烃源岩测井定量评价方法探讨
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摘要
烃源岩评价是油气地质研究最重要的基础工作之一.岩心分析数据量往往有限,难以满足勘探的需求;测井资料经分析数据标定后能获得连续的烃源岩指标数据,应用较广泛.文中阐述了烃源岩总有机碳含量(TOC)、热解生烃潜量(S_1+S_2)和成熟度三个指标的测井定量评价方法;在孟加拉湾海域试用并对计算效果进行分析.首先详细地阐述了单因素法、多元回归法、ΔLgR法和神经网络法等4种常用TOC测井计算方法的原理及优缺点;其次介绍了TOC相关法、多元回归法和神经网络法等3种常用S_1+S_2计算方法原理及优缺点;再次介绍了镜质体反射率和剩碳率法等2种成熟度评价方法.结合研究区地质条件对定量计算效果进行分析,TOC计算结果对比表明神经网络法效果最好,多元回归法次之,ΔLgR法较差,单因素法最差.分析认为TOC较低对测井响应贡献小,单条曲线与TOC相关性低导致单因素法效果差;多元回归法考虑了多条曲线效果较好;ΔLgR法由于缺乏厚层泥岩段及热变指数难选取,效果较差;神经网络法在非线性、难用显示表达式的计算问题方面具有很大的优越性,计算效果最佳.S_1+S_2计算结果对比表明TOC相关法计算结果最优,多元回归法效果一般,神经网络法效果最差.分析认为S_1+S_2与TOC有成因联系计算效果好;S_1+S_2对测井响应贡献小,因此多元回归法和神经网络法效果都不好.成熟度评价的镜质体反射率与深度相关性好,最为常用;剩碳率法部分参数在勘探早期难取准,应用受限.
Identification and evaluation of source rock is the basis of geological study for hydrocarbon. Limited core samples restrained the demand of exploration. After calibration of analysis data,logging data can provide continuous hydrocarbon source rocks index,and it's widely used. Three Logging quantitative evaluation method were discussed in the paper including the content of Total Organic Carbon( TOC), the amount of pyrolysis hydrocarbon generation potential( S_1+S_2) and the maturity indicators. These methods were tried in Bengal bay, and combined with block geological conditions the calculation results were analyzed. First,four kinds of calculation methods for the TOC including single factor method,multiple regression method,ΔLgR method and the neural network were described in detail,as far as principles,advantages and disadvantages. What 's more, two methods including the vitrinite reflectance and residual carbon ratio for maturity evaluation were introduced. Finally,the quantitative calculation results in the study area were analyzed. TOC calculation results shows that the neural network was best,multivariate regression method was the second,ΔLgR method was poorer,and single factor method was the worst. Analysis shows the low TOC contributed little to the logging response,bad correlation between a single curve and TOC lead to poor effect of single factor method. As considering multiple curves,multiple regression method was good. Because of the lack of thick mudstone and thermal alteration index selection difficulty,ΔLgR method's effect was poorer. Neural network had great superiority when it was nonlinear and difficult to use explicit expression.Through three kinds of S_1+S_2 calculation methods in the study area, showed that the TOC related method was the best,multivariate regression was the second,and neural network effect was the worst. TOC was related with S_1+S_2,so its calculation effect was good. Contribution of S_1+S_2 to logging response was small,so the method of multiple regression and neural network effects were bad. Maturity evaluation of vitrinite reflectance had correlation with depth, it was most commonly used. Some parameters of residual carbon ratio method were determined in the early exploration,so it had limited application.
