元素扫描测井在煤系烃源岩识别与评价中的应用

王斌; 夏宗立; 张科; 李玲; 王中瑞; 赵飞; 张有鹏; 赖锦

doi:10.19509/j.cnki.dzkq.tb20240386

元素扫描测井在煤系烃源岩识别与评价中的应用

doi: 10.19509/j.cnki.dzkq.tb20240386

王斌^{1, 2, 3,},
夏宗立^{4a, 4b},
张科^{1, 2, 3},
李玲^{1, 2, 3},
王中瑞^{4a, 4b},
赵飞^{4a, 4b},
张有鹏⁵,
赖锦^{4a, 4b, ,}

1.
中国石油天然气集团有限公司超深层复杂油气藏勘探开发技术研发中心，新疆库尔勒 841000
2.
新疆维吾尔自治区超深层复杂油气藏勘探开发工程研究中心，新疆库尔勒 841000
3.
新疆超深油气重点实验室，新疆库尔勒 841000
4a.
中国石油大学（北京）：油气资源与工程国家重点实验室
4b.
中国石油大学（北京）：地球科学学院，北京 102249
5.
中国石油集团测井有限公司测井技术研究院，北京 102206

基金项目: 中国石油天然气集团有限公司科技项目“超深层碎屑岩油气分布规律与区带目标优选”（2023ZZ14YJ02）；中国石油天然气股份有限公司科技专项“塔里木盆地深层碎屑岩重点地区综合地质研究、目标优选、技术攻关与现场试验”（2022KT0201）；国家自然科学基金项目（42072150）；中国石油大学（北京）科研启动基金项目（2462021YXZZ003）；中国石油−中国石油大学（北京）战略合作协议项目（ZLZX2020-01）

详细信息

作者简介:
王斌：E-mail：wangb3-tlm@petrolchina.com.cn

通讯作者:
E-mail：laijin@cup.edu.cn

中图分类号: P631.8
计量
- 文章访问数: 373
- PDF下载量: 17
- 被引次数: 0
出版历程
- 收稿日期: 2024-07-11
- 录用日期: 2024-11-21
- 修回日期: 2024-10-09
- 网络出版日期: 2025-02-26

Application of LithoScanner logging in recognition and evaluation of coaly source rocks

WANG Bin^{1, 2, 3
,},
XIA Zongli^{4a, 4b},
ZHANG Ke^{1, 2, 3},
LI Ling^{1, 2, 3},
WANG Zhongrui^{4a, 4b},
ZHAO Fei^{4a, 4b},
ZHANG Youpeng⁵,
LAI Jin^{4a, 4b
, ,}

1.
Research and Development Center for Ultra-Deep Complex Reservoir Exploration and Development, CNPC, Korla Xinjiang 841000, China
2.
Engineering Research Center for Ultra-deep Complex Reservoir Exploration and Development, Xinjiang Uygur Autonomous Region, Korla Xinjiang 841000, China
3.
Xinjiang Key Laboratory of Ultra-deep Oil and Gas, Korla Xinjiang 841000, China
4a.
State Key Laboratory of Petroleum Resource and Engineering, China University of Petroleum (Beijing)
4b.
College of Geosciences, China University of Petroleum (Beijing), Beijing 102249, China
5.
Logging Technology Research Institute, China National Logging Corporation, Beijing 102206, China

