页岩岩相的测井曲线识别方法——以焦石坝地区五峰组-龙马溪组为例

doi:10.12108/yxyqc.20210214

岩性油气藏 ›› 2021, Vol. 33 ›› Issue (2): 135–146.doi: 10.12108/yxyqc.20210214

页岩岩相的测井曲线识别方法——以焦石坝地区五峰组-龙马溪组为例

杨洋¹, 石万忠^1,2, 张晓明¹, 王任^1,2, 徐笑丰¹, 刘俞佐¹, 白卢恒¹, 曹沈厅¹, 冯芊¹

1. 中国地质大学 (武汉)资源学院, 武汉 430074;
2. 中国地质大学 (武汉)教育部构造与油气资源重点实验室, 武汉 430074

收稿日期:2020-05-21 修回日期:2020-07-13 出版日期:2021-04-01 发布日期:2021-03-31
第一作者:杨洋(1995—),男,中国地质大学(武汉)在读硕士研究生,研究方向为页岩气储层地质。地址:(430074)湖北省武汉市洪山区鲁磨路388号。Email:youngyoung@cug.edu.cn
通信作者: 石万忠(1973—),男,博士,教授,博士生导师,主要从事层序地层学与成藏动力学及页岩气方面的教学和科研工作。Email:shiwz@cug.edu.cn。
基金资助:
国际科技创新合作重点专项“中美石炭-二叠系页岩储层评价技术合作研究”（编号：2017YFE0106300）和国家自然科学基金项目“页岩气储层总孔隙度表征及预测”（编号：41672134）和国家“十三五”科技重大专项“页岩气区域选区评价方法研究”（编号：2016ZX05034-002-003）联合资助

Identification method of shale lithofacies by logging curves: a case study from Wufeng-Longmaxi Formation in Jiaoshiba area,SW China

YANG Yang¹, SHI Wanzhong^1,2, ZHANG Xiaoming¹, WANG Ren^1,2, XU Xiaofeng¹, LIU Yuzuo¹, BAI Luheng¹, CAO Shenting¹, FENG Qian¹

1. School of Earth Resources, China University of Geosciences(Wuhan), Wuhan 430074, China;
2. Key Laboratory of Tectonics and Petroleum Resources, Ministry of Education, China University of Geosciences(Wuhan), Wuhan 430074, China

Received:2020-05-21 Revised:2020-07-13 Online:2021-04-01 Published:2021-03-31

摘要/Abstract

摘要： 页岩岩相的识别是页岩气勘探开发的基础工作，不同类型页岩具有不同物质组分与组构，进而具有不同的脆性度和物性，目前利用测井曲线来识别页岩岩相的研究较为薄弱。以焦石坝地区五峰组—龙马溪组3口井的测井资料、岩心测试数据为基础，通过多参数优选、多元线性拟合，分别建立了黏土矿物、硅质矿物相对含量的预测方程，探讨利用测井曲线识别页岩的方法。结果表明：黏土质页岩具有高DEN，CNL，K，KTh，低U，U/Th的特征；混合质页岩具有中DEN，U，CNL，K，KTh，U/Th的特征；硅质页岩具有高U，U/TH，低DEN，CNL，K，KTh的特征，并以此为依据，建立了页岩岩相识别雷达图版，不同岩相所对应的测井曲线数值在图版中有不同的分布范围，该图版可以有效识别页岩岩相，并能够对预测方程识别错误的岩相进行纠正，预测结果与实测值吻合度高。将预测方程定量识别岩相和雷达图版定性识别岩相结合起来，通过双重约束，可以很好地识别焦石坝地区五峰组—龙马溪组页岩岩相。

