发明授权
US07587373B2 Neural network based well log synthesis with reduced usage of radioisotopic sources
有权
基于神经网络的井记录综合,减少放射性同位素来源的使用
- 专利标题: Neural network based well log synthesis with reduced usage of radioisotopic sources
- 专利标题(中): 基于神经网络的井记录综合,减少放射性同位素来源的使用
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申请号: US11270284申请日: 2005-11-09
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公开(公告)号: US07587373B2公开(公告)日: 2009-09-08
- 发明人: Harry D. Smith, Jr. , John A. Quirein , Jeffery L. Grable , Dingding Chen
- 申请人: Harry D. Smith, Jr. , John A. Quirein , Jeffery L. Grable , Dingding Chen
- 申请人地址: US TX Houston
- 专利权人: Halliburton Energy Services, Inc.
- 当前专利权人: Halliburton Energy Services, Inc.
- 当前专利权人地址: US TX Houston
- 主分类号: G06E1/00
- IPC分类号: G06E1/00 ; G06E3/00
摘要:
Logging systems and methods are disclosed to reduce usage of radioisotopic sources. Some embodiments comprise collecting at least one output log of a training well bore from measurements with a radioisotopic source; collecting at least one input log of the training well bore from measurements by a non-radioisotopic logging tool; training a neural network to predict the output log from the at least one input log; collecting at least one input log of a development well bore from measurements by the non-radioisotopic logging tool; and processing the at least one input log of the development well bore to synthesize at least one output log of the development well bore. The output logs may include formation density and neutron porosity logs.
公开/授权文献
- US20070011115A1 Well logging with reduced usage of radioisotopic sources 公开/授权日:2007-01-11