渤海湾盆地渤中凹陷西南部深层烃源岩有机相预测

王祥; 马劲风; 王飞龙; 王震亮; 陈容涛; 闫昕宇

doi:10.11781/sysydz2022061070

渤海湾盆地渤中凹陷西南部深层烃源岩有机相预测

doi: 10.11781/sysydz2022061070

王祥^{1, 2, 3,},
马劲风^{1, 2, 3, ,},
王飞龙⁴,
王震亮^{1, 2, 3},
陈容涛⁴,
闫昕宇^{1, 3}

1.
西北大学地质学系，西安 710069
2.
二氧化碳捕集与封存技术国家地方联合工程研究中心，西安 710069
3.
大陆动力学国家重点实验室，西安 710069
4.
中海石油(中国)有限公司天津分公司勘探开发研究院，天津 300452

基金项目:

中海石油(中国)有限公司天津分公司课题“渤中凹陷深层成烃成藏机理与规律研究” CCL2018TJTZDST0579

详细信息

作者简介:
王祥(1997—)，男，硕士研究生，从事烃源岩地球物理预测研究。E-mail：wangxiang1@stumail.nwu.edu.cn

通讯作者:
马劲风(1965—)，男，教授，博士生导师，从事地震勘探和储层预测等研究。E-mail：jinfengma@sina.com

中图分类号: TE122.113
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出版历程
- 收稿日期: 2021-07-29
- 修回日期: 2022-09-28
- 刊出日期: 2022-11-28

Prediction of organic facies of deep source rocks in southwestern part of Bozhong Sag, Bohai Bay Basin

WANG Xiang^{1, 2, 3
,},
MA Jinfeng^{1, 2, 3
, ,},
WANG Feilong⁴,
WANG Zhenliang^{1, 2, 3},
CHEN Rongtao⁴,
YAN Xinyu^{1, 3}

1.
Department of Geology, Northwest University, Xi'an, Shaanxi 710069, China
2.
National & Local Joint Engineering Research Center of Carbon Capture and Storage Technology, Xi'an, Shaanxi 710069, China
3.
State Key Laboratory of Continental Dynamics, Xi'an, Shaanxi 710069, China
4.
Exploration and Development Research Institute, Tianjin Branch of CNOOC, Tianjin 300452, China

摘要

摘要: 针对渤海湾盆地渤中凹陷西南部烃源岩层系多、非均质性较强等特点，开展了烃源岩干酪根显微组分、元素分析、岩石热解、气相色谱等地球化学分析测试，在沉积相的约束下对比了ΔlogR系列方法、多元回归法、BP神经网络法预测有机质丰度参数的优劣，优选BP神经网络法进行烃源岩总有机碳含量、裂解烃含量的单井预测，进而计算得到氢指数预测曲线，结合总有机碳含量进行有机相分析，定量刻画各层系烃源岩的有机相，分析烃源岩的优劣和展布特征。结果表明，BP神经网络法的预测精度相对较高，东营组二段下亚段烃源岩主要为Ⅱ₂型干酪根，氢指数为125~400 mg/g，总有机碳含量基本小于3%，其有机相主要为BC相、C相和CD相；东营组三段烃源岩主要为Ⅱ₁—Ⅱ₂型干酪根，沙河街组沙一二段、沙三段烃源岩主要为Ⅰ—Ⅱ₁型干酪根，这三套烃源岩的氢指数为250~650 mg/g，总有机碳含量为3%左右或大于3%，其有机相主要为B相、BC相和C相。沙河街组优质烃源岩主要发育于研究区中南部，是下一步勘探的重点区域。
- 总有机碳含量 /
- ΔlogR方法 /
- 有机相 /
- 烃源岩 /
- BP神经网络 /
- 渤中凹陷 /
- 渤海湾盆地
Abstract: Considering the characteristics of abundant source rock formations and heterogeneity in the southwestern part of the Bozhong Sag, Bohai Bay Basin, based on the geochemical and petrographic analysis of source rocks, the methods of ΔlogR series, multiple regression and BP neural network are applied to predict the organic matter abundance under the constraints of sedimentary facies.The BP neural network method is preferably used to predict the total organic carbon content and cracked hydrocarbon content of source rocks in a single well, and then the hydrogen index prediction curve is calculated.Combined with total organic carbon content, the organic phase of each source rock layer is quantitatively described, and the advantages and disadvantages and distribution characteristics of source rocks are analyzed. Results show that the prediction accuracy of BP neural network method is relatively higher. The source rocks in the lower section of the second member of Dongying Formation are featured by kerogen of type Ⅱ₂, hydrocarbon index of 125-400 mg/g, TOC content basically less than 3%, and organic facies of BC, C and CD types. The source rocks in the third member of Dongying Formation are featured by kerogen of typesⅡ₁ to Ⅱ₂. The source rocks in the first, second and third members of Shahejie Formation are featured by kerogen of types Ⅰ to Ⅱ₁, TOC content about 3% or higher than 3%, and organic facies of B, BC and C types.The high-quality source rocks of the Shahejie Formation are mainly developed in the central and southern parts of the study area, and are the key areas for further exploration.
- total organic carbon content /
- ΔlogR method /
- organic facies /
- source rock /
- BP neural network /
- Bozhong Sag /
- Bohai Bay Basin