关键词: 页岩, 岩相识别, 测井, 雷达图, 五峰组—龙马溪组, 焦石坝地区

Abstract: Identification of shale lithofacies is the basis of shale gas exploration and development. Different types of shale have different material components and textures,and thus the brittleness and physical properties are different. At present,the study on shale lithofacies identification by logging curves is relatively weak. Based on logging data and core test data of three wells from Wufeng-Longmaxi Formation in Jiaoshiba area,through multi-parameter optimization and multivariate linear fitting,the prediction equations of relative content of clay minerals and siliceous minerals were established respectively,and the identification method of shale lithofacies by logging curves was discussed. The results show that argillaceous shale lithofacies has the characteristics of high DEN,CNL,K,KTh,and low U,U/Th,the mixed shale lithofacies has the characteristics of middle DEN, CNL,K,KTh,U,U/Th,and siliceous shale lithofacies has the characteristics of high U,U/Th and low DEN, CNL,K,KTh. Furthermore,a radar chart for shale facies identification was established. After corresponding processing,the logging curve values corresponding to different lithofacies have different distribution ranges in the chart. The chart can effectively identify shale lithofacies and correct the lithofacies identified by the prediction equation. The predicted results are in agreement with the measured values. Combining quantitative identification of lithofacies by prediction equation and qualitative identification of lithofacies by radar chart,shale lithofacies of Wufeng-Longmaxi Formation in Jiaoshiba area can be well identified through double constraints.

Key words: shale, lithofacies identification, logging, radar chart, Wufeng-Longmaxi Formation, Jiaoshiba area

中图分类号:

TE122.1

杨洋, 石万忠, 张晓明, 王任, 徐笑丰, 刘俞佐, 白卢恒, 曹沈厅, 冯芊. 页岩岩相的测井曲线识别方法——以焦石坝地区五峰组-龙马溪组为例[J]. 岩性油气藏, 2021, 33(2): 135–146.

YANG Yang, SHI Wanzhong, ZHANG Xiaoming, WANG Ren, XU Xiaofeng, LIU Yuzuo, BAI Luheng, CAO Shenting, FENG Qian. Identification method of shale lithofacies by logging curves: a case study from Wufeng-Longmaxi Formation in Jiaoshiba area,SW China[J]. Lithologic Reservoirs, 2021, 33(2): 135–146.

