Abstract：In the past, shale oil in the fourth member of Shahejie Formation (Es4) in Damintun Sag was studied by the technical ideas of tight oil exploration. This way of exploration, however, faces the following problems. First, as oil shale is the source rock of Es4, we pay more attention to its hydrocarbon generation capacity but neglect its reservoir capacity. Second, we often use conventional techniques such as impedance inversion and seismic attribute analysis to predict the geological sweet spots, but the results are multi-solution. Third, the parameters related to the engineering sweet spots (reservoir brittleness, fractures, etc.) have not been predicted yet. Therefore, on the basis of the comprehensive application of geological data and petrophysical analysis, the main evaluation factors of source rock quality, reservoir quality, and engineering quality are determined, and the relational model between main evaluation factors and geophysical response parameters is built. Given the seismic data of "wide azimuth, Wide broadband, and high density (WBH)", this study accurately predicts the distribution of sweet spots for shale oil in groups and factors and hence, forms geophysical methods and a technical process for predicting the sweet spots of terrestrial shale oil. The following knowledge is obtained:Group Ⅰ is dominated by oil shale, aiming to search for organic-rich oil shale, and TOC value prediction is the key point. Group Ⅱ is dominated by argillaceous dolomite, with excellent reservoir physical properties and developed dissolved fractures; the prediction of reservoir lithology and fractures is the key, and the prediction of the reservoir brittleness index is also important. The lower part of Group Ⅲ is to look for high-quality sand bodies, and the upper part is to look for stable argillaceous dolomite; the lithology prediction of reservoirs is the key.
邱振, 李建忠, 吴晓智, 等.国内外致密油勘探现状、主要地质特征及差异[J].岩性油气藏, 2015, 27(4):119-126.QIU Zhen, LI Jianzhong, WU Xiaozhi, et al.Exploration status, main geologic characteristics and their differences of tight oil between America and China[J].Lithologic Reservoirs, 2015, 27(4):119-126.
[2]
杜金虎, 何海清, 杨涛, 等.中国致密油勘探进展及面临的挑战[J].中国石油勘探, 2014, 19(1):1-9.DU Jinhu, HE Haiqing, YANG Tao, et al.Progress in China's tight oil exploration and challenges[J].China Petroleum Exploration, 2014, 19(1):1-9.
[3]
胡素云, 赵文智, 侯连华, 等.中国陆相页岩油发展潜力与技术对策[J].石油勘探与开发, 2020, 47(4):819-828.HU Suyun, ZHAO Wenzhi, HUO Lianhua, et al.Development potential and technical strategy of continental shale oil in China[J].Petroleum Exploration and Development, 2020, 47(4):819-829.
[4]
赵文智, 胡素云, 侯连华, 等.中国陆相页岩油类型、资源潜力及与致密油的边界[J].石油勘探与开发, 2020, 47(1):1-10.ZHAO Wenzhi, HU Suyun, HUO Lianhua, et al.Types and resource potential of continental shale oil in China and its boundary with tightoil[J].Petroleum Exploration and Development, 2020, 47(1):1-10.
[5]
邹才能, 杨智, 崔景伟, 等.页岩油形成机制、地质特征及发展对策[J].石油勘探与开发, 2013, 40(1):14-26.ZOU Caineng, YANG Zhi, CUI Jingwei, et al.Formation mechanism, geological charactertics and development stategy of nonmarine shale oil in China[J].Petroleum Exploration and Development, 2013, 40(1):14-26.
[6]
张金川, 林腊梅, 李玉喜, 等.页岩油分类与评价[J].地学前缘, 2012, 19(5):322-331.ZHANG Jinchuan, LIN Lamei, LI Yuxi, et al.Classification and evalution of shale oil[J].Earth Science Frontiers, 2012, 19(5):322-331.
[7]
刘喜武, 刘宇巍, 刘志远, 等.陆相页岩油甜点地球物理表征研究进展[J].石油与天然气地质, 2019, 40(3):504-511.LIU Xiwu, LIU Yuwei, LIU Zhiyuan, et al.Progresses in geophysical characterization of continental shale oil sweet spots[J].Oil & Gas Geology, 2019, 40(3):504-511.
[8]
宁方兴.济阳坳陷页岩油富集主控因素[J].石油学报2015, 36(8):905-914.NING Fangxing.The main control factors of shale oil enrichment in Jiyang depression[J].Acta Petrolei Sini-ca, 2015, 36(8):905-914.
[9]
李晓光, 刘兴周, 李金鹏, 等.辽河坳陷大民屯凹陷沙四段湖相页岩油综合评价及勘探实践[J].中国石油勘探, 2019, 24(5):636-648.LI Xiaoguang, LIU Xingzhou, LI Jinpeng, et al.Comprehensive evaluation and exploration practice of Sha 4 lacustrine shale oil in Damintun sag, Liaohe depression[J].China Petroleum Exploration, 2019, 24(5):636-648.