Identification and evaluation of source rock is the basis of geological study for hydrocarbon. Limited core samples restrained the demand of exploration. After calibration of analysis data,logging data can provide continuous hydrocarbon source rocks index,and it's widely used. Three Logging quantitative evaluation method were discussed in the paper including the content of Total Organic Carbon( TOC), the amount of pyrolysis hydrocarbon generation potential( S_1+S_2) and the maturity indicators. These methods were tried in Bengal bay, and combined with block geological conditions the calculation results were analyzed. First,four kinds of calculation methods for the TOC including single factor method,multiple regression method,ΔLgR method and the neural network were described in detail,as far as principles,advantages and disadvantages. What 's more, two methods including the vitrinite reflectance and residual carbon ratio for maturity evaluation were introduced. Finally,the quantitative calculation results in the study area were analyzed. TOC calculation results shows that the neural network was best,multivariate regression method was the second,ΔLgR method was poorer,and single factor method was the worst. Analysis shows the low TOC contributed little to the logging response,bad correlation between a single curve and TOC lead to poor effect of single factor method. As considering multiple curves,multiple regression method was good. Because of the lack of thick mudstone and thermal alteration index selection difficulty,ΔLgR method's effect was poorer. Neural network had great superiority when it was nonlinear and difficult to use explicit expression.Through three kinds of S_1+S_2 calculation methods in the study area, showed that the TOC related method was the best,multivariate regression was the second,and neural network effect was the worst. TOC was related with S_1+S_2,so its calculation effect was good. Contribution of S_1+S_2 to logging response was small,so the method of multiple regression and neural network effects were bad. Maturity evaluation of vitrinite reflectance had correlation with depth, it was most commonly used. Some parameters of residual carbon ratio method were determined in the early exploration,so it had limited application.
引文
Chen X R,Sun B S,Jiang T,et al.2011.The application of well logging technology to the assessment of source rock in the Jimsar depression,Junggar basin[J].Acta Geologica Sichuan(in Chinese),31(1):105-108.
Deng H C,Zhou W,Zhang J,et al.2010.The quantitative identifying and evaluation about Ordovician source rocks with logging in the middle Tazhong area of Tarim basin[J].Computing Techniques for Geophysical and Geochemical Exploration(in Chinese),32(4):380-385.
Guo L,Chen J F,Miao Z Y.2009.Study and application of a new overlay method of the TOC content[J].Natural Gas Geoscience(in Chinese),20(6):951-956.
Herron S L,Letendre I,Dufour M.1988.Source rock evaluation using geochemical information from wireline logs and cores[J].AAPGBulletin,72(8):1007-1009.
Hu J Q,Lu Y L,Cai H Z.2002.Auto-assessment on the sydrocarbon rock by using well-logging information[J].Shanghai Geology(in Chinese),(3):32-35.
Huang C,Pan B Z.Using general log information to evaluate hydrocarbon source rocks of basins in Daqing periphery[J].Journal of Jilin University(Earth Science Edition)(in Chinese),2006,36(S2):162-165.
Liu C.2011.Evaluating source rock using logging data-improvement and application(in Chinese)[Master’thesis].Daqing:Northeast Petroleum University,9-33.
Liu C,Lu S F,Xue H T.2014.Variable-coefficientΔLogR model and its application in shale organic evaluation[J].Progress in Geophysics(in Chinese),29(1):312-317,doi:10.6038/pg20140144.
Liu Z,Chang M,Zhao Y,et al.2007.Method of early prediction on source rocks in basins with low exploration activity[J].Earth Science Frontiers(in Chinese),14(4):159-167.
Ma Z.1994.Geology of Oil and Gas Well Logging(in Chinese)[M].Beijing:China University of Geosciences Press,59-69.
Meyer B L,Nederlof M H.1984.Identification of source rocks on wireline logs by density/resistivity and sonic transit time/resistivity crossplots[J].AAPG Bulletin,68(2):121-129.
Passey Q R,Creaney S,Kulla J B,et al.1990.A practical model for organic richness from porosity and resistivity logs[J].AAPGBulletin,74(12):1777-1794.
Schmoker J W.1981.Determination of organic-matter content of appalachian devonian shales from gamma-ray logs[J].AAPGBulletin,65(7):1285-1298.
Schmoker J W,Heste T C.1983.Organic carbon in Bakken formation,United States portion of Williston basin[J].AAPG Bulletin,67(12):2165-2174.
Tan T D.1988.Identification of Kuchersits from well logs[J].Well Logging Technology(in Chinese),12(6):1-11,78.
Wang G W,Zhu Z Y,Zhu G Y.2002.Logging identification and evaluation of Cambrian-Ordovician source rocks in syneclise of Tarim basin[J].Petroleum Exploration and Development(in Chinese),29(4):50-52.
Wang L,Jin Q,Lin L M,et al.2009.Characteristics of quality Tertiary source rocks in west Qaidam basin[J].Natural Gas Industry(in Chinese),29(2):23-26.
