Developing neural network analysis technology for the resolution of issues in oil and gas geophysics

S. K. Turenko
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Abstract

   Neural network analysis represents a promising avenue for enhancing the efficacy of petroleum geophysics and the oil and gas industry. The analysis of the obtained experience of using the available neural network analysis methods and software packages in solving problems of oil and gas geophysics shows the absence of a significant (breakthrough) effect. In order to achieve a significant effect, it is proposed to move from methods to neural network analysis technologies. The article presents a fundamental framework for neural network analysis technology in the context of oil and gas geophysics. This includes a neural network designer, a subsystem for training geophysicists in the field of neural network analysis, a digital polygon, and a knowledge base comprising tasks, neural network analysis methods, techniques, and experience in solving applied problems. The elements of the proposed technology and their interrelation are discussed in detail. The pilot version of the proposed technology, which includes its principal elements, is initially described in terms of its orientation towards the training of specialists. The results of the pilot version's approval have demonstrated the efficacy of the proposed technology. The scientific and technological priorities of the proposed technology development have been delineated.
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开发神经网络分析技术,解决石油和天然气地球物理问题
神经网络分析是提高石油地球物理和石油天然气工业效率的一条大有可为的途径。对使用现有神经网络分析方法和软件包解决石油和天然气地球物理问题的经验进行的分析表明,没有取得显著的(突破性的)效果。为了取得显著效果,建议从方法转向神经网络分析技术。文章介绍了石油和天然气地球物理学中神经网络分析技术的基本框架。其中包括一个神经网络设计器、一个用于培训神经网络分析领域地球物理学家的子系统、一个数字多边形,以及一个由任务、神经网络分析方法、技术和解决应用问题的经验组成的知识库。详细讨论了拟议技术的要素及其相互关系。首先介绍了拟议技术的试验版本,其中包括其主要元素,该版本面向专家培训。试验版本的批准结果表明了拟议技术的有效性。对拟议技术开发的科学和技术重点进行了界定。
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