More Information

Author Bio:
E-mail：wangb3-tlm@petrolchina.com.cn

Corresponding author: E-mail：laijin@cup.edu.cn

摘要

摘要:
库车坳陷三叠系、侏罗系发育湖泊相和沼泽相间互沉积的5套烃源岩层系，按岩性可划分出煤、碳质泥岩和暗色泥岩，其烃源岩具有总有机碳（TOC）丰度较高、厚度大、分布范围广等特征。由于烃源岩纵向分布层系多，不同岩性分布及纵向非均质性强，导致常用的ΔlgR（R为测井电阻率）法等在TOC测井定量表征中应用效果较差。为了更好地了解库车坳陷油气资源潜力以及评估油气储量，首先通过岩心等识别了烃源岩岩性特征，进一步通过地球化学分析资料实现烃源岩地质特征评价。将ΔlgR法运用于TOC测井定量评价，然后将元素扫描测井应用于烃源岩岩性的测井识别工作中，并进一步利用元素扫描测井实现TOC测井定量评价。整体上，三叠系、侏罗系有机质类型以Ⅱ₁型、Ⅱ₂型和Ⅲ型为主，有机质演化为成熟阶段，其烃源岩品质为好−优质烃源岩。通过元素扫描测井识别不同岩性烃源岩并进一步定量评价TOC的方法，其精度相比ΔlgR法提升显著。研究成果对库车坳陷油气资源潜力评估有一定指导意义，同时还有利于拓展元素扫描测井资料应用范围。
- 烃源岩 /
- 测井评价 /
- 总有机碳（TOC） /
- 元素扫描测井 /
- 库车坳陷 /
- 煤 /
- 碳质泥岩 /
- 暗色泥岩
Abstract: <p>In the Kuqa Depression, the Triassic and Jurassic periods feature five sets of source rock sequences that developed as alternating lake and swamp facies. These sequences can be classified into coal, carbonaceous mudstone, and dark mudstone based on lithology. The source rocks are characterized by high TOC abundance, significant thickness, and wide distribution. However, due to the vertical distribution of multiple source rock layers and the strong heterogeneity in lithological distribution, conventional methods such as the Δlg<italic>R</italic> method perform poorly in TOC logging quantification. </p></sec><sec><title>Objective and Methods
To better understand the hydrocarbon resource potential and assess reserves in the Kuqa Depression, this study first identified the lithological characteristics of the source rocks through core analysis. Further geological characterization was achieved using geochemical analysis data. The ΔlgR method was initially applied for quantitative TOC logging evaluation, followed by the application of LithoScanner logging for lithological identification of the source rocks. Subsequently, LithoScanner logging was utilized for quantitative TOC evaluation.
Results
Overall, the Triassic and Jurassic source rocks are primarily composed of type Ⅱ₁, Ⅱ₂, and Ⅲ organic matter, with medium to high maturity. The quality of these source rocks ranges from medium to good. The method of using LithoScanner logging to identify different lithological source rocks and quantitatively evaluate TOC demonstrated a significantly higher accuracy compared to the ΔlgR method.
Conclusion
The findings provide valuable guidance for assessing the hydrocarbon resource potential in the Kuqa Depression and expand the application scope of LithoScanner logging data.
- source rock /
- logging evaluation /
- TOC /
- LithoScanner logging /
- Kuqa Depression /
- coal /
- carbonaceous mudstone /
- dark mudstone

HTML全文

图 1 库车坳陷三叠系−侏罗系烃源岩岩性特征图

a. 暗色泥岩，J₂kz（克孜勒努尔组，下同），DB2井，4045.17 m；b. 碳质泥岩，T₃t（塔里奇克组，下同），TD202井，5110.22 m；c. 煤，T₃t，TD202井，5111.85 m

Figure 1. Lithologic characteristics map of Triassic-Jurassic source rocks in Kuqa Depression

下载: 全尺寸图片幻灯片

图 2 库车坳陷三叠系−侏罗系烃源岩HI与T_max关系图

HI. 氢指数；T_max. 最大热解峰温；Ⅱ₁，Ⅱ₂和Ⅲ. 均为有机质类型；下同

Figure 2. Relationship between HI and T_max of Triassic-Jurassic source rocks in Kuqa Depression

下载: 全尺寸图片幻灯片

图 3 库车坳陷三叠系−侏罗系烃源岩品质评价

a. 湖相泥岩；b. 煤系泥岩；c. 煤岩；d. 碳质泥岩；P_g. 生烃潜量；w（TOC）. 总有机碳质量分数；J₂q. 中侏罗统恰克马克组；T₃h. 上三叠统黄山组；T₃t. 上三叠统塔里奇克组；下同

Figure 3. Quality evaluation of Triassic-Jurassic source rocks in Kuqa Depression

下载: 全尺寸图片幻灯片

图 4 库车坳陷DB501井侏罗系克孜勒努尔组暗色泥岩(a)、碳质泥岩(b)和煤(c)常规−成像−元素扫描测井响应

BIT. 钻头直径；CAL. 井径；GR. 自然伽马；MLR4C. 深电阻率；MLR3C. 中电阻率；MLR2C. 浅电阻率；CNC. 中子；DEN. 密度；DT. 声波时差；1 in=2.54 cm；下同

Figure 4. Conventional-image logging-LithoScanner logging responses of dark mudstones (a), canbonferious mudstones (b) and coal (c) of Jurassic Kezilenuer Formation of Well DB501 in Kuqa Depression

下载: 全尺寸图片幻灯片

图 5 基于ΔlgR法与岩性扫描测井的库车坳陷烃源岩TOC 测井定量评价（DB501 井）

w（TC），w（TIC）. 分别为总碳质量分数和无机碳质量分数

Figure 5. TOC content evaluation of source rocks in Kuqa Depression using ΔlgR method and LithoScanner logging

下载: 全尺寸图片幻灯片

图 6 岩心实测w（TOC）与ΔlgR法计算w（TOC）(a)、元素扫描测井计算w（TOC）(b)交会图

Figure 6. Crossplot of rock core measurement w(TOC) versus w(TOC) calculated by ΔlgR method (a), by LithoScanner logging (b)

