Lithologic Reservoirs ›› 2025, Vol. 37 ›› Issue (3): 95-107.doi: 10.12108/yxyqc.20250309
• PETROLEUM EXPLORATION • Previous Articles
ZHANG Zhaohui1,2, ZHANG Jiaosheng3, LIU Jungang3, ZOU Jiandong3, ZHANG Jianwu3, LIAO Jianbo4, LI Zhiyong4, ZHAO Wenwen1
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[1] MIALL A D. Reconstructing the architecture and sequence stratigraphy of the preserved fluvial record as a tool for reservoir development:A reality check[J]. AAPG Bulletin,2006,90(7):989-1002. [2] MIALL A D. Fluvial depositional systems[M]. Berlin:Springer, 2014:322. [3] 张昌民,王绪龙,朱锐,等.准噶尔盆地玛湖凹陷百口泉组岩石相划分[J].新疆石油地质,2016,37(5):606-614. ZHANG Changmin,WANG Xulong,ZHU Rui,et al. Litho-facies classification of Baikouquan Formation in Mahu Sag,Junggar Basin[J]. Xinjiang Petroleum Geology,2016,37(5):606-614. [4] 刘君龙,刘忠群,肖开华,等.致密砂岩有利岩石相表征及油气地质意义:以四川盆地新场地区三叠系须家河组二段为例[J].石油勘探与开发,2020,47(6):1111-1121. LIU Junlong,LIU Zhongqun,XIAO Kaihua,et al. Characterization of favorable lithofacies in tight sandstone reservoirs and its significance for gas exploration and exploitation:A case study of the 2nd member of Triassic Xujiahe Formation in the Xinchang area,Sichuan Basin[J]. Petroleum Exploration and Development,2020,47(6):1111-1121. [5] 柴毓,王贵文.致密砂岩储层岩石物理相分类与优质储层预测:以川中安岳地区须二段储层为例[J].岩性油气藏,2016, 28(3):74-85. CHAI Yu,WANG Guiwen. Petrophysical facies classification of tight sandstone reservoir and high-quality reservoir prediction:A case study from the second member of Xujiahe Formation in Anyue area,central Sichuan Basin[J]. Lithologic reservoirs,2016, 28(3):74-85. [6] 赖锦,王贵文,王书南,等.碎屑岩储层成岩相测井识别方法综述及研究进展[J]. 中南大学学报(自然科学版),2013,44(12):4942-4953. LAI Jin,WANG Guiwen,WANG Shunan,et al. Overview and research progress in logging recognition method of clastic reservoir diagenetic facies[J]. Journal of Central South University (Science and Technology),2013,44(12):4942-4953. [7] 张华,叶青,郇金来,等.基于成分指示因子的复杂岩相识别:以南海宝岛凹陷深水深层低渗气藏为例[J].海洋地质前沿, 2024,40(7):87-95. ZHANG Hua,YE Qing,HUAN Jinlai,et al. Identification of complex lithofacies based on compositional indicators:A case study of deep-water low-permeability gas reservoir in Baodao Sag,South China Sea[J]. Marine Geology Frontiers,2024,40(7):87-95. [8] 田明智,朱超,李森明,等.湖相碳酸盐岩测井岩相识别技术与应用:以柴达木盆地英西地区为例[J].中国石油勘探,2023, 28(1):135-143. TIAN Mingzhi,ZHU Chao,LI Senming,et al. Application of logging lithofacies identification technology of lacustrine carbonate rocks:A case study of Yingxi area,Qaidam Basin[J]. China Petroleum Exploration,2023,28(1):135-143. [9] 刘跃杰,刘书强,马强,等. BP神经网络法在三塘湖盆地芦草沟组页岩岩相识别中的应用[J].岩性油气藏,2019,31(4):101-111. LIU Yuejie,LIU Shuqiang,MA Qiang,et al. Application of BP neutral network method to identification of shale lithofacies of Lucaogou Formation in Santanghu Basin[J]. Lithologic Reservoirs,2019,31(4):101-111. [10] 武中原,张欣,张春雷,等.基于LSTM循环神经网络的岩性识别方法[J].