China Petroleum Exploration ›› 2026, Vol. 31 ›› Issue (1): 193-204.DOI: 10.3969/j.issn.1672-7703.2026.01.014
Previous Articles Next Articles
Yu Chunhao, Cheng Daojie, Liu Jie, Cui Shitao, Ren Guohui
Online:2026-01-15
Published:2026-01-15
CLC Number:
Yu Chunhao, Cheng Daojie, Liu Jie, Cui Shitao, Ren Guohui. Progress of Well Logging Technology of CNPC during the “14th Five–Year Plan” period and development directions in the “15th Five-Year Plan”[J]. China Petroleum Exploration, 2026, 31(1): 193-204.
Add to citation manager EndNote|Ris|BibTeX
URL: http://www2.cped.cn/EN/10.3969/j.issn.1672-7703.2026.01.014
| [1] 王小宁. 地层评价与测井技术新进展:第62 届SPWLA 年会综述[J].测井技术,2021,45(05) Wang Xiaoning. Advances in Formation Evaluation and Well Logging Technology: Overview of the SPWLA 62nd Annual Logging Symposium[J]. Well Logging Technology ,2021,45(05) [2] 王小宁, 陈文辉, 杜雪威等. 地层评价与测井技术新进展:第63 届SPWLA 年会综述[J]. 测井技术. 2023(03) Wang Xiaoning Chen Wenhui, et al. Advances in Formation Evaluation and Well Logging Technology:Overview of the SPWLA 63rd Annual Logging Symposium [J]. Well Logging Technology . 2023(03) [3] 徐红军, 李潮流, 袁超, 等. 地层评价与测井技术新进展: 第64 届SPWLA 年会综述[J]. 测井技术,2023,47(05) Xu Hongjun, Li Chaoliu, et al. Advances in Formation Evaluation and Well Logging Technology:Overview of the SPWLA 64th Annual Logging Symposium [J]. Well Logging Technology,2023,47(05) [4] BIRKEDAL K A,DATIR H,ZHANG T H.A method to identify vertical reservoir communication by combining borehole sonic and high-frequency electrical imaging data[C]//SPWLA 64th Annual Logging Symposium,Conroe,Texas,USA,2023. [5] AHMAD S,WAAGE H,MIRZA D,et al.A machinelearning approach performed on new technology for images in oil-based mud for advanced electrofacies analysis:a cased study from the Norwegian Sea[C]//SPWLA 64th Annual Logging Symposium,Conroe,Texas,USA,2023. [6] IJASAN O.Learning from impact and implications of signal-tonoise in NMR T1-T2 logging of unconventional reservoirs[C]//SPWLA 64th Annual Logging Symposium,Conroe,Texas,USA,2023. [7] DICK M J,KENNEY T,VESELINOVIC D,et al.Multi field evaluation of T2 pore-size distribution and T1-T2 2Dmaps[C]//SPWLA 64 th Annual Logging Symposium,Conroe,Texas,USA,2023. [8] WU H H, CULL A, PAN L, et al. A new generation of LWD geosteering electromagnetic resistivity tool providing multilayered bed boundary detection, anisotropy determination, and azimuthal resistivity measurements for accurate well placement and formation evaluation[C]//SPWLA 63rd Annual Logging Symosium, Stavanger,Norway, 2022. [ 9 ] XIEH,SUNKL,MIRTOE, et al. Anadvanced ultrahighdefinition directional electromagnetic propagation logging tool for mapping while drilling and multilayered formation evaluation[C]//SPWLA 63rd Annual Logging Symosium, Stavanger, Norway, 2022. [ 1 0 ] SAKAIDAS, ZHUD,HILLAD .Development of comprehensive and efficient DTS interpretation method for fracture diagnosis[C]//SPWLA 63rd Annual Logging Symosium,Stavanger, Norway, 2022. [11] MENDOZA A, CERRAHO?LU ? , DELFINO A, et al. Signal processing and machine learning for effective integration of distributed fiber opticsensing data in production petrophysics[C]//SPWLA 63 rd Annual Logging Symosium,Stavanger, Norway, 2022. [12] MCDONALD A. Impact of missing data on petrophysical regression-based machine learning model