下载: 全尺寸图片幻灯片

表 1 库车坳陷三叠系−侏罗系烃源岩实测镜质体反射率(R_o)

Table 1. Reflectance of vitrinite measured of Triassic-Jurassic source rocks in Kuqa Depression

地区	井号	层位	R_o平均值/%	层位	R_o平均值/%
吐格地区	TX1	J₁y	0.82	J₂kz	−
	MN1		0.58		0.59
	TG4		0.76		−
	TG6		1.17		0.88
	TD2		1.09		−
迪北地区	YS4	J₁y	0.71	J₂kz	0.68
	YN2		0.95		0.85
	YN4		0.96		0.81
	YN5		0.96		−
	DB5		1.17		0.98
	DB6		1.18		0.88
阳霞地区	YT1	J₁y	1.05	J₂kz	1.07
阳霞地区	YX1	J₁y	0.92	J₂kz	0.89
注：J₁y.下侏罗统阳霞组；J₂kz.中侏罗统克孜勒努尔组；下同

下载: 导出CSV

表 2 库车坳陷三叠系−侏罗系煤系烃源岩测井响应特征

Table 2. Logging response characteristics of coaly source rocks of Triassic-Jurassic in Kucha Depression

岩性	暗色泥岩	碳质泥岩	煤
GR/API	>120	>120	<60
CNC/%	>20	>30	>40
DT/(μs·ft⁻¹)	>70	>80	>110
RT/(Ω⋅m)	>5	>10	>50
DEN/(g·cm⁻³)	<2.6	<2.5	<2.0
注：RT. 电阻率

下载: 导出CSV

参考文献(65)

