Prediction of reservoir parameters is always the bottle neck problem and difficulty in seismic survey.
储层参数预测一直是地震勘探的关键和难点问题。
The application of an example proves that the method demonstrated its superiority when using in the prediction of reservoir parameters of complex formations.
实例证明该方法应用在复杂地层储层参数预测中具有优越性。
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。
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。
However. the authors developed a new method available for the prediction on reservoir parameters of only two Wells, applying geostatistics combined with fractional geometry in reservoir description.
作者在油藏描述中利用地质统计与分形几何学相结合的方法，开发了只有两口井条件下的井间储层参数预测方法。
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。
The results show that the small errors of less than 12% between the prediction and measured values are achieved due to the reservoir parameters, fluid physical property and non-Darcy skin factor.
结果表明：预测模型考虑煤层参数、流体物性和非达西表皮效应，结果具有较高精度，整体误差可控制在12%以内。
This thesis studies on the prediction modeling method of water quality parameters based on normal time-series data in the background of the Three Gorges Reservoir.
本文以三峡库区常态水质参数时序数据为研究对象，进行水质参数预测建模研究。
This thesis studies on the prediction modeling method of water quality parameters based on normal time-series data in the background of the Three Gorges Reservoir.
本文以三峡库区常态水质参数时序数据为研究对象，进行水质参数预测建模研究。
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