| 基于MATLAB的BP神经网络在储层物性预测中的应用 |
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| 引用本文： | 陈蓉,王峰.基于MATLAB的BP神经网络在储层物性预测中的应用[J].测井技术,2009,33(1). |
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| 作者姓名： | 陈蓉 王峰 |
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| 作者单位： | 1. 成都理工大学沉积地质研究院,四川,成都,610059;成都理工大学博物馆,四川,成都,610059
2. 成都理工大学沉积地质研究院,四川,成都,610059 |
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| 摘 要： | 在阐述BP神经网络模型结构的基础上.根据取心井段储层物性与测井信息的关系,选取相应的测井曲线,运用MATLAB神经网络工具箱中特定的函数对建立的神经网络模型进行训练,使得储层物性(孔隙度、渗透率)和测井响应之间具有较强的非线性映射关系,在一定的条件下运用该模型可对研究区未知样本的物性参数进行预测.实例研究表明,预测准确性较高,显示出BP神经网络对储层预测的潜在优势和实用价值.
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| 关 键 词： | BP神经网络 孔隙度 渗透率 预测 储层物性 |
Application of MATLAB-based of BP Neural Network in Reservoir Parameters Prediction |
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| CHEN Rong,WANG Feng.Application of MATLAB-based of BP Neural Network in Reservoir Parameters Prediction[J].Well Logging Technology,2009,33(1). |
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| Authors: | CHEN Rong WANG Feng |
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| Affiliation: | 1.Sediment Geology Institute;Chengdu University of Technology;Chengdu;Sichuan 610059;China;2.Museum of Chengdu University of Technology;China |
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| Abstract: | On the basis of expounding structure of the BP neural network model,and considering the relationship between reservoir the physical properties and well logging data,the authors iterate the constructed BP neural network model by choosing corresponding well logging data and using functions of neural network toolbox offered by MATLAB.This process can establish better nonlinear mapping relationship between reservoir physical parameters(porosity and permeability) and well logging data,with which we can predict t... |
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| Keywords: | MATLAB |
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