[1]	邹才能, 陶士振, 薛叔浩. “相控论” 的内涵及其勘探意义[J]. 石油勘探与开发, 2005, 32(6): 7-12. doi: 10.3321/j.issn:1000-0747.2005.06.002 ZOU C N, TAO S Z, XUE S H. Connotation of "facies control theory" and its significance for exploration[J]. Petroleum Exploration and Development, 2005, 32(6): 7-12. (in Chinese with English abstract doi: 10.3321/j.issn:1000-0747.2005.06.002
[2]	霍秋立, 曾花森, 付丽, 等. ΔlgR测井源岩评价方法的改进及其在松辽盆地的应用[J]. 吉林大学学报(地球科学版), 2011, 41(2): 586-591. HUO Q L, ZENG H S, FU L, et al. The advance of ΔlgR method and its application in Songliao Basin[J]. Journal of Jilin University (Earth Science Edition), 2011, 41(2): 586-591. (in Chinese with English abstract
[3]	胡慧婷, 卢双舫, 刘超, 等. 测井资料计算源岩有机碳含量模型对比及分析[J]. 沉积学报, 2011, 29(6): 1199-1205. HU H T, LU S F, LIU C, et al. Models for calculating organic carbon content from logging information: Comparison and analysis[J]. Acta Sedimentologica Sinica, 2011, 29(6): 1199-1205. (in Chinese with English abstract
[4]	赖锦, 白天宇, 苏洋, 等. 烃源岩测井识别与评价方法研究进展[J]. 地质论评, 2024, 70(2): 721-741. LAI J, BAI T Y, SU Y, et al. Researches progress in well log recognition and evaluation of source rocks[J]. Geological Review, 2024, 70(2): 721-741. (in Chinese with English abstract
[5]	高阳. 利用测井信息评价盐湖相烃源岩[J]. 沉积学报, 2013, 31(4): 730-737. GAO Y. Salt lake source rock evaluation by logging data[J]. Acta Sedimentologica Sinica, 2013, 31(4): 730-737. (in Chinese with English abstract
[6]	MAHMOUD A A A, ELKATATNY S, MAHMOUD M, et al. Determination of the total organic carbon (TOC) based on conventional well logs using artificial neural network[J]. International Journal of Coal Geology, 2017, 179: 72-80. doi: 10.1016/j.coal.2017.05.012
[7]	殷杰, 王权. 利用测井和地震信息识别和预测优质烃源岩: 以渤海湾盆地饶阳凹陷沙一段为例[J]. 天然气地球科学, 2017, 28(11): 1761-1770. YIN J, WANG Q. Using seismic and log information to identify and predict high-quality source rocks: A case study of the First Member of Shahejie Formation in Raoyang Sag, Bohai Bay Basin[J]. Natural Gas Geoscience, 2017, 28(11): 1761-1770. (in Chinese with English abstract
[8]	LAI J, SU Y, XIAO L, et al. Application of geophysical well logs in solving geologic issues: Past, present and future prospect[J]. Geoscience Frontiers, 2024, 15(3): 101779. doi: 10.1016/j.gsf.2024.101779
[9]	陈海峰, 王凤启, 王民, 等. 基于变系数ΔlogR技术的烃源岩TOC精细评价[J]. 中国石油大学学报(自然科学版), 2017, 41(4): 54-64. doi: 10.3969/j.issn.1673-5005.2017.04.007 CHEN H F, WANG F Q, WANG M, et al. TOC evaluation using variable-coefficient ΔlogR model[J]. Journal of China University of Petroleum (Edition of Natural Science), 2017, 41(4): 54-64. (in Chinese with English abstract doi: 10.3969/j.issn.1673-5005.2017.04.007
[10]	AZIZ H, EHSAN M, ALI A, et al. Hydrocarbon source rock evaluation and quantification of organic richness from correlation of well logs and geochemical data: A case study from the sembar formation, southern Indus Basin, Pakistan[J]. Journal of Natural Gas Science and Engineering, 2020, 81: 103433. doi: 10.1016/j.jngse.2020.103433
[11]	袁超, 周灿灿, 胡松, 等. 地层有机碳含量测井评价方法综述[J]. 地球物理学进展, 2014, 29(6): 2831-2837. doi: 10.6038/pg20140652 YUAN C, ZHOU C C, HU S, et al. Summary on well logging evaluation method of total organic carbon content in formation[J]. Progress in Geophysics, 2014, 29(6): 2831-2837. (in Chinese with English abstract doi: 10.6038/pg20140652
[12]	LAI J, WANG G W, FAN Q X, et al. Geophysical well-log evaluation in the era of unconventional hydrocarbon resources: A review on current status and prospects[J]. Surveys in Geophysics, 2022, 43(3): 913-957. doi: 10.1007/s10712-022-09705-4
[13]	赖锦, 苏洋, 肖承文, 等. 地球物理测井在地质领域应用经典案例解析[J]. 地质科技通报, 2024, 43(5): 279-288. LAI J, SU Y, XIAO C W, et al. Analysis of typical applications of geophysical well logs in geological fields[J]. Bulletin of Geological Science and Technology, 2024, 43(5): 279-288. (in Chinese with English abstract
