四川盆地威远地区五峰组—龙马溪组页岩TOC含量地震定量预测方法及应用

doi:10.11764/j.issn.1672-1926.2018.10.026

天然气地球科学

四川盆地威远地区五峰组—龙马溪组页岩TOC含量地震定量预测方法及应用

邓宇^1,2，曾庆才^2,3，陈胜³，管全中3，郭晓龙³，贺佩³

1.中国科学院大学，北京 100049；
2.中国科学院渗流流体力学研究所，河北廊坊 065007；
3.中国石油勘探开发研究院，北京 100083

收稿日期:2018-08-12 修回日期:2018-10-31 出版日期:2019-03-10
作者简介:邓宇(1994-)，女，湖南浏阳人，硕士研究生，主要从事非常规油气地震勘探研究.E-mail：dengyu16@mails.ucas.ac.cn.
基金资助:
国家科技重大专项课题“富有机质页岩储层精细描述与定量表征”（编号：2017ZX05035-02）资助.

Seismic quantitative prediction method and application of TOC content in Wufeng-Longmaxi Formations shale reservoirs in Weiyuan area,Sichuan Basin

Deng Yu^1,2,Zeng Qing-cai^2,3,Chen Sheng³,Guan Quan-zhong³,Guo Xiao-long³,He Pei³

1.Chinese Academy of Sciences University,Beijing 100049,China;
2.Institute of Porous Flow and Fluid Mechanics,Chinese Academy of Sciences,Langfang 065007,China;
3.China Petroleum Exploration and Development Research Institute,Beijing 100083,China

Received:2018-08-12 Revised:2018-10-31 Online:2019-03-10

摘要/Abstract

摘要： 四川盆地威远地区内部钻井少，仅靠岩心实测和测井计算的TOC含量评价该区页岩气资源潜力难度较大，利用地震资料预测页岩TOC 含量不但能弥补该区钻井取心少的不足，而且能够评价无井地区页岩的TOC含量。以四川盆地威远地区W201井区三维五峰组—龙马溪组一段1亚段为例，利用钻测井及三维地震资料定量预测了页岩TOC含量的平面及空间分布。首先通过测井计算得到的TOC与地球物理参数交会分析，优选出敏感参数密度，在此基础上，分析该区钻井岩心实测和测井计算的TOC含量与密度的关系，得到计算TOC含量的地震预测模型，然后利用叠前同时反演技术获得该区的密度体，通过预测模型最终实现页岩TOC含量的定量预测。结果表明：①地震预测的TOC与岩心实测和测井计算TOC结果较为吻合，误差较小；②研究区东南部及北部W201井区TOC含量较高，平均值可达2%~4%，为勘探开发有利区。结论认为，该TOC定量预测方法对于研究区适用有效，且对川南地区页岩气勘探开发评价具有一定的指导意义。

关键词: 威远地区, 龙马溪组, TOC, 地震预测, 岩石物理分析, 叠前反演

Abstract: There is less internal drilling in the Weiyuan area of the Sichuan Basin.It is difficult to evaluate the shale gas resource potential in the area by the TOC content of the core measurement and logging calculation.Using seismic data to predict shale TOC content can not only make up for the lack of drilling cores,but also can evaluate the TOC content of shale in well-free areas.Taking the 1st section of the Wufeng Formation-Longmaxi Formation in the Weiyuan area of the Sichuan Basin as an example,the plane and spatial distribution of shale TOC content were quantitatively predicted by drilling logging and 3D seismic data.Firstly,the TOC and geophysical parameters obtained by logging calculation are analyzed,and the density of sensitive parameters is optimized.On the basis of this,the relationship between the TOC content and the density of the core measurement and logging calculation of the vertical well in the area is analyzed,and the TOC content is calculated by seismic prediction model.Then,the density of the area is obtained by pre-stack simultaneous inversion technique,and the quantitative prediction of shale TOC is finally realized by the prediction model.The results show that:(1)The TOC of seismic prediction is in good agreement with the core measurement and log calculation TOC results,and the error is small.(2)The TOC in the southeastern part of the study area and the Well W210 area in the north is higher,with an average value of 2%-4%,which is a favorable area for exploration and development.It is concluded that the TOC quantitative prediction method is effective for the study area and has certain reference significance for the evaluation of shale gas exploration and development in southern Sichuan.

