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齐古地区常规测井地应力预测及裂缝识别方法研究

Study on Geostress Prediction and Crack Identification Method of Conventional Logging in Qigu Area

【作者】 张小龙

【导师】 李生杰;

【作者基本信息】 中国石油大学(北京) , 地球物理学, 2018, 硕士

【摘要】 本文以准噶尔盆地南缘齐古背斜地区实际勘探为例,开展了地应力分析与裂缝识别研究。首先对测井数据进行环境校正以及归一化处理,然后对处理后的测井数据开展了地层参数处理研究,获得该地区五口井的孔隙度、泥质含量以及含水饱和度等曲线。针对该地区岩性复杂、非均质性强等特点,开展了地层岩石物理体积模型构建方法研究,并采用最优化求解技术获得目的层段各地层的岩石矿物含量。采用改进的Biot-Gassmann理论预测了该地区横波速度,通过对比发现预测的横波速度与实测横波速度基本一致。在此基础上,本项研究开展了地应力预测方法研究,分别采用纵横波速度测井曲线、地层密度测井曲线计算了地层动态弹性模量及上覆地层压力,基于有效应力原理预测了地层孔隙压力;然后根据孔弹性理论关系,计算垂向地应力、最大、最小水平地应力等参数。最后,采用了支持向量机分析方法探讨了致密储层裂缝识别方法。通过本文的研究,为储层预测提供了理论支持。

【Abstract】 Taking the actual exploration of Qigu anticline area in the southern margin of Junggar basin as an example,the geostress analysis and crack identification are carried out.First,the logging data are corrected and normalized;and then the formation parameters are processed to obtain the curves of porosity,mud content and water saturation of the five wells in the area.In view of the characteristics of complex lithology and strong heterogeneity in this area,the construction method of physical volume model of strata rock is studied,and the rock mineral content of the target layer is obtained by the optimization method.The shear wave velocity in this area is predicted by the improved Biot-Gassmann theory.By comparison,it is found that the predicted shear wave velocity is basically the same as the measured shear wave velocity.On this basis,the study of geostress prediction is carried out in this study.The dynamic elastic modulus and overlying strata pressure are calculated by the P-wave and S-wave velocity logging curves and the density logging curves respectively.The pore pressure is predicted based on the effective stress principle.Then according to the relationship between pore elasticity theory,we calculate vertical geostress,maximum and minimum horizontal stress and other parameters.Finally,the method of support vector machine analysis is used to identify the fractures in tight reservoirs.This study provides theoretical support for reservoir prediction.

  • 【分类号】P631.81;P618.13
  • 【下载频次】225
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