[14]	PASSEY Q R, CREANEY S, KULLA J B, et al. A practical model for organic richness from porosity and resistivity logs[J]. AAPG Bulletin, 1990, 74(12): 1777-1794.
[15]	王贵文, 朱振宇. 烃源岩测井识别与评价方法研究[J]. 石油勘探与开发, 2002, 29(4): 50-52. doi: 10.3321/j.issn:1000-0747.2002.04.015 WANG G W, ZHU Z Y. Logging identification and evaluation Cambrian-Ordovician source rocks in syneclise of Tarim Basin[J]. Petroleum Exploration and Development, 2002, 29(4): 50-52. (in Chinese with English abstract doi: 10.3321/j.issn:1000-0747.2002.04.015
[16]	ZHAO P Q, MAO Z Q, HUANG Z H, et al. A new method for estimating total organic carbon content from well logs[J]. AAPG Bulletin, 2016, 100(8): 1311-1327.
[17]	AMOSU A, SUN Y F. Identification of thermally mature total organic carbon-rich layers in shale formations using an effective machine-learning approach[J]. Interpretation, 2021, 9(3): 735-745.
[18]	杨涛涛, 邵大力, 曹光伟, 等. 烃源岩测井定量评价方法探讨[J]. 地球物理学进展, 2018, 33(1): 285-291. doi: 10.6038/pg2018AA0358 YANG T T, SHAO D L, CAO G W, et al. Logging quantitative evaluation method for hydrocarbon source rock[J]. Progress in Geophysics, 2018, 33(1): 285-291. (in Chinese with English abstract doi: 10.6038/pg2018AA0358
[19]	LAI J, ZHAO F, XIA Z L, et al. Well log prediction of total organic carbon: A comprehensive review[J]. Earth-Science Reviews, 2024, 258: 104913. doi: 10.1016/j.earscirev.2024.104913
[20]	袁龙, 王谦, 虞兵, 等. 致密气藏烃源岩地化参数测井综合评价方法研究[J]. 地球物理学进展, 2020, 35(1): 239-249. doi: 10.6038/pg2020CC0562 YUAN L, WANG Q, YU B, et al. Well logging evaluation method research of source rock geochemical parameters in the tight gas[J]. Progress in Geophysics, 2020, 35(1): 239-249. (in Chinese with English abstract doi: 10.6038/pg2020CC0562
[21]	黄小鹏, 杨占龙, 张兆辉, 等. 烃源岩地化参数的测井反演: 以雅布赖盆地小湖次凹侏罗系新河组下段为例[J]. 煤炭学报, 2020, 45(增刊1): 415-426. HUANG X P, YANG Z L, ZHANG Z H, et al. Logging inversion geochemical parameters of hydrocarbon source rocks: A case study of Jurassic Lower Xinhe Formation in Xiaohu sub-sag, Yabulai Basin[J]. Journal of China Coal Society, 2020, 45(S1): 415-426. (in Chinese with English abstract
[22]	杜文凤, 王攀, 梁明星, 等. 煤系烃源岩有机碳含量测井响应特征与定量预测模型[J]. 煤炭学报, 2016, 41(4): 954-963. DU W F, WANG P, LIANG M X, et al. Well logs response characteristics and quantitative prediction model of organic carbon content of hydrocarbon source rocks in coal-bearing strata measures[J]. Journal of China Coal Society, 2016, 41(4): 954-963. (in Chinese with English abstract
[23]	凡闪, 卢玉红, 李玲, 等. 塔里木盆地库车坳陷吐格尔明及周缘地区三叠系−侏罗系烃源岩地球化学特征、分布规律与油气地质意义[J]. 天然气地球科学, 2022, 33(12): 2074-2086. doi: 10.11764/j.issn.1672-1926.2022.08.012 FAN S, LU Y H, LI L, et al. Geochemical characteristics, distribution and petroleum geological significance of Triassic-Jurassic source rocks in the Tugeerming and surrounding areas of Kuqa Depression, Tarim Basin[J]. Natural Gas Geoscience, 2022, 33(12): 2074-2086. (in Chinese with English abstract doi: 10.11764/j.issn.1672-1926.2022.08.012
[24]	丁修建, 高天泽, 李淑凤, 等. 煤系烃源岩特征与发育机制研究现状[J]. 科学技术与工程, 2023, 23(13): 5373-5389. DING X J, GAO T Z, LI S F, et al. Research status of characteristics and development mechanism of coal-measure source rocks[J]. Science Technology and Engineering, 2023, 23(13): 5373-5389. (in Chinese with English abstract
[25]	中国石油天然气总公司. 烃源岩地球化学评价方法: SY/T 5735-2019[S]. 北京: 中国标准出版社, 2019. China National Petroleum Corporation. Hydrocarbon source rock geochemical evaluation method: SY/T 5735-2019[S]. Beijing: Standards Press of China. (in Chinese)
[26]	宋占东, 查明, 张小莉, 等. 烃源岩有机碳测井定量评价及在高邮凹陷永安地区的应用[J]. 西安石油大学学报(自然科学版), 2009, 24(2): 18-20. doi: 10.3969/j.issn.1673-064X.2009.02.005 SONG Z D, ZHA M, ZHANG X L, et al. A method for the quantitative evaluation of the organic carbon content of the hydrocarbon source rock from well logging information and its application in Yong'an oilfield in Gaoyou Sag[J]. Journal of Xi'an Shiyou University (Natural Science Edition), 2009, 24(2): 18-20. (in Chinese with English abstract doi: 10.3969/j.issn.1673-064X.2009.02.005