Key words: Weiyuan area, Longmaxi Formation, TOC, Seismic prediction, Petrophysical analysis, Prestack inversion

中图分类号:

TE132.1

邓宇, 曾庆才, 陈胜, 管全中, 郭晓龙, 贺佩. 四川盆地威远地区五峰组—龙马溪组页岩TOC含量地震定量预测方法及应用[J]. 天然气地球科学, 2019, 30(3): 414–422.

Deng Yu, Zeng Qing-cai, Chen Sheng, Guan Quan-zhong, Guo Xiao-long, He Pei. Seismic quantitative prediction method and application of TOC content in Wufeng-Longmaxi Formations shale reservoirs in Weiyuan area,Sichuan Basin[J]. Natural Gas Geoscience, 2019, 30(3): 414–422.

参考文献

［1］Bie Fan,Wan Yu,Nie Xin,et al.A new method of TOC content evaluation in shale gas reservoirs with log data[J].Logging Technology,2016,40(6):736-738.
别凡,万宇,聂昕,等.页岩气储层总有机碳含量测井评价新方法[J].测井技术,2016,40(6):736-738.
[2]Chen Chao,Liu Yun,Wang Mingfei,et al.Research on shale TOC content prediction techniques and contrast in Jiaoshiba area[J].Journal of Chengdu University of Technology ：Natural Science Edition,2016,43(1):51-58.
陈超,刘韵,王明飞,等.焦石坝地区泥页岩有机碳含量预测技术及对比[J].成都理工大学学报：自然科学版,2016,43(1):51-58.
Wang Feiyu,Guan Jing,Feng Weiping,et al.Evolution of overmature marine shale porosity and implication to the free gas volume[J].Petroleum Exploration and Development,2013,40(6):764-768.
王飞宇,关晶,冯伟平,等.过成熟海相页岩孔隙度演化特征和游离气量[J].石油勘探与开发,2013,40(6):764-768.
[4]China National Standardization Administration Committee.National Standard GB/T 19145-2003 Determination of Total Organic Carbon in Sedimentary Rocks[S].Beijing:China Standard Press,2003.
中国国家标准化管理委员会.国家标准GB/T 19145-2003沉积岩中总有机碳的测定[S].北京:中国标准出版社,2003.
[5]China National Standardization Administration Committee.National Standard GB/T 18602-2001 Rock Pyrolysis Analysis[S].Beijing:China Standard Press,2002.
中国国家标准化管理委员会.国家标准GB/T 18602-2001 岩石热解分析[S].北京:中国标准出版社,2002.
[6]Huang Renchun,Wang Yan,Cheng Sijie,et al.Optimal selection of logging-based TOC calculation method of shale reservoirs:A case study of the Jiaoshiba shale gas field,Sichuan Basin[J].Natural Gas Industry,2014,34(12):25-32.
黄仁春,王燕,程斯洁,等.利用测井资料确定页岩储层有机碳含量的方法优选——以焦石坝页岩气田为例[J].天然气工业,2014,34(12):25-32.
[7]Schmoker J W,Hester T C.Organic-carbon in Bakken Formation,United-States portion of Williston Basin[J].AAPG Bulletin,1983,67(12):2165-2174.
[8]Liu Xiaowei,Cui Yue,Geng Yi.Effect factors and forecasting techniques of TOC content in shale gas reservoir[J].Liaoning Chemical Industry,2015,44(3):267-270.
刘笑伟,崔跃,耿懿.页岩气储层总有机碳含量的影响因素及预测技术[J].辽宁化工,2015,44(3):267-270.
[9]Yang Shaochun,Wang Na,Li Mingrui,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,2013,24(3):470-476.
杨少春,王娜,李明瑞,等.鄂尔多斯盆地崇信地区三叠系延长组烃源岩测井评价[J].天然气地球科学,2013,24(3):470-476.
[10]Meng Zhaoping,Guo Yansheng,Liu Wei.Relationship between organic carbon content of shale gas reservoir and logging parameters and its prediction model[J].Journal of Coal,2015,40(2):247-253.