参考文献

[1] HICKEY J J, HENK B. Lithofacies summary of the Mississippian Barnett Shale, Mitchell 2 T. P. Sims well, Wise county, Texas. AAPG Bulletin, 2007, 91(4):437-443.
[2] SIMENSON A. Depositional facies and petrophysical analysis of the Bakken Formation, Parshall Field,Mountrail county, North Dakota. Golden, Colorado:Colorado School of Mines, 2009:1-198.
[3] ALSHAHRANI S S. Depositional environment, history, diagenesis and petroleum geology of the Cleveland shale member, northeastern Ohio. Bowling Green, Ohio:Bowling Green State University, 2013:1-190.
[4] POTMA K, JONK R, DAVIE M, et al. A mudstone lithofacies classification of the Horn River Group:Integrated stratigraphic analysis and inversion from wireline log and seismic data proceedings of sixth BC unconventional gas technical forum. Victoria:GeoConvention, 2012:1-3.
[5] 梁超, 姜在兴, 杨镱婷, 等.四川盆地五峰组-龙马溪组页岩岩相及储集空间特征. 石油勘探与开发, 2012, 39(6):691-698. LIANG C, JIANG Z X, YANG Y T, et al. Characteristics of shale lithofacies and reservoir space of the Wufeng-Longmaxi Formation, Sichuan Basin. Petroleum Exploration and Development, 2012, 39(6):691-698.
[6] 郭彤楼, 张汉荣.四川盆地焦石坝页岩气田形成与富集高产模式.石油勘探与开发, 2014, 41(1):28-36. GUO T L, ZHANG H R. Formation and enrichment model of Jiaoshiba shale gas field, Sichuan Basin. Petroleum Exploration and Development, 2014, 41(1):28-36.
[7] 吴蓝宇, 胡东风, 陆永潮, 等.四川盆地涪陵气田五峰组-龙马溪组页岩优势岩相. 石油勘探与开发, 2016, 43(2):189-197. WU L Y, HU D F, LU Y C, et al. Advantageous shale lithofacies of Wufeng Formation-Longmaxi Formation in Fuling gas field of Sichuan Basin, SW China. Petroleum Exploration and Development, 2016, 43(2):189-197.
[8] 王玉满, 王淑芳, 董大忠, 等.川南下志留统龙马溪组页岩岩相表征.地学前缘, 2016, 23(1):119-133. WANG Y M, WANG S F, DONG D Z, et al. Lithofacies characterization of Longmaxi Formation of the Lower Silurian, southern Sichuan. Earth Science Frontiers, 2016, 23(1):119-133.
[9] 王志峰, 张元福, 梁雪莉, 等.四川盆地五峰组-龙马溪组不同水动力成因页岩岩相特征. 石油学报, 2014, 35(4):623-632. WANG Z F, ZHANG Y F, LIANG X L, et al. Characteristics of shale lithofacies formed under different hydrodynamic conditions in the Wufeng-Longmaxi Formation, Sichuan Basin. Acta Petrolei Sinica, 2014, 35(4):623-632.
[10] LIU S G, MA W X, JANSA L, et al. Characteristics of the shale gas reservoir rocks in the Lower Silurian Longmaxi Formation, east Sichuan Basin, China. Energy Exploration & Exploitation, 2013, 31(2):187-219.
[11] 冉波, 刘树根, 孙玮, 等.四川盆地及周缘下古生界五峰组-龙马溪组页岩岩相分类.地学前缘, 2016, 23(2):96-107. RAN B, LIU S G, SUN W, et al. Lithofacies classification of shales of the Lower Paleozoic Wufeng-Longmaxi Formations in the Sichuan Basin and its surrounding areas, China. Earth Science Frontiers, 2016, 23(2):96-107.
[12] 邹才能, 董大忠, 王社教, 等.中国页岩气形成机理、地质特征及资源潜力.石油勘探与开发, 2010, 37(6):641-653 ZOU C N, DONG D Z, WANG S J, et al. Geological characteristics, formation mechanism and resource potential of shale gas in China. Petroleum Exploration and Development, 2010, 37(6):641-653.
[13] JIANG Z X, GUO L, LIANG C. Lithofacies and sedimentary characteristics of the Silurian Longmaxi shale in the southeastern Sichuan Basin, China. Journal of Palaeogeography, 2013, 2(3):238-251.
