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气烟囱识别新技术及其在A盆地中的应用

A New Technique for the Identification of Gas Chimney and Its Application in Basin A
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摘要 气烟囱是热流体在地层中活动时伴生的一种特殊构造。气烟囱可作为油、气、水等流体运移的通道,亦可连接烃源岩和上覆地层中的圈闭,从而决定了油气运移及成藏模式。石油地质和地球物理工作者分别从形成条件、控制因素以及模式类型、地震反射特征对气烟囱进行了大量的研究。此文重点介绍一种基于倾角/方位角导向体控制下的地震气烟囱识别技术(Opend Tect平台)。首先通过多类型的倾角/方位角扫描技术,在时间域或者深度域地震数据上生成包含倾角/方位角信息的导向体数据,然后拾取种子点,利用基于有监督分析的神经网络计算方法对大量的地震属性进行优化排序分析,从而得出能够反映气烟囱体特征的最佳地震属性类型,用来预测气烟囱的发生概率体。该方法很好地补充和发展了模式识别技术在地震勘探领域中的应用。应用这一技术对A盆地烟囱体进行识别分析的结果表明,目标圈闭顶部烟囱效应明显,表明研究对象具有很高的含油气性,勘探潜力较大。 Gas chimney is a special associated structure produced by the activity of thermal fluid in the strata.The occurrence of gas chimney decides the migration of hydrocarbon and the accumulation mode as it acts as migration passageway of oil,gas and water or as the connection of source rock with the traps in the overlying stata.Many studies have been performed by petroleum geologists and geophysicists from the formation condition,controlling factor,mode and seismic reflection characteristics.This paper focuses on the introduction of OpendTec,a new technique for the identification of gas chimney,which is based on the control of dip/azimuth steering,and its application in Basin A.In the process of identification,the steering data containing dip/azimuth information are firstly generated on the seismic data of time domain or depth domain by different dip/azimuth scanning techniques.And then,pick up the seed points,optimize and rank the large amounts of seismic attributes by the neutral network computing with the control of seed points.Finally,the optimum seismic attributes that reflect the characteristics of gas chimney can be obtained and are used to predict the probability of occurrence for gas chimney.This technique supplements the application of pattern recognition technology in the seismic exploration field.The application of this technique in Basin A indicates that there are obvious chimney effects on the top of the target traps,which means the study objects have large probability of oil-gas-bearing,with the potential of exploration.
作者 余学兵
出处 《海洋石油》 CAS 2017年第2期1-7,共7页 Offshore Oil
关键词 倾角数据体 神经网络 气烟囱识别 Dip steering data neural network identification of gas chimney
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