| 基于神经网络和GIS的储层裂缝预测与可视化 |
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| 引用本文： | 周子勇.基于神经网络和GIS的储层裂缝预测与可视化[J].地质与勘探,2011,47(3):492-497. |
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| 作者姓名： | 周子勇 |
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| 作者单位： | 油气资源与探测国家重点实验室,中国石油大学(北京)地球科学学院,北京102200 |
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| 基金项目： | 中国石油天然气股份有限公司科技风险创新研究项目(编号07-06D-01-04-01-08)资助 |
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| 摘 要： | 低渗透储层裂缝预测与可视化是油气勘探开发工作中的一个重要课题.以鄂尔多斯盆地杏河区长6-1油层组为研究对象,根据已有的分形维、砂地比、破裂率等数据,构建BP神经网格,通过试验设计出最优的网格拓扑结构和训练函数,对研究区的裂缝分布情况进行预测.然后以ArcGIS为基础,通过二次开发以及C-Tech实现裂缝数据的二维及三维...
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| 关 键 词： | 裂缝 预测 神经网络 GIS 可视化 |
| 收稿时间： | 2010/7/31 0:00:00 |
| 修稿时间： | 2011/1/17 0:00:00 |
Prediction and Visualization of Reservoir Fracture Based on ANN and GIS |
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| ZHOU Zi-yong.Prediction and Visualization of Reservoir Fracture Based on ANN and GIS[J].Geology and Prospecting,2011,47(3):492-497. |
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| Authors: | ZHOU Zi-yong |
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| Institution: | ZHOU Zi-yong,WANG Chun-xiao,ZENG Lian-bo State Key Laboratory of Petroleum Resource and Prospecting,College of Geosciences,China University of Petroleum,Beijing 102200 |
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| Abstract: | Prediction and visualization of fissure distribution in low-permeability reservoirs is an important issue in petroleum exploration and development. Taking the oil-bearing formation Chang 6-1 in the Ordos basin as an example, this work constructed a BP ANN (Artificial Neural Network) based on the known fractal dimension, sand/formation ratio and crack ratio, and designed an optimum network topology and training function through experiments to predict fissure distribution beneath the study area. Then secondar... |
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| Keywords: | fissure prediction neural network GIS visualization |
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