HTML全文

图 1 渤海湾盆地渤中凹陷区域概况(a)、研究区位置(b)及地层综合柱状图(c)

据文献[19, 37]修改。

Figure 1. Regional overview of Bozhong Sag (a), location of study area (b), and generalized stratigraphic histogram (c), Bohai Bay Basin

下载: 全尺寸图片幻灯片

图 2 渤海湾盆地渤中凹陷西南部烃源岩干酪根显微组分(a)、干酪根H/C原子比和O/C原子比(b)、TOC含量(c)和Pr/nC₁₇和Ph/nC₁₈值相关图(d)

Figure 2. Microscopic composition of kerogen (a), H/C and O/C ratio of kerogen (b), TOC content (c), and correlation between Pr/nC₁₇ and Ph/nC₁₈ (d) of source rocks from southwestern part of Bozhong Sag, Bohai Bay Basin

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图 3 渤海湾盆地渤中凹陷西南部烃源岩岩石热解氢指数、总有机碳含量、生烃潜力交会图

Figure 3. Intersection of pyrolysis hydrogen index, TOC content and S₁+S₂ of source rocks from southwestern part of Bozhong Sag, Bohai Bay Basin

下载: 全尺寸图片幻灯片

图 4 渤海湾盆地渤中凹陷西南部烃源岩测井参数与TOC、S₂交会图

Figure 4. Intersection of logging parameters and TOC and S₂ of source rocks from southwestern part of Bozhong Sag, Bohai Bay Basin

下载: 全尺寸图片幻灯片

图 5 三层BP神经网络预测TOC、S₂原理

Figure 5. Schematic diagram of TOC and S₂ prediction by three-layer BP neural network

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图 6 四种方法预测TOC判定系数R²、平均相对误差分析

Figure 6. Coefficient R² and average relative error of four methods for TOC prediction

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图 7 渤海湾盆地渤中凹陷西南部Q3井TOC、S₂、I_H预测与实测综合地球化学剖面

Figure 7. Generalized geochemical profiles showing predicted and measured TOC, S₂, and I_H values of well Q3, southwestern part of Bozhong Sag, Bohai Bay Basin

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图 8 渤海湾盆地渤中凹陷西南部烃源岩沉积相和各有机相分布

a.E₃d₂^L沉积相；b.E₃d₃沉积相；c.E₂s₁₊₂沉积相；d.E₂s₃沉积相；e.E₃d₂^LC相；f.E₃d₃B相；g.E₂s₁₊₂B相；h.E₂s₃B相；i.E₃d₂^LCD相；j.E₃d₃BC相；k.E₂s₁₊₂BC相；l.E₂s₃BC相

Figure 8. Sedimentary facies and organic facies distribution of source rocks in southwestern part of Bozhong Sag, Bohai Bay Basin

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表 1 有机相分类

Table 1. Classification of organic facies

表 2 渤海湾盆地渤中凹陷西南部各TOC预测方法判定系数R²对比

Table 2. Coefficient R² calculated by various methods for TOC prediction, southwestern part of Bozhong Sag, Bohai Bay Basin