Xu S H,Zhu Y Q.2010.Well logs response and prediction model of organic carbon content in source rocks:A case study from the source rock of Wenchang Formation in the Pearl Mouth basin[J].Petroleum Geology&Experiment(in Chinese),32(3):290-295,300.
Xu X H,Huang H P,Lu S N.1998.A quantitative relationship between well logging information and organic carbon content[J].Journal of Jianghan Petroleum Institute(in Chinese),20(3):8-12.
Yu X T.2009.Application of well logging technology to source rocks evaluation[J].Journal of Yangtze University(Natural Science Edition):Science&Engineering(in Chinese),6(2):198-200.
Yue B S,Huang H,Chen B,et al.2005.A method for logging source rock evaluation in Dongpu depression and its application[J].Journal of Oil and Gas Technology(in Chinese),27(3):351-354.
Zhang L P,Bian R X,Yang S Y,et al.2001.Identifying hydrocarbon source rock with log data[J].Well Logging Technology(in Chinese),25(2):146-152.
Zhang Z W,Zhang L H.2000.A method of source rock evaluation by well-logging and its application result[J].Petroleum Exploration and Development(in Chinese),27(3):84-87.
Zheng Z H.2009.Log recognition for source rocks in West Tidal Zone,Liaohe oil field(in Chinese)[Master’thesis].Beijing:China University of Geosciences(Beijing),2-6.
Zhu G Y,Jin Q,Zhang L Y.2003.Using log information to analyze the geochemical characteristics of source rocks in Jiyang depression[J].Well Logging Technology(in Chinese),27(2):104-109,146.
Zhu Z Y,Wang G W,Zhu G Y.2002.The application of artificial neural network to the source rock’s evaluation[J].Progress in Geophysics(in Chinese),17(1):137-140,doi:10.3969/j.issn.1004-2903.2002.01.019.
陈小蓉,孙宝生,姜涛,等.2011.测井技术在评价准噶尔盆地吉木萨尔凹陷烃源岩中的应用[J].四川地质学报,31(1):105-108.
邓虎成,周文,张娟,等.2010.塔中地区奥陶系烃源岩测井定量识别及评价[J].物探化探计算技术,32(4):380-385.
郭龙,陈践发,苗忠英.2009.一种新的TOC含量拟合方法研究与应用[J].天然气地球科学,20(6):951-956.
胡佳庆,陆芸兰,蔡洪正.2002.用测井资料自动评价烃源岩[J].上海地质,(3):32-35.
黄晨,潘保芝.2006.利用测井资料识别与评价大庆外围盆地烃源岩[J].吉林大学学报(地球科学版),36(S2):162-165.
刘超.2011.测井资料评价烃源岩方法改进及作用[硕士论文].大庆:东北石油大学,9-33.
刘超,卢双舫,薛海涛.2014.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,29(1):312-317,doi:10.6038/pg20140144.
刘震,常迈,赵阳,等.2007.低勘探程度盆地烃源岩早期预测方法研究[J].地学前缘,14(4):159-167.
马正.1994.油气测井地质学[M].北京:中国地质大学出版社,59-69.
谭廷栋.1988.测井识别生油岩方法[J].测井技术,12(6):1-11,78.
王贵文,朱振宇,朱广宇.2002.烃源岩测井识别与评价方法研究[J].石油勘探与开发,29(4):50-52.
王力,金强,林腊梅,等.2009.柴达木盆地西部古近系-新近系优质烃源岩特征[J].天然气工业,29(2):23-26.
徐思煌,朱义清.2010.烃源岩有机碳含量的测井响应特征与定量预测模型---以珠江口盆地文昌组烃源岩为例[J].石油实验地质,32(3):290-295,300.
许晓宏,黄海平,卢松年.1998.测井资料与烃源岩有机碳含量的定量关系研究[J].江汉石油学报,20(3):8-12.
于翔涛.2009.测井技术在烃源岩评价中的应用[J].长江大学学报(自然科学版):理工,6(2):198-200.
岳炳顺,黄华,陈彬,等.2005.东濮凹陷测井烃源岩评价方法及应用[J].石油天然气学报,27(3):351-354.
张立鹏,边瑞雪,杨双彦,等.2001.用测井资料识别烃源岩[J].测井技术,25(2):146-152.