[27]	杜江民, 张小莉, 郑茜, 等. 致密油烃源岩有机碳含量测井定量预测模型适用性分析: 以柴达木盆地上干柴沟组下段烃源岩为例[J]. 西北大学学报(自然科学版), 2016, 46(2): 239-245. DU J M, ZHANG X L, ZHENG X, et al. The applicability of well logs prediction models of organic carbon content in source rocks of the tight oil: A case of the source rocks of lower section of N₁ Formation in Qaidm Basin[J]. Journal of Northwest University (Natural Science Edition), 2016, 46(2): 239-245. (in Chinese with English abstract
[28]	秦建强, 付德亮, 钱亚芳, 等. 烃源岩有机质丰度预测的地球物理研究进展[J]. 石油物探, 2018, 57(6): 803-812. doi: 10.3969/j.issn.1000-1441.2018.06.002 QIN J Q, FU D L, QIAN Y F, et al. Progress of geophysical methods for the evaluation of TOC of source rock[J]. Geophysical Prospecting for Petroleum, 2018, 57(6): 803-812. (in Chinese with English abstract doi: 10.3969/j.issn.1000-1441.2018.06.002
[29]	赖锦, 肖露, 白天宇, 等. 成像测井解释评价方法及其地质应用[J]. 地质科技通报, 2024, 43(3): 323-340. LAI J, XIAO L, BAI T Y, et al. Interpretation and evaluation methods of image logs and their geological applications[J]. Bulletin of Geological Science and Technology, 2024, 43(3): 323-340. (in Chinese with English abstract
[30]	ZHAO F, LAI J, XIA Z L, et al. Coaly source rock evaluation using well logs: The Jurassic Kezilenuer Formation in Kuqa Depression, Tarim Basin, China[J]. Petroleum Science, 2025, 22(9): 3599-3612.
[31]	张亮, 夏宗立, 王斌, 等. 深层烃源岩测井评价方法: 以库车坳陷侏罗系阳霞组烃源岩为例[J]. 地球物理学进展, 2025, 40(4): 1563-1576. ZHANG L, XIA Z L, WANG B, et al. Well log evaluation methods of deep source rocks: The Jurassic Yangxia Formation in Kuqa Depression[J]. Progress in Geophysics, 2025, 40(4): 1563-1576. (in Chinese with English abstract
[32]	李正勇, 郑姝, 彭瀚霖, 等. 安岳气田下寒武统海相烃源岩总有机碳含量测井预测[J]. 测井技术, 2020, 44(4): 398-403. LI Z Y, ZHENG S, PENG H L, et al. Log prediction of total organic carbon content in the Lower Cambrian marine source rocks of Anyue gas field[J]. Well Logging Technology, 2020, 44(4): 398-403. (in Chinese with English abstract
[33]	KHOSHNOODKIA M, MOHSENI H, RAHMANI O, et al. TOC determination of Gadvan Formation in South Pars gas field, using artificial intelligent systems and geochemical data[J]. Journal of Petroleum Science and Engineering, 2011, 78(1): 119-130. doi: 10.1016/j.petrol.2011.05.010
[34]	WANG H J, WU W, CHEN T, et al. An improved neural network for TOC, S₁ and S₂ estimation based on conventional well logs[J]. Journal of Petroleum Science and Engineering, 2019, 176: 664-678. doi: 10.1016/j.petrol.2019.01.096
[35]	WOOD D A. Total organic carbon predictions from lower Barnett shale well-log data applying an optimized data matching algorithm at various sampling densities[J]. Pure and Applied Geophysics, 2020, 177(11): 5451-5468. doi: 10.1007/s00024-020-02566-1
[36]	SCHMOKER J W. Determination of organic-matter content of Appalachian Devonian shales from gamma-ray logs[J]. 1981, 65(7): 1285-1298.
[37]	SCHMOKER J W, HESTER T C. Organic carbon in bakken formation, United States portion of Williston Basin[J]. 1983, 67(12): 2165-2174.
[38]	师展, 赵靖舟, 孙雄伟, 等. 鄂尔多斯盆地东南部上古生界煤系烃源岩特征及生烃潜力评价[J]. 天然气地球科学, 2023, 34(9): 1612-1626. SHI Z, ZHAO J Z, SUN X W, et al. Characteristics and hydrocarbon generation potential of Upper Paleozoic coal measure source rocks in the southeastern Ordos Basin[J]. Natural Gas Geoscience, 2023, 34(9): 1612-1626. (in Chinese with English abstract
[39]	赵彦超. 生油岩测井评价的理论和实践: 以南阳、泌阳凹陷为例[J]. 地球科学(中国地质大学学报), 1990, 15(1): 65-74. ZHAO Y C. The theory and application of logging for source rock evaluation: From the working results in Nanyang and Biyang depressions[J]. Earth Science(Journal of China University of Geosciences), 1990, 15(1): 65-74. (in Chinese with English abstract