层位	沉积相	ΔlogR法	广义ΔlogR法	多元回归法	BP神经网络法
E₃d₂^L	辫状河三角洲	0.712 3	0.722 7	0.818 1	0.933 5
	滨浅湖	0.780 6	0.800 3	0.581 4	0.878 9
	半深湖—深湖	0.008 8	0.321 5	0.322 3	0.839 2
	湖底扇	0.220 0	0.592 4	0.609 6	0.890 2
E₃d₃	滨浅湖	0.550 6	0.818 1	0.719 8	0.804 1
E₃d₃	半深湖—深湖	0.346 0	0.580 2	0.705 9	0.891 1
E₂s₁₊₂	滨浅湖	0.312 5	0.469 5	0.347 7	0.862 5
E₂s₃	半深湖—深湖	0.215 3	0.433 4	0.325 5	0.743 2
E₂s₃	辫状河三角洲	0.558 3	0.693 2	0.700 9	0.811 3

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参考文献(40)

[1]	邹才能, 朱如凯, 吴松涛, 等. 常规与非常规油气聚集类型、特征、机理及展望: 以中国致密油和致密气为例[J]. 石油学报, 2012, 33(2): 173-187. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB201202002.htm ZOU Caineng, ZHU Rukai, WU Songtao, et al. Types, characte-ristics, genesis and prospects of conventional and unconventional hydrocarbon accumulations: taking tight oil and tight gas in China as an instance[J]. Acta Petrolei Sinica, 2012, 33(2): 173-187. https://www.cnki.com.cn/Article/CJFDTOTAL-SYXB201202002.htm
[2]	焦方正. 非常规油气之"非常规"再认识[J]. 石油勘探与开发, 2019, 46(5): 803-810. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201905002.htm JIAO Fangzheng. Re-recognition of "unconventional" in unconventional oil and gas[J]. Petroleum Exploration and Development, 2019, 46(5): 803-810. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201905002.htm
[3]	LAW B E, CURTIS J B. Introduction to unconventional petroleum systems[J]. AAPG Bulletin, 2002, 86(11): 1851-1852.
[4]	SOEDER D J. The successful development of gas and oil resources from shales in North America[J]. Journal of Petroleum Science and Engineering, 2018, 163: 399-420. doi: 10.1016/j.petrol.2017.12.084
[5]	ROGERS M A. PD 1(3) application of organic facies concepts to hydrocarbon source rock evaluation[C]//Proceedings of the 10th World Petroleum Congress. Bucharest: WPC, 1979: 23-30.
[6]	JONES R W. Organic facies[M]//BROOKS J, WELTE D. Advances in Petroleum Geochemistry. London: Academic, 1987: 1-89.
[7]	PEPPER A S, CORVI P J. Simple kinetic models of petroleum formation. Part Ⅰ: oil and gas generation from kerogen[J]. Marine and Petroleum Geology, 1995, 12(3): 291-319. doi: 10.1016/0264-8172(95)98381-E
[8]	郝芳, 陈建渝, 孙永传, 等. 有机相研究及其在盆地分析中的应用[J]. 沉积学报, 1994, 12(4): 77-86. doi: 10.14027/j.cnki.cjxb.1994.04.009 HAO Fang, CHEN Jianyu, SUN Yongchuan, et al. Organic facies studies and their use in sedimentary basin analysis[J]. Acta Sedimentologica Sinica, 1994, 12(4): 77-86. doi: 10.14027/j.cnki.cjxb.1994.04.009
[9]	ABDULLAH W H. Organic facies variations in the Triassic shallow marine and deep marine shales of central Spitsbergen, Svalbard[J]. Marine and Petroleum Geology, 1999, 16(5): 467-481. doi: 10.1016/S0264-8172(98)00086-5
[10]	李君文, 陈洪德, 田景春, 等. 沉积有机相的研究现状及其应用[J]. 沉积与特提斯地质, 2004, 24(2): 96-100. https://www.cnki.com.cn/Article/CJFDTOTAL-TTSD200402015.htm LI Junwen, CHEN Hongde, TIAN Jingchun, et al. Sedimentary organic facies: current research and applications[J]. Sedimentary Geology and Tethyan Geology, 2004, 24(2): 96-100. https://www.cnki.com.cn/Article/CJFDTOTAL-TTSD200402015.htm
[11]	姚素平, 毛鹤龄, 金奎励, 等. 准噶尔盆地侏罗系西山窑组沉积有机相研究及烃源岩评价[J]. 中国矿业大学学报, 1997, 26(1): 62-66. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGKD701.016.htm YAO Suping, MAO Heling, JIN Kuili, et al. Study of sedimentary organic facies and the evaluating of source rock on Xishanyao Formation coal-bearing strata of Jurassic system in Junggar Basin[J]. Journal of China University of Mining & Technology, 1997, 26(1): 62-66. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGKD701.016.htm