孟召平,郭彦省,刘尉.页岩气储层有机碳含量与测井参数的关系及预测模型[J].煤炭学报,2015,40(2):247-253.
[11]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 & Engineering,2004,45(3):141-148.
[12]Huang Z,Williamson M A.Artificial neural network modeling as an aid to source rock characterization[J].Marine and Petroleum Geology,1996,13(2):277-290.
[13]Yang Taotao,Fan Guozhang,Lv Fuliang,et al.The logging features and identification methods of source rock[J].Natural Gas Geoscience,2013,24(2):414-422.
杨涛涛，范国章，吕福亮，等.烃源岩测井响应特征及识别评价方法[J].天然气地球科学，2013，24(2)：414-422.
[14]Jia J,Liu Z,Meng Q,et al.Quantitative evaluation of oil shale based on well log and 3-D seismic technique in the Songliao Basin,northeast China[J].Oil Shale,2012,29(2):128-150.
[15]Lashin A,Mogren S.Total organic carbon enrichment and source rock evaluation of the Lower Miocene rocks based on well logs:October Oil Field,Gulf of Suez-Egypt[J].International Journal of Geosciences,2012,3(4):683-695.
[16]Zhu Guangyou,Jin Qiang.Evaluation of geochemical characteristics of source rocks using logging information[J].Geoscience Frontiers,2003,10(2):494.
朱光有,金强.利用测井信息评价烃源岩的地球化学特征[J].地学前缘,2003,10(2):494.
[17]Xu Sihuang,Zhu Yiqing.Logging response characteristics and quantitative prediction model of organic carbon content in source rocks:A case study of the Wenchang Formation source rocks in the Pearl River Basin[J].Petroleum Geology & Experiment,2012,32(3):290-295,300.
徐思煌，朱义清.烃源岩有机碳含量的测井响应特征与定量预测模型——以珠江盆地文昌组烃源岩为例[J].石油实验地质，2012，32(3)：290-295,300.
[18]Chen Kegui,Li Min,Tan Bisheng,et al.Logging identification and evaluation of Cambrian-Ordovician source rocks in syneclise of Tarim Basin[J].Advances in Geophysics,2017,32(1):114-119.
陈科贵,李民,谭必生,等.牛庄洼陷烃源岩TOC新型测井多参数复合评价方法研究[J].地球物理学进展,2017,32(1):114-119.
[19]Dong Guoliang.Evaluation of Chang 7 Shale Reservoir in Yanchang Formation,Zhenyu Block,Ordos Basin[D].Chengdu:Chengdu University of Technology,2012.
董国良.鄂尔多斯盆地镇泾区块延长组长7页岩储层评价[D].成都:成都理工大学,2012.
[20]Passey Q R,Moretti F J,Kulla J B,et al.Practical model for organic richness from porosity and resistivity logs[J].AAPG Bulletin,1990,74(12):1777-1794.
[21]Li Yanjun,Zhang Liehui,Feng Yuanyuan,et al.Logging evaluation method and its application for measuring the total organic carbon content in shale gas[J].Natural Gas Geoscience,2013,24(1):169-175.
李延钧,张烈辉,冯媛媛,等.页岩有机碳含量测井评价方法及其应用[J].天然气地球科学,2013,24(1):169-175.
[22]Liu Chao,Yin Changhai,Lu Shuangfang.Prediction key parameters for variable-coefficient ΔlgR logging technique and its application in source rocks evaluation[J].Natural Gas Geoscience,2015,26(10):1925-1931.
刘超,印长海,卢双舫.变系数ΔLgR烃源岩测井评价技术关键参数厘定方法及应用[J].天然气地球科学,2015,26(10):1925-1931.