[40]	王清辉, 冯进. 烃源岩TOC测井评价方法及应用: 以珠江口盆地文昌组为例[J]. 天然气地球科学, 2018, 29(2): 251-258. WANG Q H, FENG J. The TOC logging evaluation methods and application of source rock: A case study of Wenchang Formation in Pearl River Mouth Basin[J]. Natural Gas Geoscience, 2018, 29(2): 251-258. (in Chinese with English abstract
[41]	周妍, 王长胜, 林伟川, 等. 页岩油烃源岩地化参数测井评价方法及应用[J]. 测井技术, 2022, 46(3): 334-339. ZHOU Y, WANG C S, LIN W C, et al. Evaluation method and application for geochemical parameters of shale oil source rock[J]. Well Logging Technology, 2022, 46(3): 334-339. (in Chinese with English abstract
[42]	袁龙, 曹志锋, 别康, 等. 深层−超深层碎屑岩测井评价技术进展及展望[J]. 油气地质与采收率, 2025, 32(6): 1-14. YUAN L, CAO Z F, BIE K, et al. Review and prospect of logging evaluation technologies for deep and ultra-deep clastic rocks[J]. Petroleum Geology and Recovery Efficiency, 2025, 32(6): 1-14. (in Chinese with English abstract
[43]	SHALABY M R, JUMAT N, LAI D, et al. Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt[J]. Journal of Petroleum Science and Engineering, 2019, 176: 369-380. doi: 10.1016/j.petrol.2019.01.055
[44]	卢妍欣, 包书景, 周志, 等. 高热演化页岩总有机碳地球物理预测方法研究进展[J]. 地球物理学进展, 2023, 38(1): 229-241. doi: 10.6038/pg2023GG0212 LU Y X, BAO S J, ZHOU Z, et al. Research progress of geophysical prediction methods for total organic carbon in high-thermal evolution shale[J]. Progress in Geophysics, 2023, 38(1): 229-241. (in Chinese with English abstract doi: 10.6038/pg2023GG0212
[45]	朱建伟, 赵刚, 刘博, 等. 油页岩测井识别技术及应用[J]. 吉林大学学报(地球科学版), 2012, 42(2): 289-295. ZHU J W, ZHAO G, LIU B, et al. Identification technology and application of well-logging about oil shale[J]. Journal of Jilin University (Earth Science Edition), 2012, 42(2): 289-295. (in Chinese with English abstract
[46]	刘瑞, 郭少斌, 王继远. 烃源岩TOC计算模型: 以鄂尔多斯盆地太原组−山西组为例[J]. 天然气地球科学, 2020, 31(11): 1628-1636. LIU R, GUO S B, WANG J Y. TOC calculation model of source rocks: Case study from Taiyuan-Shanxi formations in Ordos Basin[J]. Natural Gas Geoscience, 2020, 31(11): 1628-1636. (in Chinese with English abstract
[47]	胡慧婷, 苏瑞, 刘超, 等. 广义ΔlgR技术预测陆相深层烃源岩有机碳含量方法及其应用[J]. 天然气地球科学, 2016, 27(1): 149-155. doi: 10.11764/j.issn.1672-1926.2016.01.0149 HU H T, SU R, LIU C, et al. The method and application of using generalized-ΔlgR technology to predict the organic carbon content of continental deep source rocks[J]. Natural Gas Geoscience, 2016, 27(1): 149-155. (in Chinese with English abstract doi: 10.11764/j.issn.1672-1926.2016.01.0149
[48]	王宵宇, 谢然红, 毛治国, 等. 基于集成学习的烃源岩总有机碳含量测井评价方法研究[J]. 地球物理学进展, 2022, 37(2): 684-694. WANG X Y, XIE R H, MAO Z G, et al. Research on logging evaluation method of total organic carbon content of source rock based on ensemble learning[J]. Progress in Geophysics, 2022, 37(2): 684-694. (in Chinese with English abstract
[49]	苏洋, 赖锦, 赵飞, 等. 岩性扫描测井解释评价方法及其地质应用[J]. 地质论评, 2024, 70(5): 1884-1898. SU Y, LAI J, ZHAO F, et al. Interpretation and evaluation methods of litho-scanner logging data and its geological application[J]. Geological Review, 2024, 70(5): 1884-1898. (in Chinese with English abstract
[50]	赖锦, 党文乐, 苏洋, 等. 声波测井地质与工程应用[J]. 地质论评, 2025, 71(3): 1046-1072. LAI J, DANG W L, SU Y, et al. Geological and engineering applications of sonic logs[J]. Geological Review, 2025, 71(3): 1046-1072. (in Chinese with English abstract
[51]	柳建华, 刘瑞林, 吴兴能, 等. 化学元素测井资料在地层界面处的响应特征研究[J]. 石油天然气学报, 2007, 29(1): 84-87. LIU J H, LIU R L, WU X N, et al. On the data of response characters of elemental capture spectroscopy (ECS) logging at stratum boundary[J]. Journal of Oil and Gas Technology, 2007, 29(1): 84-87. (in Chinese with English abstract
[52]	魏翔宇, 赵延朋, 王璞珺, 等. 松辽盆地徐家围子断陷营城组火山地层期次划分及分布规律[J]. 中国石油大学学报(自然科学版), 2023, 47(4): 12-23. doi: 10.3969/j.issn.1673-5005.2023.04.002 WEI X Y, ZHAO Y P, WANG P J, et al. Division of volcanic eruption stages and distribution patterns of volcanic rocks in Yingcheng Formation of Xujiaweizi fault depression, Songliao Basin[J]. Journal of China University of Petroleum (Edition of Natural Science), 2023, 47(4): 12-23. (in Chinese with English abstract doi: 10.3969/j.issn.1673-5005.2023.04.002