[12]	YURCHENKO I A, MOLDOWAN J M, PETERS K E, et al. Source rock heterogeneity and migrated hydrocarbons in the Triassic Shublik Formation and their implication for unconventional resource evaluation in Arctic Alaska[J]. Marine and Petroleum Geology, 2018, 92: 932-952. doi: 10.1016/j.marpetgeo.2018.03.033
[13]	DEAF A S, TAHOUN S S, GENTZIS T, et al. Organic geochemical, palynofacies, and petrographic analyses examining the hydrocarbon potential of the Kharita Formation (Albian) in the Matruh Basin, northwestern Egypt[J]. Marine and Petroleum Geology, 2020, 112: 104087. doi: 10.1016/j.marpetgeo.2019.104087
[14]	RODRIGUEZ N D, PHILP R P. Source rock facies distribution predicted from oil geochemistry in the central Sumatra Basin, Indonesia[J]. AAPG Bulletin, 2015, 99(11): 2005-2022. doi: 10.1306/06191514050
[15]	赵志刚, 王飞宇, 王洪波, 等. 二连盆地赛汉塔拉凹陷烃源岩有机相与烃源灶[J]. 岩性油气藏, 2017, 29(2): 28-35. https://www.cnki.com.cn/Article/CJFDTOTAL-YANX201702004.htm ZHAO Zhigang, WANG Feiyu, WANG Hongbo, et al. Source kitchen and organic facies of source rocks in Sahantala Sag, Erlian Basin[J]. Lithologic Reservoirs, 2017, 29(2): 28-35. https://www.cnki.com.cn/Article/CJFDTOTAL-YANX201702004.htm
[16]	孙哲, 彭靖淞, 江尚昆, 等. 渤海海域庙西中南洼围区烃源岩有机相与测井评价[J]. 岩性油气藏, 2020, 32(1): 102-110. https://www.cnki.com.cn/Article/CJFDTOTAL-YANX202001011.htm SUN Zhe, PENG Jingsong, JIANG Shangkun, et al. Organic facies and well logging evaluation of source rocks in centeral-south sag of Miaoxi Depression and its surrounding areas, Bohai Sea[J]. Litho-logic Reservoirs, 2020, 32(1): 102-110. https://www.cnki.com.cn/Article/CJFDTOTAL-YANX202001011.htm
[17]	杨海风, 涂翔, 赵弟江, 等. 渤海湾盆地莱州湾凹陷沙河街组第三、第四段烃源岩有机相特征[J]. 成都理工大学学报(自然科学版), 2021, 48(1): 72-81. https://www.cnki.com.cn/Article/CJFDTOTAL-CDLG202101008.htm YANG Haifeng, TU Xiang, ZHAO Dijiang, et al. Organic facies characteristics of source rocks on the 3rd and 4th member of Shahejie Formation in the southern Laizhouwan Depression, Bohai Bay Basin, China[J]. Journal of Chengdu University of Technology (Science & Technology Edition), 2021, 48(1): 72-81. https://www.cnki.com.cn/Article/CJFDTOTAL-CDLG202101008.htm
[18]	徐长贵, 于海波, 王军, 等. 渤海海域渤中19-6大型凝析气田形成条件与成藏特征[J]. 石油勘探与开发, 2019, 46(1): 25-38. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201901003.htm XU Changgui, YU Haibo, WANG Jun, et al. Formation conditions and accumulation characteristics of Bozhong 19-6 large condensate gas field in offshore Bohai Bay Basin[J]. Petroleum Exploration and Development, 2019, 46(1): 25-38. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201901003.htm
[19]	薛永安, 王奇, 牛成民, 等. 渤海海域渤中凹陷渤中19-6深层潜山凝析气藏的充注成藏过程[J]. 石油与天然气地质, 2020, 41(5): 891-902. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT202005002.htm XUE Yongan, WANG Qi, NIU Chengmin, et al. Hydrocarbon charging and accumulation of BZ 19-6 gas condensate field in deep buried hills of Bozhong Depression, Bohai Sea[J]. Oil & Gas Geology, 2020, 41(5): 891-902. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT202005002.htm
[20]	李慧勇, 牛成民, 许鹏, 等. 渤中13-2大型整装覆盖型潜山油气田的发现及其油气勘探意义[J]. 天然气工业, 2021, 41(2): 19-26. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG202102005.htm LI Huiyong, NIU Chengmin, XU Peng, et al. Discovery of Bozhong 13-2 archean large monoblock volatile buried hill oilfield and its oil and gas exploration significance[J]. Natural Gas Industry, 2021, 41(2): 19-26. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG202102005.htm
