ISSN 1004-4140
CN 11-3017/P
黄捍东, 张建军, 刘伟, 沈金松. 地震相控混沌反演在岩性油气藏储层预测中的应用——以RY坳陷M井区为例[J]. CT理论与应用研究, 2019, 28(5): 549-557. DOI: 10.15953/j.1004-4140.2019.28.05.04
引用本文: 黄捍东, 张建军, 刘伟, 沈金松. 地震相控混沌反演在岩性油气藏储层预测中的应用——以RY坳陷M井区为例[J]. CT理论与应用研究, 2019, 28(5): 549-557. DOI: 10.15953/j.1004-4140.2019.28.05.04
HUANG Handong, ZHANG Jianjun, LIU Wei, SHEN Jinsong. Application of Chaos Inversion Controlled by Seismic Facies in Prediction of Lithologic Reservoirs: A Case Study of M Well Area in RY Depression[J]. CT Theory and Applications, 2019, 28(5): 549-557. DOI: 10.15953/j.1004-4140.2019.28.05.04
Citation: HUANG Handong, ZHANG Jianjun, LIU Wei, SHEN Jinsong. Application of Chaos Inversion Controlled by Seismic Facies in Prediction of Lithologic Reservoirs: A Case Study of M Well Area in RY Depression[J]. CT Theory and Applications, 2019, 28(5): 549-557. DOI: 10.15953/j.1004-4140.2019.28.05.04

地震相控混沌反演在岩性油气藏储层预测中的应用——以RY坳陷M井区为例

Application of Chaos Inversion Controlled by Seismic Facies in Prediction of Lithologic Reservoirs: A Case Study of M Well Area in RY Depression

  • 摘要: RY坳陷M井区位于浅水三角洲前缘斜坡带,多发育水下分流河道沉积,砂岩储层厚度薄、横向变化快,且同一时期的砂体在平面上表现为多套油水系统,容易形成岩性油气藏,利用常规手段进行储层预测的难度较大。本文通过引入地震相控制,利用纵向及横向上的构造起伏、岩性变化、沉积环境变迁等先验信息降低了反演的多解性;同时将混沌理论与反演算法结合,根据反演迭代的实时状态自适应地修改正则化算子,调节反演稳定性和分辨率达到最佳平衡,既避免了混沌现象的出现,又最大限度地揭示薄层信息。M井区的实际应用显示,相控混沌反演可以突出地震波形的细节变化,准确刻画储层尖灭和分叉点位置,达到精准预测岩性油气藏的目的,对后续岩性油气藏的勘探开发具有较大指导意义。

     

    Abstract: The M well area of RY depression is located in the slope belt of the shallow water delta front, where underwater distributary channel sandstone is mostly developed. The thickness of sandstone reservoir is thin and changes quickly the horizontal direction. In addition, the sand body in the same period is featured by multiple oil-water systems. Hence, it is easy to form lithologic reservoirs, which is very difficult to predict by conventional inversion methods. In this paper, we introduce seismic phase interface, such as structural fluctuation, lithologic change and sedimentary environment change, to reduce the multi-solution of inversion. Meanwhile, we combine chaos theory with inversion algorithm to modify adaptively regularization operator. Doing like that can adjust stability and resolution of inversion to reach the optimal balance, which not only avoids the occurrence of chaos, but also reveals the information of thin layer to the maximum extent from seismic data. The practical application of well M shows that phased chaos inversion can highlight the detailed changes of seismic waveform, accurately describe the positions of reservoir annihilation and bifurcation points, and achieve the purpose of accurately predicting lithologic oil and gas reservoirs. This paper is of great guiding significance for subsequent exploration and development of lithologic reservoirs.

     

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