANG Zhi zhang   XIONG Qi hua
Affiliation:YANG Li qiang 1,WANG Zhi zhang 2,XIONG Qi hua 2
Abstract:The relation between parameters of reservoir and attributes of logging data is complex in reservoirs of complicated lithology. These non linear problems can't be solved by traditional methods, so popular manual neural network technique is adopted. The author started this study on the ninth area of SN oil field on the base of the others. The geological condition of this area is not homogeneous and complex. Data of 314 routine logging well is interpreted by this way, and the result accords with actual data well. We can see that neural network is in the ascendant in solving non-linear problems, which need us to do father work.
Keywords:reservoir   neural network   logging interpretation
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