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基于地震纹理属性聚类分析的磨溪地区台内带灯四段储层预测研究 被引量:3

Reservoir prediction of Sinian Deng 4 member in the intra-platform of Moxi area based on seismic texture attributes clustering method
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摘要 磨溪地区震旦系灯影组四段已经在台缘带获得了重大油气勘探成果,但是灯四段台内滩储层非均质性强,采用台缘带的储层预测方法不能有效地表征台内带灯四段的储层发育特征,即单一振幅属性或波阻抗反演难以准确地进行储层预测.本文从地震相分析的角度出发,对比分析了常规的地震波形分类和基于地震纹理属性聚类分析的台内带灯四段的储层预测符合率,发现基于地震纹理属性聚类分析得到的地震相平面特征与研究区的完钻井储层发育情况符合率高,有效地表征了储层发育区与非储层发育区,有助于提高台内带灯四段的勘探成功率. Major oil and gas exploration achievements has been found in the fourth member of the Sinna Dengying Formation in Moxi area.The intra-platform reservoir in this area have strong heterogeneity;therefore,using the reservoir prediction method of platform margint cannot efficiently characterize the reservoir development characteristics of the fourth member of the Sinna Dengying Formation.And using single amplitude attributes or Wave Impedance Inversion is difficult to accurately predict reservoirs.The frequency,amplitude and phase of seismic wave can affect the characteristics of seismic texture attributes.We use clustering analysis based on seismic texture attributes to predicte plane features of the study area’s seismic facies.From the perspective of seismic facies analysis,the coincidence rate of conventional seismic waveform classification and clustering analysis based on seismic texture attributes have been compared and analyzed in this paper.We found this method have the higher coincidence rate with completed wells.This method can efficiently characterize developed zone of reservoirs.It is helpful to improve the exploration success rate of the fourth member of the Dengying Formation.
作者 许志远 熊晓军 肖尧 张敏知 唐松 熊高君 XU ZhiYuan;XIONG XiaoJun;XIAO Yao;ZHANG MinZhi;TANG Song;XIONG GaoJun(College of Geophysics,Chengdu University of Technology,Chengdu 610059,China;Central Sichuan Division,PetroChina Southwest Oil and Gasfield Company,Suining 629000,China)
出处 《地球物理学进展》 CSCD 北大核心 2022年第3期1207-1213,共7页 Progress in Geophysics
基金 国家科技重大专项(2016ZX05023004-001-003)资助。
关键词 灯影组 台内带 地震相 纹理 聚类分析 Dengying Formation Intra-platform Seismic facies Texture Cluster analysis
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