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最大似然属性在断裂识别中的应用——以塔里木盆地哈拉哈塘地区热瓦普区块奥陶系走滑断裂的识别为例
Application of maximum likelihood attribute to fault identification:A case study of Rewapu block in Halahatang area,Tarim Basin,NW China
【摘要】 断裂是重要的油气储集空间和渗流通道,控制着油气藏形成与分布。断裂的精细刻画是油气藏勘探开发的关键环节。利用最大似然属性进行哈拉哈塘地区热瓦普区块奥陶系走滑断裂识别,取得良好的应用效果。最大似然属性是通过对整个地震数据体扫描计算数据样点之间的相似性,获得研究区内断裂发育的最可能位置及概率,提升断裂刻画精度。关键步骤包括:(1)断裂的地震反射特征分析;(2)倾角控制下断裂成像加强;(3)最大似然属性的提取(Likelihood属性、Thin Likelihood属性);(4)属性切片的解译。热瓦普区块奥陶系走滑断裂的刻画证实最大似然属性刻画的断裂效果优于相干体,其中Likelihood属性对于分支断裂的刻画效果较好,Thin Likelihood属性对于分支断裂以及断裂带内部结构的刻画较为清楚,还对裂缝密集发育区的预测有一定的效果。
【Abstract】 Fault is an important reservoir space and percolation channel,which controls the formation and distribution of oil and gas reservoirs.The fine depiction of faults is the key step in the exploration and development of oil and gas reservoirs.In this paper,the maximum likelihood attribute is applied in Rewapu block,Halahatang area,and it works well in identifying the Ordovician strike slip faults.The maximum likelihood attribute is to get the most probable location and probability of fault development in the study area by scanning the similarity between the seismic data points in the whole seismic volume,and improving the accuracy of fault identification.The key steps include:(1)Analysis of seismic reflection characteristics of faults;(2)Imaging enhancement for faults under the control of dip angle;(3)Extraction of maximum likelihood attribute(likelihood,thin likelihood);(4)Interpretation of attribute slice.The case study in Rewapu block proves that fault distribution depicted by maximum likelihood attribute is better than that of coherence body.The likelihood attribute is better for the portrayal of branch fault,and thin likelihood attribute is more applicable to the depiction of the branch fault and the internal structure of the fault zone,and it also works well on the prediction of the fractured dense zone.
【Key words】 Maximum likelihood attribute; Likelihood; Thin likelihood; Fault identification; Halahatang area;
- 【文献出处】 天然气地球科学 ,Natural Gas Geoscience , 编辑部邮箱 ,2018年06期
- 【分类号】P618.13
- 【被引频次】50
- 【下载频次】780