The relations of velocity and density with reservoir parameters are crucial to seismic data interpretation and reservoir parameters prediction.

油气储层速度和密度与储层参数的关系对地震资料解释以及储层参数预测等具有重要的意义。

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In the past, the prediction of the reservoir production capacity by logging parameters was based on a single testing well.

过去人们利用测井参数对储层产能的预测都是基于单层测试资料。

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Using an example, a method based on probabilistic neural network technique is introduced, which aims at prediction of petrophysical parameters for reservoir.

通过实例介绍了利用一种概率神经网络技术预测储层物性参数的方法。

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