Application of Series Inversion of Multi-Attribute Regression and Probabilistic Neural Network to Thin Reservoir Prediction
详细信息
- 责任者：Wang Xiaohui (College Resource and Environment ; Southwest Petroleum University ; Chengdu 610081 ; China) ; Fan Sufang
- 刊名：Xinjiang Petroleum Geology
- 出版年：2013
- 卷期：34(3)
- 关键词：反演问题 ; inverse problem ; 储层预测 ; reservoir prediction ; 准噶尔盆地 ; Junggar Basin
- 页码：p.324-327
- 图表：illus., 7 refs.
- 分类号：1600
- issnNo：ISSN1001-3873
- isbnNo：CN65-1107/TE
摘要
This paper presents GR curves inversion for thin reservoir characterization in the studied area,using the series inversion of multi-attribute regression(MAR) and probabilistic neural network(PNN) based on the geophysical response analysis of reservoir.The result shows that the sand body prediction accords with the whole sedimentary features in the studied area,with high vertical resolution,clear boundary of lateral sand bodies.It could properly reflect the distribution of reservoirs and can be as a guide for next petroleum exploration in this area.
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