岩性油气藏,2021,33(3):120-128. WU Zhongyuan,ZHAGN Xin,ZHANG Chunlei,et al. Lithology identification based on LSTM recurrent neural network[J]. Lithologic Reservoirs,2021,33(3):120-128. [11] HUANG Weilin,GAO Fei,LIAO Jianping,et al. A deep learning network for estimation of seismic local slopes[J]. Petroleum Science,2021,18:92-105. [12] DONG Shaoqun,ZENG Lianbo,DU Xiangyi,et al. Lithofacies identification in carbonate reservoirs by multiple kernel Fisher discriminant analysis using conventional well logs:A case study in A oilfield,Zagros Basin,Iraq[J]. Journal of Petroleum Science and Engineering,2022,210:110081. [13] HOU Xianmu,LIAN Peiqing,ZHAO Jiuyu,et al. Identification of carbonate sedimentary facies from well logs with machine learning[J]. Petroleum Research,2024,9:165-175. [14] 邵晓州,王苗苗,齐亚林,等.鄂尔多斯盆地平凉北地区长8油藏特征及成藏主控因素[J].岩性油气藏,2021,33(6):59-69. SHAO Xiaozhou,WANG Miaomiao,QI Yalin,et al. Characteristics and main controlling factors of Chang 8 reservoir in northern Pingliang area,Ordos Basin[J]. Lithologic Reservoirs,2021,33(6):59-69. [15] 周勇,徐黎明,纪友亮,等.致密砂岩相对高渗储层特征及分布控制因素:以鄂尔多斯盆地陇东地区延长组长82为例[J]. 中国矿业大学学报,2017,46(1):106-120. ZHOU Yong,XU Liming,JI Youliang,et al. Characteristics and distributing controlling factors of relatively high permeability reservoir:A case study from Chang 82 sandstones of Yanchang formation in Longdong area,Ordos basin[J]. Journal of China University of Mining & Technology,2017,46(1):106-120. [16] 陈世加,雷俊杰,刘春,等.鄂尔多斯盆地姬塬-吴起地区三叠系延长组长6段成藏控制因素[J].石油勘探与开发,2019, 46(2):241-253. CHEN Shijia,LEI Junjie,LIU Chun,et al. Factors controlling the reservoir accumulation of Triassic Chang 6 member in JiyuanWuqi area,Ordos Basin,NW China[J]. Petroleum Exploration and Development,2019,46(2):241-253. [17] 朱如凯,白斌,袁选俊,等.利用数字露头模型技术对曲流河三角洲沉积储层特征的研究[J].沉积学报,2013,31(5):867-877. ZHU Rukai,BAI Bin,YUAN Xuanjun,et al. A new approach for outcrop characterization and geostatistical analysis of meandering Channels sandbodies within a delta plain setting using digital outcrop models:Upper Triassic Yanchang tight sandstone formation,Yanhe outcrop,Ordos Basin[J]. Acta Sedimentologica Sinica,2013,31(5):867-877. [18] 刘桂珍,高伟,张丹丹,等.姬塬地区长81亚油层组浅水型三角洲砂体结构及成因[J].岩性油气藏,2019,31(2):16-23. LIU Guizhen,GAO Wei,ZHANG Dandan,et al. Sandbody structure and its genesis of shallow-water delta of Chang 81 reservoir in Jiyuan area,Ordos Basin[J]. Lithologic Reservoirs,2019, 31(2):16-23. [19] ZHANG Zhaohui,LI Zhiyong,DENG Xiuqin,et al. Multiparameters logging identifying method for sand body architectures of tight sandstones:A case study of the Triassic Chang 9 member,Longdong area,Ordos Basin,NW China[J]. Journal of Petroleum Science and Engineering,2022,216:110824. [20] 刘昊伟,王键,刘群明,等.鄂尔多斯盆地姬塬地区上三叠统延长组长8油层组有利储集层分布及控制因素[J].古地理学报,2012,14(3):285-294. LIU Haowei,WANG Jian,LIU Qunming,et al. Favorable reservoir distribution and its controlling factors of the Chang 8 interval of Upper Triassic Yanchang Formation in Jiyuan area,Ordos Basin[J]. Journal of Palaeogeography,2012,14(3):285-294. [21] 姚泾利,楚美娟,白嫦娥,等.鄂尔多斯盆地延长组长82小层厚层砂体沉积特征及成因分析[J].岩性油气藏,2014,26(6):40-45. YAO Jingli,CHU Meijuan,BAI Change,et al. Sedimentary characteristics and genesis of thick layer sand body of Chang 82 sublayer in Ordos Basin[J]. Lithologic Reservoirs,2014,26(6):40-45. [22] 刘化清,李相博,完颜容,等.