陕西省榆林地区油气远景区预测方法研究

发布时间：2018-03-26 12:37

本文选题：油气远景区　切入点：信息量模型　出处：《中国地质大学(北京)》2017年硕士论文

【摘要】：随着开发程度的不断深入,靖边气田探明面积内可供开发的区域越来越少。为了确保其产能,靖边气田的开发工作正在向气田周边进行,因此对靖边气田周围进行油气远景区预测的工作十分必要。在现有的油气远景区预测方法中,传统的找油方法往往只依靠各类油气相关地质因素进行,却忽略了对油气藏具有重要指示作用的烃类微渗漏信息,遥感找油法虽然可以充分利用这一信息,但是却以定性分析的方法圈定油气靶区,定量分析的方法较为少见。针对这些问题,本文以位于靖边气田东部的一块区域作为研究区,综合分析研究区的烃类微渗漏异常信息、生储盖地质条件以及构造信息,以遥感和地理信息系统为技术手段,运用信息量模型对研究区进行油气远景区定量分析预测。论文的主要研究内容如下:1、对烃源岩、储集层、盖层和构造信息的常用评价因素进行分析总结,结合已有的研究区资料选取了7个用于油气远景区预测的地质因子和构造因子,并通过缓冲区、插值等方法获得。2、利用ASTER数据,采取多种数据处理方法提取研究区烃类微渗漏异常信息,通过野外采样验证,利用矿物识别率和识别准确率两个指标验证了提取的矿物蚀变异常信息的有效性,得到了4个烃类微渗漏异常信息因子。3、利用相关系数矩阵对得到的所有因子进行独立性检验,剔除相关性较大的因子,最终选定了矿物蚀变异常信息、地表温度异常信息、上古生界烃源岩生烃强度、上古生界烃源岩镜质体反射率、储集层Hφ值、盖层厚度、到断层的距离这7个因子用于油气远景区预测。4、用选定的7个因子建立油气远景区预测的信息量模型,利用效率曲线验证模型计算结果的准确性和预测效果。对研究区的信息量进行分级,其中高和极高两个级别的区域被视为油气有利区域,并与研究区已探明储量的区域进行对比分析,证明了该方法的可靠性和适用性。最终圈定了位于横山镇东南部、赵石畔镇中部和东部的两块区域作为研究区下一步勘探的重点目标。
[Abstract]:As the level of development continues to deepen, there are fewer and fewer areas within the proven area of the Jingbian gas field that can be developed. In order to ensure its productivity, the development of the Jingbian gas field is proceeding to the periphery of the gas field. Therefore, it is very necessary to predict the oil and gas prospect area around Jingbian gas field. In the existing prediction methods of oil and gas remote area, the traditional oil prospecting method often only depends on all kinds of oil and gas related geological factors. However, the hydrocarbon microleakage information, which is an important indicator for oil and gas reservoirs, is neglected. Although remote sensing oil prospecting method can make full use of this information, it uses qualitative analysis to delineate oil and gas target areas. The quantitative analysis method is relatively rare. In view of these problems, a region located in the eastern part of Jingbian gas field is taken as the study area, the information of hydrocarbon microleakage anomaly, the geological condition of source, reservoir and caprock and the structural information of the study area are comprehensively analyzed in this paper. Using remote sensing and geographic information system as technical means, quantitative analysis and prediction of oil and gas scenic spots in the study area are carried out by using information quantity model. The main contents of this paper are as follows: 1, for hydrocarbon source rocks and reservoirs, The common evaluation factors of caprock and structural information are analyzed and summarized. Seven geological factors and tectonic factors used for prediction of oil and gas scenic spots are selected in combination with the existing data of the study area, and the method of buffer zone and interpolation is used to obtain. 2, and the ASTER data are used. A variety of data processing methods are used to extract hydrocarbon microleakage anomaly information in the study area. Through field sampling and verification, the validity of extracted mineral alteration anomaly information is verified by mineral recognition rate and recognition accuracy. Four information factors of hydrocarbon microleakage anomaly were obtained. The correlation coefficient matrix was used to test the independence of all the factors obtained. The mineral alteration anomaly information and the surface temperature anomaly information were finally selected. The hydrocarbon generation intensity of the Upper Paleozoic source rock, the vitrinite reflectance of the Upper Paleozoic source rock, the H 蠁 value of the reservoir, the thickness of the caprock, The seven factors of distance to faults are used to predict oil and gas scenic spots. The information quantity model of oil and gas scenic spot prediction is established with the selected seven factors. The efficiency curve is used to verify the accuracy and prediction results of the model. The information content in the study area is classified, in which the regions of high and very high levels are regarded as favorable areas for oil and gas. The reliability and applicability of the method are proved by comparison with the proven reserves in the study area. Finally, the method is located in the southeast of Hengshan Town. The two areas in the middle and east of Zhao Shizhang Town are the key targets for further exploration in the research area.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P618.13

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