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    花岗岩型干热岩储层裂缝刻画的三维地震属性分析技术研究

    Research on three-dimensional seismic attribute fusion technology for characterizing fractures in granite geothermal reservoirs

    • 摘要:
      研究目的 花岗岩型干热岩储层中天然裂缝的发育特征对增强型地热系统(EGS)工程中钻孔部署和开采方案确定至关重要。
      研究方法 本文旨在通过高精度的地震资料和属性特征分析方法,对花岗岩储层中天然裂缝的特征、空间分布进行预测,为EGS工程施工提供科学依据。本文利用宽频带、宽角度、高密度采样的三维地震数据,采用构造导向滤波和多窗口倾角扫描等处理方法,这些技术的应用提高了地震资料的信噪比,进一步优化了花岗岩内幕探测效果。同时,本文还结合多方位角约束的地震属性体、最大似然体、相干体、曲率体、方差体和蚂蚁体等三维地震属性,对裂缝簇的空间分布密度进行了预测。
      研究结果 通过综合属性分析认为研究区花岗岩型干热岩储层主要发育北东向和北西向裂缝的规律,该规律与钻孔成像测井结果高度吻合。
      结论 通过高精度的地震资料和属性特征分析方法,成功预测了花岗岩型干热岩储层中天然裂缝的特征和空间分布,为EGS工程施工中的裂隙探测、钻孔部署和开采方案确定提供了重要依据。

       

      Abstract:
      This paper is the result of geothermal survey engineering.
      Objective It is necessary to predict the characteristics, spatial distribution and density of natural fractures in granite reservoirs using high−precision seismic data and feature analysis methods, which provide scientific evidence for the construction of Enhanced Geothermal System (EGS).
      Methods This study adopted advanced 3D seismic techniques, including wideband, wide−angle, high−density sampling, as well as advanced processing methods such as structural−oriented filtering and multi−window dip scanning. The application of these techniques greatly improved the signal−to−noise ratio of seismic data, further optimizing the detection effect of the granite interior. At the same time, this study also combines 3D seismic attributes such as seismic attribute volume, maximum likelihood volume, coherence volume, curvature volume, variance volume, and ant volume with multi−azimuth constraints to accurately predict the spatial distribution density of fracture clusters.
      Results Through comprehensive attribute analysis and drilling imaging logging results, we reveal the regularity of the development of northeast and northwest fractures in granite−type hot dry rock reservoirs. These results are highly consistent with drilling imaging logging results, further verifying the accuracy and reliability of this research method.
      Conclusions This study successfully predicted the characteristics, spatial distribution, and density of natural fractures in granite−type hot dry rock reservoirs through high−precision seismic data and feature analysis methods. This method provides important evidence for fracture detection, drilling deployment, and mining plan determination in EGS engineering construction.

       

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