鄂尔多斯盆地长8油层组古地理环境与沉积特征[J].沉积学报,2011,29(6):1086-1095. LIU Huaqing,LI Xiangbo,WANYAN Rong,et al. Palaeogeographic and sedimentological characteristics of the Triassic Chang 8,Ordos Basin,China[J]. Acta Sedimentologica Sinica,2011, 29(6):1086-1095. [23] 黄彦庆,刘忠群,王爱,等.四川盆地元坝地区上三叠统须家河组三段致密砂岩气甜点类型与分布[J].岩性油气藏,2023, 35(2):21-30. HUANG Yanqing,LIU Zhongqun,WANG Ai,et al. Types and distribution of tight sandstone gas sweet spots of the third member of Upper Triassic Xujiahe Formation in Yuanba area,Sichuan Basin[J]. Lithologic Reservoirs,2023,35(2):21-30. [24] 刘翰林,邱镇,徐黎明,等.鄂尔多斯盆地陇东地区三叠系延长组浅水三角洲砂体特征及厚层砂体成因[J].石油勘探与开发,2021,48(1):106-117. LIU Hanlin,QIU Zhen,XU Liming,et al. Distribution of shallow water delta sand bodies and the genesis of thick layer sand bodies of the Triassic Yanchang Formation,Longdong Area,Ordos Basin[J]. Petroleum Exploration and Development,2021,48(1):106- 116. [25] 牟蜚声,尹相东,胡琮,等.鄂尔多斯盆地陕北地区三叠系长7段致密油分布特征及控制因素[J].岩性油气藏,2024,36(4):71-84. MOU Feisheng,YIN Xiangdong,HU Cong,et al. Distribution characteristics and controlling factors of tight oil of Triassic Chang 7 member in northern Shaanxi area,Ordos Basin[J]. Lithologic Reservoirs,2024,36(4):71-84. [26] 米伟伟,谢小飞,曹红霞,等.鄂尔多斯盆地东南部二叠系山2- 盒8段致密砂岩储层特征及主控因素[J].岩性油气藏,2022, 34(6):101-117. MI Weiwei,XIE Xiaofei,CAO Hongxia,et al. Characteristics and main controlling factors of tight sandstone reservoirs of Permian Shan 2 to He 8 members in southeastern Ordos Basin[J]. Lithologic Reservoirs,2022,34(6):101-117. [27] 闫雪莹,桑琴,蒋裕强,等.四川盆地公山庙西地区侏罗系大安寨段致密油储层特征及高产主控因素素[J].岩性油气藏, 2024,36(6):98-109. YAN Xueying,SANG Qin,JIANG Yuqiang,et al. Main controlling factors for the high yield of tight oil in the Jurassic Da'anzhai Section in the western area of Gongshanmiao,Sichuan Basin[J]. Lithologic Reservoirs,2024,36(6):98-109. [28] 刘芬,朱筱敏,李洋,等.鄂尔多斯盆地西南部延长组重力流沉积特征及相模式[J].石油勘探与开发,2015,42(5):577-588. LIU Fen,ZHU Xiaomin,LI Yang,et al. Sedimentary characteristics and facies model of gravity flow deposits of Late Triassic Yanchang Formation in southwestern Ordos Basin,NW China[J]. Petroleum Exploration and Development,2015,42(5):577-588. [29] 李士祥,楚美娟,黄锦绣,等.鄂尔多斯盆地延长组长8油层组砂体结构特征及成因机理[J].石油学报,2013,34(3):435-444. LI Shixiang,CHU Meijuan,HUANG Jinxiu,et al. Characteristics and genetic mechanism of sandbody architecture in Chang- 8 oil layer of Yanchang Formation,Ordos Basin[J]. Acta Petrolei Sinica,2013,34(3):435-444. [30] 马瑶,史涛,王冠男,等.陇东地区长82砂体结构特征及成因模式[J].西北大学学报(自然科学版),2019,49(5):765-771. MA Yao,SHI Tao,WANG Guannan,et al. Sandbody structural characteristics and genetic model of Chang 82 in Longdong area[J]. Journal of Northwest University(Natural Science Edition), 2019,49(5):765-771. [31] 测井学编写组.测井学[M].北京:石油工业出版社,1998. Logging science writing group. Logging[M]. Beijing:Petroleum Industry Press,1998. [32] 李宁,徐彬森,武宏亮,等. 人工智能在测井地层评价中的应用现状及前景[J].石油学报,2021,42(4):508-522. LI Ning,XU Bingsen,WU Hongliang,et al. Application status and prospects of artificial intelligence in well logging and formation evaluation[J]. Acta Petrolei Sinica,2021,42(4):508-522. [33] 董少群,曾联波,车小花,等.