[21]	施和生, 牛成民, 侯明才, 等. 渤中13-2双层结构太古宇潜山成藏条件分析与勘探发现[J]. 中国石油勘探, 2021, 26(2): 12-20. https://www.cnki.com.cn/Article/CJFDTOTAL-KTSY202102002.htm SHI Hesheng, NIU Chengmin, HOU Mingcai, et al. Analysis of hydrocarbon accumulation conditions of double-layered Archaeozoic buried hill and major discovery of Bozhong 13-2 Oil and Gasfield, Bohai Sea area[J]. China Petroleum Exploration, 2021, 26(2): 12-20. https://www.cnki.com.cn/Article/CJFDTOTAL-KTSY202102002.htm
[22]	PASSEY Q R, CREANEY S, KULLA J B, et al. A practical model for organic richness from porosity and resistivity logs1[J]. AAPG Bulletin, 1990, 74(12): 1777-1794.
[23]	刘超, 卢双舫, 薛海涛. 变系数ΔlogR方法及其在泥页岩有机质评价中的应用[J]. 地球物理学进展, 2014, 29(1): 312-317. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201401044.htm LIU Chao, LU Shuangfang, XUE Haitao. Variable-coefficient ΔlogR model and its application in shale organic evaluation[J]. Progress in Geophysics, 2014, 29(1): 312-317. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201401044.htm
[24]	王祥, 马劲风, 王德英, 等. 渤中凹陷西南部烃源岩TOC含量预测[J]. 石油地球物理勘探, 2020, 55(6): 1330-1342. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ202006018.htm WANG Xiang, MA Jinfeng, WANG Deying, et al. Prediction of TOC content in source rocks in southwestern Bozhong Sag[J]. Oil Geophysical Prospecting, 2020, 55(6): 1330-1342. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ202006018.htm
[25]	杜江民, 张小莉, 钟高润, 等. 致密油烃源岩有机碳含量测井评价方法优选及应用: 以鄂尔多斯盆地延长组长7段烃源岩为例[J]. 地球物理学进展, 2016, 31(6): 2526-2533. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201606023.htm DU Jiangmin, ZHANG Xiaoli, ZHONG Gaorun, et al. Analysis on the optimization and application of well logs indentification methods for organic carbon content in source rocks of the tight oil: illustrated by the example of the source rocks of Chang 7 member of Yanchang Formation in Ordos Basin[J]. Progress in Geophysics, 2016, 31(6): 2526-2533. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWJ201606023.htm
[26]	HUANG Zehui, WILLIAMSON M A. Artificial neural network modelling as an aid to source rock characterization[J]. Marine and Petroleum Geology, 1996, 13(2): 277-290.
[27]	KAMALI M R, MIRSHADY A A. Total organic carbon content determined from well logs using ΔlogR and neuro fuzzy techniques[J]. Journal of Petroleum Science and Engineering, 2004, 45(3/4): 141-148.
[28]	BOLANDI V, KADKHODAIE-ILKHCHI A, ALIZADEH B, et al. Source rock characterization of the Albian Kazhdumi Formation by integrating well logs and geochemical data in the Azadegan Oilfield, Abadan Plain, SW Iran[J]. Journal of Petroleum Science and Engineering, 2015, 133: 167-176.
[29]	WANG Huijun, WU Wei, CHEN Tao, 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.
[30]	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.
[31]	赵峦啸, 刘金水, 姚云霞, 等. 基于随机森林算法的陆相沉积烃源岩定量地震刻画: 以东海盆地长江坳陷为例[J]. 地球物理学报, 2021, 64(2): 700-715. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX202102025.htm ZHAO Luanxiao, LIU Jinshui, YAO Yunxia, et al. Quantitative seismic characterization of source rocks in lacustrine depositional setting using the Random Forest method: an example from the Changjiang Sag in East China Sea Basin[J]. Chinese Journal of Geophysics, 2021, 64(2): 700-715. https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX202102025.htm