performance[C]//SPWLA 63rd Annual Logging Symosium, Stavanger,Norway,2022. [13] KRISHNARAJ N, MYERS M, ARAD A, et al. Joint inversion and unsupervised learning applied to NMR data processing that eliminates the need for regularization[C]//SPWLA 63rd Annual Logging Symosium, Stavanger,Norway, 2022. [14] ABBASI J, ZHAO J Y, AHMED S, et al. Machine learning assisted prediction of permeability of tight sandstones from mercury injection capillary pressure tests[C]//SPWLA 63rd Annual Logging Symosium, Stavanger,Norway, 2022. [15] RAHEEM O,PAN W,TORRES-VERDíN C,et al.Best practices in automatic permeability estimation:machinelearning methods vs conventional petrophysical models[C]//SPWLA 64th Annual Logging Symposium,Conroe,Texas,USA,2023. [16] WESTENG K,CROMBRUGGE Y V,LEHRE C N,et al.Robust and automatic shale volume interpretation using adaptive lithological thresholds built on depth trends,statistics,and geological units[C]//SPWLA 64th Annual Logging Symposium,Conroe,Texas,USA,2023. [17] ALSULAMI G,MA S X.AI driven image based digital twin rock properties:fast,consistent,and cost effective[C]//SPWLA 64th Annual Logging Symposium,Conroe,Texas,USA,2023. [18] 王东宇, 张崇儒, 王晓冬等. 测井仪器传热理论研究及仿真试验分析[J]. 测井技术,2024,48(01):19-26 Wang Dongyu, Zhang Chongru, et al. Theoretical Research and Simulation Experiment Analysis on Heat Transfer of Logging Tools[J]. Well Logging Technology, 2024,48(01):19-26 [19]《中国石油测井简史》编委会,2022. 中国石油测井简史[M]. 北京:石油工业出版社:255-256. Editorial Board of A Brief History of Petroleum Well Logging in China. (2022). A brief history of petroleum well logging in China. Petroleum Industry Press. pp. 255-256. [20] 陈龙川, 张兆谦, 郑建东等. 核磁共振测井在古龙页岩油评价中的应用[J]. 测井技术,2024,48(01):110-116. Chen Longchuan, Zhang Zhaoqian, Zheng Jiandong, et al.“Application of Nuclear Magnetic Resonance Logging in Evaluation of Gulong Shale Oil.” Well Logging Technology, vol. 48, no. 1, 2024, pp. 110–116. [21] 吴柏志, 许孝凯, 杜群杰等. 声波远场三维成像测井技术及应用[J].应用声学,2024,43(06):1341-1349. Wu Baizhi, Xu Xiaokai, Du Qunjie, et al. “Acoustic Far-Field 3D Imaging Logging Technology and Its Application.” Applied Acoustics, vol. 43, no. 6, 2024, pp. 1341–1349. [22] 朱万里, 陈涛, 侯学理等. 加权数字相敏检波算法在核磁共振测井数据采集中的应用[J]. 测井技术,2020,44(06):543-547. Zhu Wanli, Chen Tao, Hou Xueli, et al. “Application of Weighted Digital Phase-Sensitive Detection Algorithm in Nuclear Magnetic Resonance Logging Data Acquisition.” Well Logging Technology, vol. 44, no. 6, 2020, pp. 543–547. [23] 陈国军, 张啸, 高明等. 超深油气井核磁共振测井影响分析及谱形态校正[J]. 测井技术,2023,47(04):457-461. Chen Guojun, Zhang Xiao, Gao Ming, et al. “Influence Analysis and Spectral Shape Correction of Nuclear Magnetic Resonance Logging in Ultra-Deep Oil and Gas Wells.” Well Logging Technology, vol. 47, no. 4, 2023, pp. 457–461. [24] 赵培强, 陈阵, 李卫兵等. 基于介电测井和电阻率测井的致密砂岩储层饱和度联合反演方法[J]. 测井技术,2022,46(02):174-181. Zhao Peiqiang, Chen Zhen, Li Weibing, et al. “Joint Inversion Method for Tight Sandstone Reservoir Saturation Based on Dielectric Logging and Resistivity Logging.” Well Logging Technology, vol. 46, no. 2, 2022, pp. 174–181. [25] 王忠良, 徐文远, 王文泽等. 结合伽马成像技术的三维地质建模在页岩油地质导向中的应用[J]. 西安石油大学学报(自然科学版),2024, 39(2): 112-119. WANG Zhongliang, XU Wenyuan, WANG Wenze, et al. Application of 3D Geological Modeling Combined with Gamma Imaging Technology to Geosteering of Shale Oil Reservoir[J]. Journal of Xi’an Shiyou University (Natural Science Edition),2024, 39(2): 112-119.. [26] 唐章宏, 阳质量, 陈刚, 等. 