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Gas-Chimney Detection in 3D Seismic by Neural Network

机译:神经网络在3D地震气烟囱检测中的应用

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摘要

Recognition of hydrocarbon migration is so vital for petroleum exploration. Developing intelligent systems (artificial neural network) enable experts to achieve more details from seismic data. Although detection of migration direction using seismic data is difficult, Chimney-cube analysis overcomes this problem. The authors used several filters, seismic attributes, neural network (supervised and unsupervised), and interpreters' viewpoints. In supervised method artificial and human intelligence cover their limitations and in unsupervised method the authors eliminate the experts' views. Chimney recognizes the migration direction and locates the spill points, mud volcanoes, gas seepages, sealing, and nonsealing faults and finally the origin of hydrocarbon.
机译:碳氢化合物迁移的识别对于石油勘探至关重要。开发智能系统(人工神经网络)使专家可以从地震数据中获得更多细节。尽管使用地震数据检测迁移方向很困难,但烟囱立方体分析克服了这个问题。作者使用了几种过滤器,地震属性,神经网络(有监督的和无监督的)以及解释者的观点。在有监督的方法中,人工智能和人类智能弥补了其局限性;在无监督的方法中,作者消除了专家的观点。烟囱可识别迁移方向,并确定溢出点,泥火山,气体渗漏,密封和非密封性断层,最后确定碳氢化合物的来源。

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