[53]	王胜建, 任收麦, 周志, 等. 鄂西地区震旦系陡山沱组二段页岩气储层测井评价初探[J]. 中国地质, 2020, 47(1): 133-143. doi: 10.12029/gc20200111 WANG S J, REN S M, ZHOU Z, et al. Discussion on petrophysical evaluation of shale gas reservoir in the Second Member of Sinian Doushantuo Formation in western Hubei Province, South China[J]. Geology in China, 2020, 47(1): 133-143. (in Chinese with English abstract doi: 10.12029/gc20200111
[54]	庞小娇, 王贵文, 匡立春, 等. 沉积环境控制下的页岩岩相组合类型及测井表征: 以松辽盆地古龙凹陷青山口组为例[J]. 古地理学报, 2023, 25(5): 1156-1175. doi: 10.7605/gdlxb.2023.05.090 PANG X J, WANG G W, KUANG L C, et al. Logging evaluation of lithofacies and their assemblage under control of sedimentary environment: A case study of the Qingshankou Formation in Gulong Sag, Songliao Basin[J]. Journal of Palaeogeography (Chinese Edition), 2023, 25(5): 1156-1175. (in Chinese with English abstract doi: 10.7605/gdlxb.2023.05.090
[55]	赖锦, 王贵文, 范卓颖, 等. 非常规油气储层脆性指数测井评价方法研究进展[J]. 石油科学通报, 2016, 1(3): 330-341. LAI J, WANG G W, FAN Z Y, et al. Research progress in brittleness index evaluation methods with logging data in unconventional oil and gas reservoirs[J]. Petroleum Science Bulletin, 2016, 1(3): 330-341. (in Chinese with English abstract
[56]	MEWS K S, ALHUBAIL M M, BARATI R G. A review of brittleness index correlations for unconventional tight and ultra-tight reservoirs[J]. Geosciences, 2019, 9(7): 319. doi: 10.3390/geosciences9070319
[57]	LAI J, WANG G W, CHEN J, et al. Origin and distribution of carbonate cement in tight sandstones: The Upper Triassic Yanchang Formation Chang 8 oil layer in West Ordos Basin, China[J]. Geofluids, 2017, 2017(1): 8681753.
[58]	DE S, SENGUPTA D. An advanced well log and an effective methodology to evaluate water saturation of the organic-rich Cambay shale[J]. Natural Resources Research, 2021, 30(2): 1719-1733. doi: 10.1007/s11053-020-09763-8
[59]	CHARSKY A, HERRON S. Accurate, direct total organic carbon (TOC) log from a new advanced geochemical spectroscopy tool: Comparison with conventional approaches for TOC estimation[J]. Search and Discovery, 2013, 4116, 2(1): 1-17.
[60]	贺聪, 苏奥, 张明震, 等. 鄂尔多斯盆地延长组烃源岩有机碳含量测井预测方法优选及应用[J]. 天然气地球科学, 2016, 27(4): 754-764. doi: 10.11764/j.issn.1672-1926.2016.04.0754 HE C, SU A, ZHANG M Z, et al. Optimal selection and application of prediction means for organic carbon content of source rocks based on logging data in Yanchang Formation, Ordos Basin[J]. Natural Gas Geoscience, 2016, 27(4): 754-764. (in Chinese with English abstract doi: 10.11764/j.issn.1672-1926.2016.04.0754
[61]	赖锦, 凡雪纯, 黎雨航, 等. 苏北盆地古近系阜宁组页岩七性关系与三品质测井评价[J]. 地质论评, 2022, 68(2): 751-768. LAI J, FAN X C, LI Y H, et al. Well logging evaluation of seven kinds of relationships and three types of properties of Paleogene Funing Formation oil shales in Subei Basin[J]. Geological Review, 2022, 68(2): 751-768. (in Chinese with English abstract
[62]	赖锦, 宋翔羽, 杨薰, 等. 致密砂岩气储层测井综合评价技术研究进展[J]. 石油学报, 2025, 46(1): 220-235. LAI J, SONG X Y, YANG X, et al. Research progresses of comprehensive well logging evaluation methods of tight gas sandstone reservoirs[J]. Acta Petrolei Sinica, 2025, 46(1): 220-235. (in Chinese with English abstract
[63]	赖锦, 苏洋, 党文乐, 等. 储层裂缝测井评价技术[J]. 石油学报, 2025, 46(11): 2187-2210. LAI J, SU Y, DANG W L, et al. Well logging evaluation method of reservoir fractures[J]. Acta Petrolei Sinica, 2025, 46(11): 2187-2210. (in Chinese with English abstract
[64]	ZHAO F, LAI J, XIAO L, et al. Pore structure and gas content evaluation of coal-rock gas using well log data[J]. Unconventional Resources, 2025, 8: 100247.
[65]	邹才能, 赵群, 刘翰林, 等. 中国煤岩气突破及意义[J]. 天然气工业, 2025(4): 1-18. ZOU C N, ZHAO Q, LIU H L, et al. China's breakthrough in coal-rock gas and its significance[J]. Natural Gas Industry, 2025(4): 1-18. (in Chinese with English abstract