人工智能在致密储层裂缝测井识别中的应用[J].地球科学,2023,48(7):2443-2461. DONG Shaoqun,ZENG Lianbo,CHE Xiaohua,et al. Application of artificial intelligence in fracture identification using well logs in tight reservoirs[J]. Earth Science,2023,48(7):2443-2461. [34] 王贵文,邓清平,唐为清.测井曲线谱分析方法及其在沉积旋回研究中的应用[J].石油勘探与开发,2002,29(1):93-95. WANG Guiwen,DENG Qingping,TANG Weiqing. The application of spectral analysis of logs in depositional cycle studies[J]. Petroleum Exploration and Development,2002,29(1):93-95. [35] JIANG Shiyi,SUN Panke,LYU Fengqing,et al. Machine learning(ML)for fluvial lithofacies identification from well logs:A hybrid classification model integrating lithofacies characteristics,logging data distributions,and ML models applicability[J]. Geoenergy Science and Engineering,2024,233:212587. [36] TIAN Miao,OMRE Henning,XU Huaimin. Inversion of well logs into lithology classes accounting for spatial dependencies by using hidden markov models and recurrent neural networks[J]. Journal of Petroleum Science and Engineering,2021,196:107598. [37] LUBO-ROBLES D,BEDLE H,MARFURT K J,et al. Evaluation of principal component analysis for seismic attribute selection and self-organizing maps for seismic facies discrimination in the presence of gas hydrates[J]. Marine and Petroleum Geology,2023,150:106097. [38] REN Quan,ZHANG Hongbing,ZHANG Dailu,et al. Lithology identification using principal component analysis and particle swarm optimization fuzzy decision tree[J]. Journal of Petroleum Science and Engineering,2023,220:111233. [39] CHEN Tianqi,GUESTRIN C. XGBoost:A scalable tree Boosting system[J]. CoRR,2016,1603:785-794. [40] DOU Jie,YUNUS A P,BUI D T,et al. Assessment of advanced random forest and decision tree algorithms for modeling rainfallinduced landslide susceptibility in the Izu-Oshima Volcanic Island,Japan[J]. Science of the Total Environment,2019,662:332-346. [41] YAN Tie,XU Rui,SUN Shihui,et al. A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm[J]. Petroleum Science,2024, 21:1135-1148. [42] AZARHOOSH M J,KOOHMISHI M. Prediction of hydraulic conductivity of porous granular media by establishment of random forest algorithm[J]. Construction and Building Materials, 2023,366:130065. [43] 黄莉莎,闫建平,郭伟,等.基于随机森林回归算法的低电阻率页岩气储层饱和度评价[J].测井技术,2023,47(1):22-28. HUANG Lisha,YAN Jianping,GUO Wei,et al. Evaluation of Low resistivity shale gas reservoir saturation based on random forest regression method[J]. Well Logging Technology,2023, 47(1):22-28. [44] DONG Shaoqun,SUN Yanming,XU Tao,et al. How to improve machine learning models for lithofacies identification by practical and novel ensemble strategy and principles[J]. Petroleum Science,2023,20:733-752. [45] MARKOVIC S,BRYAN J L,REZAEE R,et al. Application of XGBoost model for in-situ water saturation determination in Canadian oil-sands by LF-NMR and density data[J]. Scientific Reports,2022,12(1):13984. [46] SUN Hao,LUO Qiang,XIA Zhaohui,et al. Bottomhole pressure prediction of carbonate reservoirs using XGBoost[J]. Processes,2024,12(1):125. |
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