方位侧向电阻率成像随钻测井仪软聚焦仿真分析[J]. 测井技术, 2024, 48(2): 135-141. Tang Zhanghong, Yang Zhiliang, Chen Gang, et al. Simulation analysis of soft focusing for azimuthal laterolog resistivity imaging while drilling tool. Well Logging Technology, 2024,48(2), 135-141. [27]Amr Serry, Shafiq Ahmed, Owais Amee, et al. Production Sustainability of a Challenging Heterogeneous, Mature Carbonate Reservoir: An Integrated Solution Comprising Near and Far-Field LWD Measurements[C]//SPWLA 65th Annual Logging Symposium. Rio de Janeiro, Brazil: Society of Petrophysicists and Well Log Analysts, 2024. [28] 刘合等, 基于光纤监测的分段压裂多簇均衡性评价与优化建议, 钻采工艺, 2024,47 (06). Liu He, et al. Evaluation and Optimization Suggestions for Multi-Cluster Uniformity in Staged Fracturing Based on Fiber Optic Monitoring, Drilling & Production Technology, 2024,47 (06). [29] 刘合等, 光纤传感技术在油气田开发中的应用, 石油物探, 2024,63(04). Liu He, et al. Application of Fiber Optic Sensing Technology in Oil and Gas Field Development. Geophysical Prospecting for Petroleum, 2024,63 (04). [30] 何祖源等, 光纤分布式声波传感器原理与应用, 激光与光电子学进展,2021,58 (13). He Zuyuan, et al. Principle and Application of Fiber Optic Distributed Acoustic Sensors. Laser & Optoelectronics Progress,2021,58 (13). [31] 石玉江, 张哲豪, 赵建斌, 等.“核磁+”页岩油实验技术体系及应用[J].石油实验地质,2025,47(04):872-881. Shi Yujiang, Zhang Zhehao, Zhao Jianbin, et al. “NMR+”Experimental Technology System for Shale Oil and Its Application[J]. Petroleum Geology & Experiment, 2025, 47(04):872-881. [32] 石玉江, 赵建斌, 肖占山, 等. 基于复电阻率实验测量的页岩电性频散特征及影响规律分析[J]. 地球物理学进展,2025,40(03):1096-1104. Shi Yujiang, Zhao Jianbin, Xiao Zhanshan, et al. Analysis of Electrical Dispersion Characteristics and Influencing Factors in Shale Based on Complex Resistivity Experimental Measurements[J]. Progress in Geophysics, 2025, 40(03): 1096-1104. [33] 石玉江, 蔡文渊, 刘国强, 等. 页岩油储层孔隙流体的全直径岩心二维核磁共振图谱特征及评价方法[J].中国石油勘探,2023,28(03):132-144. Shi Yujiang, Cai Wenyuan, Liu Guoqiang, et al. Characteristics and Evaluation Method of 2D NMR Spectra for Pore Fluids in Whole-Core Shale Oil Reservoirs[J]. China Petroleum Exploration, 2023, 28(03): 132-144. [34] 周军, 石玉江, 张娟, 等. 统一测井数据库建设与应用[J]. 测井技术,2022,46(06):757-761 Zhou Jun, Shi Yujiang, Zhang Juan, et al. Construction and Application of a Unified Logging Database[J]. Well Logging Technology, 2022, 46(06): 757-761. [35] 杨耀忠, 谭绍泉, 孙业恒, 穆星, 马承杰, 刘建涛. 油气勘探开发综合研究数字平台建设及应用[J]. 油气藏评价与开发,2021,11(4):628-634. Yang Yaozhong, Tan Shaoquan, Sun Yeheng, Mu Xing, Ma Chengjie, Liu Jiantao. Construction and Application of an Integrated Digital Platform for Oil and Gas Exploration and Development Research [J]. Reservoir Evaluation and Development, 2021, 11(4): 628-634. [36] 程希, 任战利. 人工智能测井: 基础、原理、技术及应用[J]. 煤田地质与勘探,2024,52(8):145-164 Cheng Xi, Ren Zhanli. Artificial intelligence logging: Fundamental, principle, technique, and application[J]. Coal Geology& Exploration,2024,52(8):145-164 [37]Shao, R., Xiao, L., Liao, G., Luo, S., Luo, G., Zhou, J., Zhou, J., Li, G., 2023b.Generative adversarial networks based forward-inverse method for geophysical logging. In: SPWLA Annual Logging Symposium, Vol. Day 5 Wed, June 14, 2023 [38] 邵蓉波, 肖立志, 廖广志等. 