[32]	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. https://www.cnki.com.cn/Article/CJFDTOTAL-TDKX201601018.htm HU Huiting, SU Rui, LIU Chao, 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. https://www.cnki.com.cn/Article/CJFDTOTAL-TDKX201601018.htm
[33]	边雷博, 柳广弟, 孙明亮, 等. 优化的ΔLogR技术及其在中—深层烃源岩总有机碳含量预测中的应用[J]. 油气地质与采收率, 2018, 25(4): 40-45. https://www.cnki.com.cn/Article/CJFDTOTAL-YQCS201804007.htm BIAN Leibo, LIU Guangdi, SUN Mingliang, et al. Improved ΔlogR technique and its application to predicting total organic carbon of source rocks with middle and deep burial depth[J]. Petroleum Geology and Recovery Efficiency, 2018, 25(4): 40-45. https://www.cnki.com.cn/Article/CJFDTOTAL-YQCS201804007.htm
[34]	赵彦德, 刘洛夫, 王旭东, 等. 渤海湾盆地南堡凹陷古近系烃源岩有机相特征[J]. 中国石油大学学报(自然科学版), 2009, 33(5): 23-29. ZHAO Yande, LIU Luofu, WANG Xudong, et al. Characteristics of organic facies of Eogene hydrocarbon source rocks in Nanpu Sag, Bohai Bay Basin[J]. Journal of China University of Petroleum (Edition of Natural Science), 2009, 33(5): 23-29.
[35]	崔永谦, 王飞宇, 张传宝, 等. 渤海湾盆地冀中坳陷霸县凹陷深层沙四段源岩有机相评价及意义[J]. 天然气地球科学, 2021, 32(1): 38-46. https://www.cnki.com.cn/Article/CJFDTOTAL-TDKX202101005.htm CUI Yongqian, WANG Feiyu, ZHANG Chuanbao, et al. Orgao-faices evolution of deep Es₄ source rock in Baxian Sag, Jizhong Depression of Bohai Bay Basin and its significance[J]. Natural Gas Geoscience, 2021, 32(1): 38-46. https://www.cnki.com.cn/Article/CJFDTOTAL-TDKX202101005.htm
[36]	侯明才, 曹海洋, 李慧勇, 等. 渤海海域渤中19-6构造带深层潜山储层特征及其控制因素[J]. 天然气工业, 2019, 39(1): 33-44. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG201901005.htm HOU Mingcai, CAO Haiyang, LI Huiyong, et al. Characteristics and controlling factors of deep buried-hill reservoirs in the BZ19-6 structural belt, Bohai Sea area[J]. Natural Gas Industry, 2019, 39(1): 33-44. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG201901005.htm
[37]	薛永安, 王飞龙, 汤国民, 等. 渤海海域页岩油气地质条件与勘探前景[J]. 石油与天然气地质, 2020, 41(4): 696-709. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT202004005.htm XUE Yongan, WANG Feilong, TANG Guomin, et al. Geological condition and exploration prospect of shale oil and gas in the Bohai Sea[J]. Oil & Gas Geology, 2020, 41(4): 696-709. https://www.cnki.com.cn/Article/CJFDTOTAL-SYYT202004005.htm
[38]	ZHU Linqi, ZHANG Chaomo, ZHANG Zhansong, et al. An improved method for evaluating the TOC content of a shale formation using the dual-difference ΔlogR method[J]. Marine and Petroleum Geology, 2019, 102: 800-816.
[39]	严鸿, 管燕萍. BP神经网络隐层单元数的确定方法及实例[J]. 控制工程, 2009, 16(S2): 100-102. https://www.cnki.com.cn/Article/CJFDTOTAL-JZDF2009S2030.htm YAN Hong, GUAN Yanping. Method to determine the quantity of internal nodes of back propagation neural networks and its demonstration[J]. Control Engineering of China, 2009, 16(S2): 100-102. https://www.cnki.com.cn/Article/CJFDTOTAL-JZDF2009S2030.htm
[40]	季少聪, 杨香华, 朱红涛, 等. 下刚果盆地A区块Madingo组烃源岩TOC含量的地球物理定量预测[J]. 石油地球物理勘探, 2018, 53(2): 369-380. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ201802020.htm JI Shaocong, YANG Xianghua, ZHU Hongtao, et al. Geophysical quantitative prediction of TOC content in source rocks of Madingo Formation in block A, Lower Congo Basin[J]. Oil Geophysical Prospecting, 2018, 53(2): 369-380. https://www.cnki.com.cn/Article/CJFDTOTAL-SYDQ201802020.htm