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滴南凸起石炭系火山岩储层地震识别与描述

Seismic identification and description of the Carboniferous volcanic reservoirs on the Dinan salient,Kelameili Gas Field

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【作者】 毛海波谷新萍朱明贺陆明

【Author】 Mao Haibo,Gu Xinping,Zhu Ming,He Luming(Exploration and Development Research Institute of Xinjiang Oilfield Company,PetroChina,Urumqi,Xinjiang 830013,China)

【机构】 中国石油新疆油田公司勘探开发研究院地球物理研究所

【摘要】 在克拉美丽气田的发现过程中,火山岩储层的地震识别与描述是勘探过程中使用的主体技术之一,对于在空间上寻找和优选火山岩储层发挥了重要作用。为此,以滴南凸起石炭系勘探为例,介绍了应用该项技术的成功经验与做法:①地震资料常规处理上,采用合理的静校正方法消除复杂地表影响,通过多域去噪提高地震资料信噪比,采用多次波压制、叠前时间、深度偏移的方法,改善火山岩地震成像品质;②在叠前偏移资料上建立了重要的火山岩地震相识别模式;③根据测井资料开展了火山岩敏感岩石物理参数分析,运用叠前弹性参数反演来预测火山岩储层分布。通过实施上述措施,形成了适用于该区石炭系火山岩储层的地震识别与描述技术。

【Abstract】 Seismic identification and description of volcanic reservoirs played an important role in the discovery of the Kelameili Gas Field.Such techniques have been successfully applied to the exploration of the Carboniferous volcanic reservoirs on the Dinan salient(Dinan refers to the southern Dishuiquan area),which is taken as a case study herein.In conclusion,this paper draws the following good experiences from this case study.(1) In conventional processing of seismic data,rational static correction methods were used to eliminate the influences of complex surface conditions;the multi-domain noise suppression technique was used to improve the signal-to-noise ratio;multiple rejection,pre-stack time migration,and pre-stack depth migration were applied to improve the quality of seismic imaging of volcanic reservoirs.(2) Models for the identification of seismic faces of volcanic rocks were established based on the pre-stack migration data.(3) Logging data were used to analyze sensitive petrophysical parameters of volcanic rocks which were integrated into pre-stack elastic parameter inversion for the prediction of volcanic reservoir distribution.Through all the above techniques,seismic identification and description are thus developed for the Carboniferous volcanic reservoirs in the study area.

【创新点】滴南凸起石炭系火山岩储层地震识别与描述

  • 【文献出处】 天然气工业 ,Natural Gas Industry , 编辑部邮箱 ,2012年02期
  • 【分类号】P631.4;P618.13
  • 【网络出版时间】2012-02-22 19:58
  • 【被引频次】9
  • 【下载频次】284
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