张志伟,张龙海.2000.测井评价烃源岩的方法及其应用效果[J].石油勘探与开发,27(3):84-87.
郑兆惠.2009.辽河滩海西部地区烃源岩测井识别[硕士论文].北京:中国地质大学(北京),2-6.
朱光有,金强,张林晔.2003.用测井信息获取烃源岩的地球化学参数研究[J].测井技术,27(2):104-109,146.
朱振宇,王贵文,朱广宇.2002.人工神经网络法在烃源岩测井评价中的应用[J].地球物理学进展,17(1):137-140,doi:10.3969/j.issn.1004-2903.2002.01.019.
Deng H C,Zhou W,Zhang J,et al.2010.The quantitative identifying and evaluation about Ordovician source rocks with logging in the middle Tazhong area of Tarim basin[J].Computing Techniques for Geophysical and Geochemical Exploration(in Chinese),32(4):380-385.
Guo L,Chen J F,Miao Z Y.2009.Study and application of a new overlay method of the TOC content[J].Natural Gas Geoscience(in Chinese),20(6):951-956.
Herron S L,Letendre I,Dufour M.1988.Source rock evaluation using geochemical information from wireline logs and cores[J].AAPGBulletin,72(8):1007-1009.
Hu J Q,Lu Y L,Cai H Z.2002.Auto-assessment on the sydrocarbon rock by using well-logging information[J].Shanghai Geology(in Chinese),(3):32-35.
Huang C,Pan B Z.Using general log information to evaluate hydrocarbon source rocks of basins in Daqing periphery[J].Journal of Jilin University(Earth Science Edition)(in Chinese),2006,36(S2):162-165.
Liu C.2011.Evaluating source rock using logging data-improvement and application(in Chinese)[Master’thesis].Daqing:Northeast Petroleum University,9-33.
Liu C,Lu S F,Xue H T.2014.Variable-coefficientΔLogR model and its application in shale organic evaluation[J].Progress in Geophysics(in Chinese),29(1):312-317,doi:10.6038/pg20140144.
Liu Z,Chang M,Zhao Y,et al.2007.Method of early prediction on source rocks in basins with low exploration activity[J].Earth Science Frontiers(in Chinese),14(4):159-167.
Ma Z.1994.Geology of Oil and Gas Well Logging(in Chinese)[M].Beijing:China University of Geosciences Press,59-69.
Meyer B L,Nederlof M H.1984.Identification of source rocks on wireline logs by density/resistivity and sonic transit time/resistivity crossplots[J].AAPG Bulletin,68(2):121-129.
Passey Q R,Creaney S,Kulla J B,et al.1990.A practical model for organic richness from porosity and resistivity logs[J].AAPGBulletin,74(12):1777-1794.
Schmoker J W.1981.Determination of organic-matter content of appalachian devonian shales from gamma-ray logs[J].AAPGBulletin,65(7):1285-1298.
Schmoker J W,Heste T C.1983.Organic carbon in Bakken formation,United States portion of Williston basin[J].AAPG Bulletin,67(12):2165-2174.
Tan T D.1988.Identification of Kuchersits from well logs[J].Well Logging Technology(in Chinese),12(6):1-11,78.
Wang G W,Zhu Z Y,Zhu G Y.2002.Logging identification and evaluation of Cambrian-Ordovician source rocks in syneclise of Tarim basin[J].Petroleum Exploration and Development(in Chinese),29(4):50-52.
Wang L,Jin Q,Lin L M,et al.2009.Characteristics of quality Tertiary source rocks in west Qaidam basin[J].Natural Gas Industry(in Chinese),29(2):23-26.
Xu S H,Zhu Y Q.2010.Well logs response and prediction model of organic carbon content in source rocks:A case study from the source rock of Wenchang Formation in the Pearl Mouth basin[J].Petroleum Geology&Experiment(in Chinese),32(3):290-295,300.
Xu X H,Huang H P,Lu S N.1998.A quantitative relationship between well logging information and organic carbon content[J].Journal of Jianghan Petroleum Institute(in Chinese),20(3):8-12.
Yu X T.2009.Application of well logging technology to source rocks evaluation[J].Journal of Yangtze University(Natural Science Edition):Science&Engineering(in Chinese),6(2):198-200.