[14] 郑和荣, 高波, 彭勇民, 等.中上扬子地区下志留统沉积演化与页岩气勘探方向.古地理学报, 2013, 15(5):645-656 ZHENG H R, GAO B, PENG Y M, et al. Sedimentary evolution and shale gas exploration direction of the Lower Silurian in Middle-Upper Yangtze area. Journal of Palaeogeography, 2013, 15(5):645-656.
[15] 王泽华, 朱筱敏, 孙中春, 等.测井资料用于盆地中火成岩岩性识别及岩相划分:以准噶尔盆地为例.地学前缘, 2015, 22(3):254-268. WANG Z H, ZHU X M, SUN Z C, et al. Igneous lithology identification and lithofacies classification in the basin using logging data:Taking Junggar Basin as an example. Earth Science Frontiers, 2015, 22(3):254-268.
[16] 周正龙, 王贵文, 冉治, 等.致密油储集层岩性岩相测井识别方法:以鄂尔多斯盆地合水地区三叠系延长组7段为例.石油勘探与开发, 2016, 43(1):61-69. ZHOU Z L, WANG G W, RAN Z, et al. A logging identification method of tight oil reservoir lithology and lithofacies:a case from Chang 7 member of Triassic Yanchang Formation in Heshui area, Ordos Basin, NW China. Petroleum Exploration and Development, 2016, 43(1):61-69.
[17] 车世琦.测井资料用于页岩岩相划分及识别:以涪陵气田五峰组-龙马溪组为例.岩性油气藏, 2018, 30(1):121-132. CHE S Q. Shale lithofacies identification and classification by using logging data:a case of Wufeng-Longmaxi Formation in Fuling gas field, Sichuan Basin. Lithologic Reservoirs, 2018, 30(1):121-132.
[18] 王敏, 朱家俊, 余光华, 等.罗家地区泥页岩岩相特征及测井分析技术.测井技术,2013,37(4):426-431. WANG M, ZHU J J, YU G H, et al. The shale lithofacies characteristics and logging analysis techniques in Luojia area. Well Logging Technology, 2013, 37(4):426-431.
[19] 张超, 张立强, 陈家乐, 等.渤海湾盆地东营凹陷古近系细粒沉积岩岩相类型及判别.天然气地球科学, 2017, 28(5):713-723. ZHANG C, ZHANG L Q, CHEN J L, et al. Lithofacies types and discrimination of Paleogene fine-grained sedimentary rocks in the Dongying Sag, Bohai Bay Basin, China. Natural Gas Geoscience, 2017, 28(5):713-723.
[20] HE J H, DING W L, JIANG Z X, et al. Logging identification and characteristic analysis of the lacustrine organic-rich shale lithofacies:a case study from the Es₃L shale in the Jiyang Depression, Bohai Bay Basin, Eastern China. Journal of Petroleum Science & Engineering, 2016, 145:238-255.
[21] 操应长, 葸克来, 赵贤正, 等.廊固凹陷沙四上亚段储层成岩相及其测井识别.中南大学学报(自然科学版), 2015, 46(11):4183-4194. CAO Y C, XI K L, ZHAO X Z, et al. Reservoir diagenetic facies and its logging identification of Es4s in Langgu Sag. Journal of Central South University(Science and Technology), 2015, 46(11):4183-4194.
[22] 范宜仁, 李菲, 邓少贵, 等.致密砂岩储层成岩相特征分析及测井识别.测井技术, 2018,42(3):307-314. FAN Y R, LI F, DENG S G, et al. Characteristics analysis of diagenetic facies in tight sandstone reservoir and its logging identification. Well Logging Technology, 2018, 42(3):307-314.
[23] 祝鹏, 林承焰, 吴鹏, 等.基于主成分分析法的成岩相测井定量识别:以五号桩油田桩62-66块沙三下Ⅰ油组储层为例. 地球物理学进展, 2015, 30(5):2360-2365. ZHU P, LIN C Y, WU P, et al. Logging quantitative identification of diagenetic facies by using principal component analysis:a case of Es₃x¹ in Zhuang 62-66 area, Wuhaozhuang oilfeild. Progress in Geophysics(in Chinese), 2015, 30(5):2360-2365.
[24] 朱怡翔, 石广仁.火山岩岩性的支持向量机识别.石油学报, 2013, 34(2):312-322. ZHU Y X, SHI G R. Identification of lithologic characteristics of volcanic rocks by support vector machine. Acta Petrolei Sinica, 2013, 34(2):312-322.
