TANG Ping. CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2003, 25(4): 413-416. doi: 10.11781/sysydz200304413
Citation: TANG Ping. CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2003, 25(4): 413-416. doi: 10.11781/sysydz200304413

CALCULATION OF RESERVOIR PARAMETERS BY THE NEURAL NETWORK MODEL WITH THE LOGGING DATA OF MULTIPLE WELLS

doi: 10.11781/sysydz200304413
  • Received Date: 2003-01-17
  • Rev Recd Date: 2003-06-20
  • Publish Date: 2003-07-25
  • The neural network has been widely used in reservoir parameter calculation with logging data and has got good effects. But under the control of logging data from multiple wells, it is crucial to construct a unified mathematical model, which helps to promote the contrast of calculating outputs among all the wells and in turn to promote the accuracy of interwell prediction. Based on the edition, standardization, normalization and depth correction of logging data, this research constructed a unified BP neural network model for each sand group. Compared with real samples, the predicting effect was good.

     

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  • [1]
    肖慈珣, 杨斌, 马维炎. 利用测井录井信息识别水淹层[J]. 测井技术, 1998, 22(4):267-272.
    [2]
    孙建孟, 谭未一, 李召成. 应用测井和BP神经网络算法预测储层敏感性[J]. 石油钻探技术, 2001, 29(2):37-40.
    [3]
    席道瑛, 张涛. BP人工神经网络模型在测井资料岩性自动识别中的应用[J]. 物探化探计算技术, 1995, 17(1):42-48.
    [4]
    阳文生, 赵力民, 侯守探, 等. 精细储层描述在荆丘油田调整挖潜中的初步实践[J]. 石油实验地质, 2000, 22(4):375-381.
    [5]
    刘争平, 何永富. 人工神经网络在测井解释中的应用[J]. 地球物理学报, 1995, 35(增刊1):323-330.
    [6]
    陶淑娴, 肖慈珣, 杨斌, 等. 神经网络在测井解释中的应用[J]. 石油物探, 1995, 34(3):90-102.
    [7]
    夏宏泉, 张贤辉, 范翔宇, 等. 基于神经网络法的逐点渗透率测井解释研究[J]. 西南石油学院学报, 2001, 23(1):11-13.
    [8]
    金燕, 张旭. 测井裂缝参数估算与储层裂缝评价方法研究[J]. 天然气工业, 2002, 22(增刊):64-67.
    [9]
    王捷. 油藏描述技术(勘探阶段)[M]. 北京:石油工业出版社,1996.
    [10]
    曾文冲. 油气藏储集层测井评价技术[M]. 北京:石油工业出版社,1991.
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