[23]Wang Jian,Shi Wanzhong,Shu Zhiguo,et al.Geophysical quantitative prediction of TOC content in organic matter shale[J].Petroleum Geophysical Prospecting,2016,51(3):596-604.
王健,石万忠,舒志国,等.富有机质页岩TOC含量的地球物理定量化预测[J].石油地球物理勘探,2016,51(3):596-604.
[24]Jin Jineng,Pan Renfang,Wang Peng,et al.Seismic multi-attribute inversion to predict total organic carbon content in shale[J].Journal of Oil and Gas,2012,34(11):68-72.
金吉能,潘仁芳,王鹏,等.地震多属性反演预测页岩总有机碳含量[J].石油天然气学报,2012,34(11):68-72.
[25]Yan Jun,Yan Wenfen,Lin Lin,et al.Seismic prediction of quality mud shale in Da’anzhai Formation of Fuling area[J].Fault Block Oil and Gas Field,2015,22(3):335-337.
严俊,严文芬,林琳,等.涪陵地区大安寨段优质泥页岩地震预测[J].断块油气田,2015,22(3):335-337.
[26]Xu Jie,He Zhiliang,Dong Ning,et al.Geophysical prediction of organic carbon content in gas-bearing shale[J].Petroleum Geophysical Prospecting,2013,48(supplement 1):64-68.
许杰,何治亮,董宁,等.含气页岩有机碳含量地球物理预测[J].石油地球物理勘探,2013,48(增刊1):64-68.
[27]Han Bing,Sun Weichao.Geophysical prediction of organic carbon content in Jiaoshiba shale[J].Journal of Hebei University of Geosciences,2017,40(6):8-12.
韩冰,孙伟超.焦石坝页岩有机碳含量地球物理预测[J].河北地质大学学报,2017,40(6):8-12.
[28]Lu Minghua,Luo Pu,Jiang Chuanfang,et al.Application of seismic attribute technology in shale fracture prediction[J].Journal of Oil and Gas Technology,2013,35(8):62-64.
陆明华,骆璞,姜传芳,等.地震属性技术在页岩裂缝预测中的应用[J].石油天然气学报,2013,35(8):62-64.
[29]Chen Zuqing.Quantitative prediction technology of marine shale TOC seismic and its application:A case study of Jiaoshiba area in Sichuan Basin[J].Nature Gas Industry,2014,34(6):24-29.
陈祖庆.海相页岩TOC地震定量预测技术及其应用——以四川盆地焦石坝地区为例[J].天然气工业,2014,34(6):24-29.
[30]Guo Xusheng,Yin Zhengwu,Li Jinlei.Quantitative prediction technology of marine shale gas content and its application:A case study of Jiaoshiba area in Sichuan Basin[J].Petroleum Geophysical Prospecting,2015,50(1):144-149.
郭旭升,尹正武,李金磊.海相页岩含气量地震定量预测技术及其应用——以四川盆地焦石坝地区为例[J].石油地球物理勘探,2015,50(1):144-149.
[31]Yuan Shujin.Progress of pre-stack inversion and application in exploration of the lithological reservoirs[J].Advances in Geophysics,2007,22(3):879-886.
苑书金.叠前地震反演技术的进展及其在岩性油气藏勘探中的应用[J].地球物理学进展,2007,22(3):879-886.
[32]Su Jianlong,Qu Dapeng,Chen Chao,et al.Comparative analysis of prestack seismic inversion methods:Exploration of shale gas reservoirs in Jiaoshiba[J].Petroleum Geophysical Prospecting,2016,51(3):581-588.
苏建龙，屈大鹏，陈超，等.叠前地震反演方法对比分析——焦石坝页岩气藏勘探实例[J].石油地球物理勘探,2016,51(3):581-588.
[33]Chen Sheng,Zhao Wenzhi,Ouyang Yonglin,et al.Comprehensive prediction of shale gas sweet spots based on geophysical properties:A case study of the Lower Silurian Longmaxi Formation in Changning block,Sichuan Basin[J].Natural Gas Industry,2017,37(5):20-30.
陈胜,赵文智,欧阳永林,等.利用地球物理综合预测方法识别页岩气储层甜点——以四川盆长宁区块下志留统龙马溪组为例[J].天然气工业,2017,37(5):20-30.

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