[25] 牟丹, 王祝文, 黄玉龙, 等.基于SVM测井数据的火山岩岩性识别:以辽河盆地东部坳陷为例. 地球物理学报, 2015, 58(5):1785-1793. MOU D, WANG Z W, HUANG Y L, et al. Lithological identification of volcanic rocks from SVM well logging data:a case study in the eastern depression of Liaohe Basin. Chinese Journal of Geophysics(in Chinese), 2015, 58(5):1785-1793.
[26] 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.岩性油气藏, 2019, 31(4):101-111. LIU Y J, LIU S Q, MA Q, et al. Application of BP neutral network method to identification of shale lithofacies of Lucaogou Formation in Santanghu Basin. Lithologic Reservoirs, 2019, 31(4):101-111.
[27] CORINA A N, HOVDA S. Automatic lithology prediction from well logging using kernel density estimation. Journal of Petroleum Science and Engineering, 2018, 170:664-674.
[28] LOPES D M R, ANDRADE A J N. Lithology identification on well logs by fuzzy inference. Journal of Petroleum Science and Engineering, 2019, 180:357-368.
[29] ASOODEH M, BAGHERIPOUR P. Fuzzy classifier based support vector regression framework for Poisson ratio determination. Journal of Applied Geophysics, 2013, 96:7-10.
[30] SAGGAF M M, NEBRIJA E L. A fuzzy logic approach for the estimation of facies from wire-line logs. AAPG Bulletin, 2003, 87(7):1223-1240.
[31] 李湘涛, 石文睿, 郭美瑜, 等.涪陵页岩气田焦石坝区海相页岩气层特征研究.石油天然气学报, 2014, 36(11):11-15. LI X T, SHI W R, GUO M Y, et al. Characteristics of marine shale gas reservoirs in Jiaoshiba area of Fuling shale gas field. Journal of Oil and Gas Technology, 2014, 36(11):11-15.
[32] 申宝剑, 仰云峰, 腾格尔, 等. 四川盆地焦石坝构造区页岩有机质特征及其成烃能力探讨:以焦页1井五峰-龙马溪组为例. 石油实验地质, 2016, 38(4):480-495. SHEN B J, YANG Y F, TENG G E, et al. Characteristics and hydrocarbon significance of organic matter in shale from the Jiaoshiba structure, Sichuan Basin:a case study of the Wufeng-Longmaxi formations in well Jiaoye 1. Petroleum Geology & Experiment, 2016, 38(4):480-495.
[33] 张晓明, 石万忠, 徐清海, 等.四川盆地焦石坝地区页岩气储层特征及控制因素.石油学报, 2015, 36(8):926-939. ZHANG X M, SHI W Z, XU Q H, et al. Reservoir characteristics and controlling factors of shale gas in Jiaoshiba area, Sichuan Basin. Acta Petrolei Sinica, 2015, 36(8):926-939.
[34] 佘晓宇, 陈洁, 张士万, 等.焦石坝地区中、古生界构造特征及其页岩气地质意义. 石油与天然气地质, 2016, 37(6):828-837. SHE X Y, CHEN J, ZHANG S W, et al. Tectonic characteristics and their shale gas geological significance of the MesozoicPaleozoic in Jiaoshiba area, the Sichuan Basin. Oil & Gas Geology, 2016, 37(6):828-837.
[35] 庹秀松, 陈孔全, 罗顺社, 等.渝东大焦石坝地区差异构造变形.石油与天然气地质, 2019, 40(5):1074-1083. TUO X S, CHEN K Q, LUO S S, et al. Differential structural deformation of the Dajiaoshiba area, east Chongqing. Oil & Gas Geology, 2019, 40(5):1074-1083.
[36] 陆扬博, 马义权, 王雨轩, 等.上扬子地区五峰组-龙马溪组主要地质事件及岩相沉积响应.地球科学, 2017, 42(7):1169-1184. LU Y B, MA Y Q, WANG Y X, et al. The sedimentary response to the major geological events and lithofacies characteristics of Wufeng Formation-Longmaxi Formation in the Upper Yangtze area. Earth Science, 2017, 42(7):1169-1184.
[37] 王超, 张柏桥, 陆永潮, 等.焦石坝地区五峰组-龙马溪组一段页岩岩相展布特征及发育主控因素. 石油学报, 2018, 39(6):631-644. WANG C, ZHANG B Q, LU Y C, et al. Lithofacies distribution characteristics and main development controlling factors of shale in Wufeng Formation-member 1 of Longmaxi Formation in Jiaoshiba area. Acta Petrolei Sinica, 2018, 39(6):631-644.
