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首页> 外文会议>International symposium on neural networks;ISNN 2009 >A Hybrid MPSO-BP-RBFN Model for Reservoir Lateral Prediction
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A Hybrid MPSO-BP-RBFN Model for Reservoir Lateral Prediction

机译：MPSO-BP-RBFN混合模型在储层横向预测中的应用

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摘要

The degree of success of many oil and gas drilling, completion, and production activities depends on the accuracy of the models used in the reservoir lateral prediction and description. In this paper, a hybrid MPSO-BP-RBFN model for predicting reservoir from seismic attributes is proposed. The model in which every particle consists of binary and real parts is able to simultaneously search for optimal network topology (the number of hidden nodes) and parameters, as it proceeds. The model has been used to reservoir lateral prediction of a reservoir zone and proved the model's applicability.
机译：许多油气钻探，完井和生产活动的成功程度取决于在储层横向预测和描述中使用的模型的准确性。本文提出了一种基于地震属性预测储层的MPSO-BP-RBFN混合模型。每个粒子都由二进制和实数部分组成的模型可以在进行过程中同时搜索最佳网络拓扑（隐藏节点数）和参数。该模型已用于储层横向储层预测，证明了该模型的适用性。

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