印兴耀, 张洪学, 宗兆云.OVT数据域五维地震资料解释技术研究现状与进展[J].石油物探, 2018, 57(2):155-178.YIN Xingyao, ZHANG Hongxue, ZONG Zhaoyun.Research status and progress of 5D seismic data interpretation in OVT domain[J].Geophysical Prospecting for Petroleum, 2018, 57(2):155-178.
[14]
龚明平, 张军华, 王延光, 等.分方位地震勘探研究现状及进展[J].石油地球物理勘探, 2018, 53(3):642-658.GONG Mingping, ZHANG Junhua, WANG Yanguang, et al.Current situations and recent progress in different azimuths seismic exploration[J].Oil Geophysical Prospecting, 2018, 53(3):642-658.
[15]
许晓宏, 黄海平, 卢松年.测井资料与烃源岩有机碳含量的定量关系研究[J].江汉石油学院学报, 1998, 20(3):8-12.XU Xiaohong, HUANG Haiping, LU Songnian.A quantitative relationship between well logging information and organic carbon content[J].Journal of Jianghan Petroleum Institute, 1998, 20(3):8-12.
[16]
朱振宇, 刘洪, 李幼铭.ΔlogR技术在烃源岩识别中的应用与分析[J].地球物理学进展, 2003, 18(4):647-649.ZHU Zhenyu, LIU Hong, LI Youming.The analysis and application of ΔlogR method in the source rock's identification[J].Progress in Geophysics, 2003, 18(4):647-649.
[17]
何火华, 李少华, 杜家元, 等.利用地质统计学反演进行薄砂体储层预测[J].物探与化探, 2011, 35(6):804-808.HE Huohua, LI Shaohua, DU Jiayuan, et al.The application of geostatistic inversion method to prediction the thin sandstone reservoir[J].Geophysical & Geochemical Exploration, 2011, 35(6):804-808.
[18]
钱玉贵, 叶泰然, 张世华, 等.叠前地质统计学反演技术在复杂储层量化预测中的应用[J].石油与天然气地质, 2013, 34(6):834-840.QIAN Yugui, YE Tairan, ZHANG Shihua, et al.Application of pre-stack geo-statistics inversion techno-logy in quantitative prediction of complex reservoirs[J].Oil & Gas Geology, 2013, 34(6):834-840.
[19]
王香文, 刘红, 滕彬彬, 等.地质统计学反演技术在薄储层预测中的应用[J].石油与天然气地质, 2012, 33(5):730-735.WANG Xiangwen, LIU Hong, TENG Binbin, et al.Application of geostatistical inversion to thin reservoir prediction[J].Oil & Gas Geology, 2012, 33(5):730-735.
[20]
郭同翠, 姜明军, 纪迎章, 等.叠前地质统计学反演在页岩甜点和薄夹层预测中的应用——以西加拿大盆地W区块为例[J].石油地球物理勘探, 2020, 55(1):167-175.GUO Tongcui, JIANG Mingjun, JI Yingzhang, et al.The application of prestack geostatistical in the prediction of shale sweet spots and thin interbeds:a case study of Block W in Western Canada Basin[J].Oil Geophysical Prospecting, 2020, 55(1):167-175.
戴立波, 潘仁芳, 夏丹, 等.AVO技术在裂缝性储层中的应用[J].断块油气田, 2009, 16(5):43-45.DAI Libo, PAN Renfang, XIA Dan, et al.Application of AVO technology in fractured reservoirs[J].Fault-Block Oil & Gas Field, 2009, 16(5):43-45.
[23]
杨敬雅, 李相文, 李磊, 等.一种基于RBF算法的裂缝预测参数自动优化方法与应用[J].复杂油气藏, 2018, 11(4):7-11.YANG Jingya, LI Xiangwen, LI Lei, et al.An automatic optimization method for fracture prediction parameters based on RBF algorithm and its application[J].Complex Hydrocarbon Reservoirs, 2018, 11(4):7-11.
[24]
檀文慧, 巴晶, 符力耘, 等.龙马溪-五峰组富有机质页岩三维岩石物理模板分析及"甜点"预测[J].地球物理学报, 2021, 64(8):2900-2915.TAN Wenhui, BA Jing, FU Liyun, et al.3D rock physics template analysis and "sweet spot" prediction of Longmaxi-Wufeng organic-rich shale[J].Chinese Journal of Geophysics, 2021, 64(8):2900-2915.
[25]
赖富强, 罗涵, 龚大建, 等.一种新的页岩气储层脆性指数评价模型研究——以贵州下寒武统牛蹄塘组页岩储层为例[J].地球物理学进展, 2018, 33(6):2358-2367.LAI Fuqiang, LUO Han, GONG Dajian, et al.New evaluation model for brittle index of shale reservoir:a case study of Niutitang formation shale reservoir in Guizhou province[J].Progress in Geophysics, 2018, 33(6):2358-2367.