Yue B S,Huang H,Chen B,et al.2005.A method for logging source rock evaluation in Dongpu depression and its application[J].Journal of Oil and Gas Technology(in Chinese),27(3):351-354.
Zhang L P,Bian R X,Yang S Y,et al.2001.Identifying hydrocarbon source rock with log data[J].Well Logging Technology(in Chinese),25(2):146-152.
Zhang Z W,Zhang L H.2000.A method of source rock evaluation by well-logging and its application result[J].Petroleum Exploration and Development(in Chinese),27(3):84-87.
Zheng Z H.2009.Log recognition for source rocks in West Tidal Zone,Liaohe oil field(in Chinese)[Master’thesis].Beijing:China University of Geosciences(Beijing),2-6.
Zhu G Y,Jin Q,Zhang L Y.2003.Using log information to analyze the geochemical characteristics of source rocks in Jiyang depression[J].Well Logging Technology(in Chinese),27(2):104-109,146.
Zhu Z Y,Wang G W,Zhu G Y.2002.The application of artificial neural network to the source rock’s evaluation[J].Progress in Geophysics(in Chinese),17(1):137-140,doi:10.3969/j.issn.1004-2903.2002.01.019.
陈小蓉,孙宝生,姜涛,等.2011.测井技术在评价准噶尔盆地吉木萨尔凹陷烃源岩中的应用[J].四川地质学报,31(1):105-108.
邓虎成,周文,张娟,等.2010.塔中地区奥陶系烃源岩测井定量识别及评价[J].物探化探计算技术,32(4):380-385.
郭龙,陈践发,苗忠英.2009.一种新的TOC含量拟合方法研究与应用[J].天然气地球科学,20(6):951-956.
胡佳庆,陆芸兰,蔡洪正.2002.用测井资料自动评价烃源岩[J].上海地质,(3):32-35.
黄晨,潘保芝.2006.利用测井资料识别与评价大庆外围盆地烃源岩[J].吉林大学学报(地球科学版),36(S2):162-165.
刘超.2011.测井资料评价烃源岩方法改进及作用[硕士论文].大庆:东北石油大学,9-33.
刘超,卢双舫,薛海涛.2014.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,29(1):312-317,doi:10.6038/pg20140144.
刘震,常迈,赵阳,等.2007.低勘探程度盆地烃源岩早期预测方法研究[J].地学前缘,14(4):159-167.
马正.1994.油气测井地质学[M].北京:中国地质大学出版社,59-69.
谭廷栋.1988.测井识别生油岩方法[J].测井技术,12(6):1-11,78.
王贵文,朱振宇,朱广宇.2002.烃源岩测井识别与评价方法研究[J].石油勘探与开发,29(4):50-52.
王力,金强,林腊梅,等.2009.柴达木盆地西部古近系-新近系优质烃源岩特征[J].天然气工业,29(2):23-26.
徐思煌,朱义清.2010.烃源岩有机碳含量的测井响应特征与定量预测模型---以珠江口盆地文昌组烃源岩为例[J].石油实验地质,32(3):290-295,300.
许晓宏,黄海平,卢松年.1998.测井资料与烃源岩有机碳含量的定量关系研究[J].江汉石油学报,20(3):8-12.
于翔涛.2009.测井技术在烃源岩评价中的应用[J].长江大学学报(自然科学版):理工,6(2):198-200.
岳炳顺,黄华,陈彬,等.2005.东濮凹陷测井烃源岩评价方法及应用[J].石油天然气学报,27(3):351-354.
张立鹏,边瑞雪,杨双彦,等.2001.用测井资料识别烃源岩[J].测井技术,25(2):146-152.
张志伟,张龙海.2000.测井评价烃源岩的方法及其应用效果[J].石油勘探与开发,27(3):84-87.
郑兆惠.2009.辽河滩海西部地区烃源岩测井识别[硕士论文].北京:中国地质大学(北京),2-6.
朱光有,金强,张林晔.2003.用测井信息获取烃源岩的地球化学参数研究[J].测井技术,27(2):104-109,146.
朱振宇,王贵文,朱广宇.2002.人工神经网络法在烃源岩测井评价中的应用[J].地球物理学进展,17(1):137-140,doi:10.3969/j.issn.1004-2903.2002.01.019.