| 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 |
| 基于神经网络和GIS 的储层裂缝预测与可视化 |
| Prediction and Visualization of Reservoir Fracture Based on ANN and GIS |
| 投稿时间：2010-07-31 修订日期：2011-01-17 |
| DOI： |
| 中文关键词: 裂缝 预测 神经网络 GIS 可视化 |
| 英文关键词: fissure, prediction, neural network, GIS, visualization |
| 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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| 中文摘要: |
| [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可视化。结果表明,基于GIS 的裂缝可视化
方法方便快捷,加上其强大的二次开发能力,可以把专业算法无缝地集成到GIS 中。 |
| 英文摘要: |
| Abstract:Prediction and visualization of fissure distribution in low-permeability reservoirs is an important issue in petroleum exploration and develop鄄
ment. 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 experi鄄
ments to predict fissure distribution beneath the study area. Then secondary development based on ArcGIS and C-Tech was carried out for 2D & 3D visu鄄
alization of fisure distribution. The experimental result shows the convenience of GIS-based technology in seamless in tegration of professional algorithms. |
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