基于迁移学习的地球物理测井储层参数预测方法研究, 地球物理学报, .2022,65(2):796-808 Shao R B,Xiao l Z,Liao G Z, et al. A reservoir parameters prediction method for geophysical logs based on transferlearning.Chinese J. Geophys,(in Chinese), 2022. 65(2):796-808 [39] 石玉江, 刘国强, 钟吉彬, 等. 基于大数据的测井智能解释系统开发与应用[J]. 中国石油勘探,2021,26(02):113-126. Shi Yujiang, Liu Guoqiang, Zhong Jibin, et al. Development and Application of an Intelligent Logging Interpretation System Based on Big Data[J]. China Petroleum Exploration, 2021,26(02): 113-126. [40] 程希, 周军, 傅海成, 等. 机器学习算法在地球物理测井中的适用性及应用[J]. 西北地质,2023,56(04):336-348. Cheng Xi, Zhou Jun, Fu Haicheng, et al. Applicability and Application of Machine Learning Algorithms in Geophysical Logging[J]. Northwestern Geology, 2023, 56(04): 336-348. [41] 武宏亮, 赖强, 冯周, 等. 深层- 超深层碳酸盐岩储层测井评价关键技术进展[J]. 地球科学,2025,50(07):2844-2860. Wu Hongliang, Lai Qiang, Feng Zhou, et al. Key Technological Advances in Logging Evaluation of Deep-Ultra-Deep Carbonate Reservoirs[J]. Earth Science, 2025, 50(07): 2844-2860. [42] 沈永进. 沈建国. 用井中的共振面波识别地层连通裂缝[C]. 第七届油气地球物理学会年会论文集. Shen Yongjin, Shen Jianguo. Identification of formation-connected fractures using resonance surface waves in wells [C]. Proceedings of the 7th Annual Conference of Petroleum Geophysics Society. [43] 孙学凯, 余春昊, 张浩, 等. 声波测井多尺度成像方法在压裂效果评价中的综合应用[J]. 测井技术,2024,48(02):157-162. Sun Xuekai, Yu Chunhao, Zhang Hao, et al. Comprehensive application of acoustic logging multi-scale imaging methods in fracturing effect evaluation [J]. Well Logging Technology, 2024,48(02): 157-162. [44] 石玉江, 甘仁忠, 蔺敬旗, 等. 准噶尔盆地南缘超深层致密碎屑岩储层油气高产机理与潜力[J]. 中国石油勘探,2025,30(01):82-97. Shi Yujiang, Gan Renzhong, Lin Jingqi, et al. High-Yield Mechanism and Potential of Ultra-Deep Tight Clastic Reservoirs in the Southern Margin of the Junggar Basin[J]. China Petroleum Exploration, 2025, 30(01): 82-97. [45] 石玉江, 刘堂晏, 肖飞, 等. 应用核磁测井与常规测井联合反演确定饱和度的新算法[J]. 石油地球物理勘探,2025,60(05):1214-1223 Shi Yujiang, Liu Tangyan, Xiao Fei, et al. A New Algorithm for Determining Saturation Using Joint Inversion of NMR Logging and Conventional Logging[J]. Oil Geophysical Prospecting,2025, 60(05): 1214-1223. [46] 石玉江, 张凤生, 李庆峰, 等. 页岩油全生命周期测井技术进展与发展方向[J]. 测井技术,2022,46(06):643-650 Shi Yujiang, Zhang Fengsheng, Li Qingfeng, et al. Advances and Development Directions of Logging Technology for the Full Life Cycle of Shale Oil[J]. Well Logging Technology, 2022, 46(06):643-650. [47] 李思亦, 陈文辉, 孙学凯, 等. 基于阵列声波测井的地层压裂效果评价方法[J]. 测井技术,2025,49(04) Li Siyi, Chen Wenhui, Sun Xuekai, et al. Fracturing Effectiveness Evaluation Method Based on Array Acoustic Logging[J]. Well Logging Technology, 2025, 49(04). [48] 任大忠, 邵宇宾, 岳爱忠, 等. 深海测井技术装备现状、挑战与发展对策[J/OL]. 地球物理学进展:1-10 Ren Dazhong, Shao Yubin, Yue Aizhong, et al. Status, Challenges, and Development Strategies of Deep-Sea Logging Technology and Equipment[J/OL]. Progress in Geophysics:1-10. |
| [1] | Wu Keqiang, Fan Caiwei, You Junjun, Chen Lin, Man Xiao, Tan Jiancai. Exploration advances and development directions of hydrocarbons in the Beibuwan Basin during the 14th Five-Year Plan period [J]. China Petroleum Exploration, 2026, 31(1): 100-115. |
| [2] | Liu Jun, Peng Guangrong, Lin Heming, Zhang Xiangtao, Liu Jie, Liu Daoli. Progress and Development Direction of Oil and Gas Exploration in the Eastern Pearl River Mouth Basin during the 14th Five-Year Plan Period [J]. China Petroleum Exploration, 2026, 31(1): 116-130. |
