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Method of Creation of “Core-Gisseismic Attributes” Dependences With Use of Trainable Neural Networks

机译:利用可训练神经网络创建“核心 - Gisseismic属性”的方法

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The study describes methodological techniques and results of geophysical well logging and seismic data interpretation by means of trainable neural networks. Objects of research are wells and seismic materials of Talakan field. The article also presents forecast of construction and reservoir properties of Osa horizon. The paper gives an example of creation of geological (lithological -facial) model of the field based on developed methodical techniques of complex interpretation of geologicgeophysical data by trainable neural network. The constructed lithological -facial model allows specifying a geological structure of the field. The developed methodical techniques and the trained neural networks may be applied to adjacent sites for research of carbonate horizons.
机译:该研究描述了通过培训神经网络的地球物理井测井和地震数据解释的方法论和结果。研究对象是Talakan领域的井和地震材料。本文还介绍了OSA地平线的建设和储层特性预测。本文介绍了基于培训神经网络的复杂地质神经数据复杂解释的开发方法技术的地质(岩性凝视)模型的创建示例。构造的岩性矩形模型允许指定该领域的地质结构。开发的方法和训练的神经网络可以应用于相邻部位以研究碳酸盐地平线。

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