[38] 张晓明, 石万忠, 舒志国, 等.涪陵地区页岩含气量计算模型及应用.地球科学, 2017, 42(7):1157-1168. ZHANG X M, SHI W Z, SHU Z G, et al. Calculation model of shale gas content and its application in Fuling area. Earth Science, 2017, 42(7):1157-1168.
[39] 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.石油地球物理勘探, 2016, 51(3):596-604. WANG J, SHI W Z, SHU Z G, et al. TOC content quantitative prediction in organic-rich shale. Oil Geophysical Prospecting, 2016, 51(3):596-604.
[40] 徐壮, 石万忠, 翟刚毅, 等.涪陵地区页岩总孔隙度测井预测. 石油学报, 2017, 38(5):533-543. XU Z, SHI W Z, ZHAI G Y, et al. Well logging prediction for total porosity of shale in Fuling area. Acta Petrolei Sinica, 2017, 38(5):533-543.
[41] 严伟,刘帅,冯明刚, 等. 四川盆地丁山区块页岩气储层关键参数测井评价方法. 岩性油气藏, 2019, 31(3):95-104. YAN W, LIU S, FENG M G, et al. Well logging evaluation methods of key parameters for shale gas reservoir in Dingshan block, Sichuan Basin. Lithologic Reservoirs, 2019, 31(3):95-104.
[42] 赵万金, 高海燕, 闫国亮, 等.基于最优化估算和贝叶斯统计的TOC预测技术. 岩性油气藏, 2020, 32(1):86-93. ZHAO W J, GAO H Y, YAN G L, et al. TOC prediction technology based on optimal estimation and Bayesian statistics. Lithologic Reservoirs, 2020, 32(1):86-93.
[43] 蒋德鑫, 姜正龙, 张贺, 等. 烃源岩总有机碳含量测井预测模型探讨:以陆丰凹陷文昌组为例. 岩性油气藏, 2019, 31(6):109-117. JIANG D X, JIANG Z L, ZHANG H, et al. Well logging prediction models of TOC content in source rocks:a case of Wenchang Formation in Lufeng Sag. Lithologic Reservoirs, 2019, 31(6):109-117.
[44] 白烨.鄂尔多斯盆地测井成岩相判别.长春:吉林大学, 2013. BAI Y. Method of well-logging diagenetic facies identification in the Ordos Basin. Changchun:Jilin University, 2013.
[45] JONES B, MANNING D A C. Comparison of geochemical indices used for the interpretation of palaeoredox conditions in ancient mudstones. Chemical Geology, 1994, 111:111-129.
[46] PATTAN J N, PEARCE N J G, MISLANKAR P G. Constraints in using cerium-anomaly of bulk sediments as an indicator of paleobottom water redox environment:a case study from the Central Indian Ocean Basin. Chemical Geology, 2005, 221:260-278.
[47] TIAN D, HE S, CHEN M F, et al. Quartz types and origins in the Paleozoic Wufeng-Longmaxi Formations, eastern Sichuan Basin, China:Implications for porosity preservation in shale reservoirs. Marine and Petroleum Geology, 2019, 106:62-73.
[48] 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.石油物探, 2018, 57(6):803-812. QIN J Q, FU D L, QIAN Y F, et al. Progress of geophysical methods for the evaluation of TOC of source rock. Geophysical Prospecting for Petroleum, 2018, 57(6):803-812.
[49] 崔玉峰. 致密砂岩储层成岩相测井表征方法及应用:以鄂尔多斯盆地合水地区长7段为例.青岛:中国石油大学(华东), 2017. CUI Y F. Prediction of diagenetic facies using well logs and its application:a case study from the Chang 7 member in Heshui field, Ordos Basin. Qingdao:China University of Petroleum(East China), 2017.

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页岩岩相的测井曲线识别方法——以焦石坝地区五峰组-龙马溪组为例

Identification method of shale lithofacies by logging curves: a case study from Wufeng-Longmaxi Formation in Jiaoshiba area,SW China

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