| [3] | Guo Xusheng, Zhang Yu, Liu Chaoying, Li Meng, Liu Shilin, Shen Baojian. Theoretical and technological progress, challenges, and development directions of oil and gas exploration of Sinopec during the 14th Five-Year Plan period [J]. China Petroleum Exploration, 2025, 30(1): 1-14. |
| [4] | Wu Guohai, Hu Xin, Guo Zhenhua, Ni Guohui, Jiang Ren, Yang Yuanqi, Wang Kun. Important role of seismic data in gas reservoir logging interpretation and evaluation: a case study of M Gas Field in Siberian Basin [J]. China Petroleum Exploration, 2024, 29(2): 147-157. |
| [5] | Liu Zixiong, Zhang Jing, Zhou Zihui, Guo Bumin , Li Xinfa , Chen Ling. Research on fracturing results evaluation method based on construction curve of tight sandstone gas reservoir [J]. China Petroleum Exploration, 2024, 29(1): 177-182. |
| [6] | Wang Haige, Huang Hongchun, Ji Guodong, Chen Changchang, Lv Zehao, Chen Weifeng, Bi Wenxin, Liu Li. Progress and challenges of drilling and completion technologies for deep,ultra-deep and horizontal wells of CNPC [J]. China Petroleum Exploration, 2023, 28(3): 1-11. |
| [7] | Liu Guoqiang, Zhao Xianran, Yuan Chao, Li Shenzhuan, Liu Zhonghua. Logging evaluation of macro-structure of continental shale oil reservoir and sweet spots selection [J]. China Petroleum Exploration, 2023, 28(1): 120-134. |
| [8] | Song Zhenxiang, Zhou Zhuoming, Xu Xuhui, Wang Baohua, Li Hao, Ma Zhongliang, Chen Feiran. Progress of key technologies for oil and gas resource assessment of Sinopec during the 13th Five-Year Plan period and development direction [J]. China Petroleum Exploration, 2022, 27(3): 27-37. |
| [9] | Zhao Bangliu, Yong Xueshan, Gao Jianhu, Chang Dekuan, Yang Cun, Li Haishan. Progress and development direction of PetroChina intelligent seismic processing and interpretation technology [J]. China Petroleum Exploration, 2021, 26(5): 12-23. |
| [10] | Liu Guoqiang. Challenges and countermeasures of well logging data acquisition technology in unconventional petroleum exploration and development [J]. China Petroleum Exploration, 2021, 26(5): 24-37. |
| [11] | Yang Qinyong, Yang Jiangfeng, Wang Xianbin, Zhou Xiaohui, Chen Wei, Li Na. Sinopec: Progress and development direction of geophysical prospecting technology#br# [J]. China Petroleum Exploration, 2021, 26(1): 121-130. |
| [12] | Yang Ping, Zhan Shifan, Li Ming, Li Lei, Guo Rui, Shang Minqiang, Tao Chunfeng. Research and practice on an artificial intelligence seismic interpretation mode based on the E&P Dream Cloud [J]. China Petroleum Exploration, 2020, 25(5): 89-96. |
| [13] | Zhao Lisha, Shi Yongbin, Jin Wei, Li Hua, Ta Siken. Application research on intelligent logging interpretation based on E&P Dream Cloud [J]. China Petroleum Exploration, 2020, 25(5): 97-103. |
| [14] | Liu Henian, Shi Buqing, Xue Liangqing, Wan Lunkun, Pan Xiaohua, Ji Zhifeng, Li Zhi, Ma Hong, Fan Guozhang. Major achievements of CNPC overseas oil and gas exploration during the 13th Five-Year Plan and prospects for the future [J]. China Petroleum Exploration, 2020, 25(4): 1-10. |
| [15] | Li Yang, Xue Zhaojie, Cheng Zhe, Jiang Haijun, Wang Ruyue. Progress and development directions of deep oil and gas exploration and development in China [J]. China Petroleum Exploration, 2020, 25(1): 45-57. |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||