基于主成分分析法与Bayes判别法组合应用的火山岩岩性定量识别:以渤海海域中生界为例
|
摘要
渤海海域中生界火山岩岩石类型复杂多样,且同一岩性受岩石成分、结构差异的影响,因此岩石物理响应特征存在较大差异,为岩性识别增加了难度。本文通过对研究区大量取心资料、壁心资料以及薄片资料的岩电分析,优选出对岩性响应敏感的自然伽马(GR)、补偿中子(CNL)、密度(DEN)、声波时差(AC)以及原状地层电阻率(Rd)等5条曲线。基于主成分分析法,构建了F_1—F_5共5个综合变量,其中F_1和F_2方差贡献率占总贡献率的81.4%,可作为两个主成分有效地反映5个变量的信息。针对主成分信息,利用Bayes判别法,构建了不同岩性的定量解释模型,对研究区9种火山岩进行了岩性识别。对取心井段的回判结果显示,基于主成分分析与Bayes判别的联合识别方法较常规交会图法在岩石成分及结构的识别精度方面均有较大程度的提高。该方法的提出对研究区成像测井、元素测井资料缺少井段的火山岩岩性识别具有重要借鉴作用。
Because of the complexity of the lithologic characteristics and structures,the Mesozoic igneous rocks of the Bohai Bay area is difficult to identify.Based on the abundant data of cores,lateral cores and rock sections,and rock-electricity relationship,five logging curves of GR,CNL,DEN,AC,and Rd were selected.Using the principal component analysis,five comprehensive variables including F_1-F_5 were constructed.F_1 and F_2 were used to replace the original five variables efficiently,as their proportion account for 81.4%.According to the principal component information,combining with the Bayes discriminant method,the model for quantitative interpretation of different lithology was established,and nine types of volcanic rocks in the study area were identified.A back evaluation of the core data was carried out.The results show that this method can identify the rock composition and the rock structure better than cross-plotting.This method is an efficient one for volcanic lithology identification in the areas with less data of FMI and ECS.
Because of the complexity of the lithologic characteristics and structures,the Mesozoic igneous rocks of the Bohai Bay area is difficult to identify.Based on the abundant data of cores,lateral cores and rock sections,and rock-electricity relationship,five logging curves of GR,CNL,DEN,AC,and Rd were selected.Using the principal component analysis,five comprehensive variables including F_1-F_5 were constructed.F_1 and F_2 were used to replace the original five variables efficiently,as their proportion account for 81.4%.According to the principal component information,combining with the Bayes discriminant method,the model for quantitative interpretation of different lithology was established,and nine types of volcanic rocks in the study area were identified.A back evaluation of the core data was carried out.The results show that this method can identify the rock composition and the rock structure better than cross-plotting.This method is an efficient one for volcanic lithology identification in the areas with less data of FMI and ECS.
引文
[1]刘嘉麒,孟凡超.火山作用与油气成藏[J].天然气工业,2009,29(8):1-4.Liu Jiaqi,Meng Fanchao.Hydrocarbon Generation,Migration and Accumulation Related to Igneous Activity[J].Natural Gas Industry,2009,29(8):1-4.
[2]Chen Zhenyan,Yan Huo,Li Junsheng,et al.Relationship Between Tertiary Volcanic Rocks and Hydrocarbons in the Liaohe Basin,Peoples Republic of China[J].AAPG,1999,83(6):1004-1014.
[3]叶涛,韦阿娟,祝春荣,等.渤海海域基底“改造型火山机构”特征及油气成藏意义[J].石油学报,2016,37(11):1370-1380,1434.Ye Tao,Wei Ajuan,Zhu Chunrong,et al.Characteristic and Hydrocarbon Accumulation Significance of Reformed Volcanic Edifice in the Basement of Bohai Sea[J].Acta Petrolei Sinica,2016,37(11):1370-1380,1434.
[4]Feng Zhiqiang.Volcanic Rocks As Prolific Gas Reservoir:A Case Study from the Qingshen Gas Field in the Songliao Basin,NE China[J].Marine and Petroleum Geology,2008,25:416-432.
[5]潘保芝,李舟波,付有升,等.测井资料在松辽盆地火成岩岩性识别和储层评价中的应用[J].石油物探,2009,48(1):48-56.Pan Baozhi,Li Zhoubo,Fu Yousheng,et al.Application of Logging Data in Lithology Identification and Reservoir Evaluation of Igneous Rock in Songliao Basin[J].Geophysical Prospecting for Petroleum,2009,48(1):48-56.
[6]寇彧,师永民,李柏任,等.克拉美丽气田石炭系火山岩复杂岩性岩电特征[J].岩石学报,2010,26(1):291-300.Kou Yu,Shi Yongmin,Li Boren,et al.The Complex Lithology Rock-Electricity Features of Volcanic Rocks in Kelameili Gas Field[J].Acta Petrologica Sinica,2010,26(1):291-300.
[7]范超颖,陈玉平,张洋洋.松辽盆地长岭断陷营城组火山岩测井响应特征与岩性识别[J].吉林大学学报(地球科学版),2010,40(增刊):87-91.Fan Chaoying,Chen Yuping,Zhang Yangyang.The Logging Response Characteristics and Identification of Yingcheng Formation Volcanic Rocks in Changling Fault Depression,Songliao Basin[J].Journal of Jilin University(Earth Science Edition),2010,40(Sup.):87-91.
[8]张建民,李超炜,张继业,等.长深1井区火成岩岩性识别方法及应用[J].吉林大学学报(地球科学版),2008,38(增刊):106-109.Zhang Jianmin,Li Chaowei,Zhang Jiye,et al.ALithological Identification Method of Igneous Rocks and Its Application in Changling Area[J].Journal of Jilin University(Earth Science Edition),2008,38(Sup.):106-109.
[9]张莹,潘保芝.多种岩性分类方法在火山岩岩性识别中的应用[J].测井技术,2011,35(5):474-478.Zhang Ying,Pan Baozhi.Application of Various Lithology Classification Methods to Volcanic Rock Identification[J].Well Logging Technology,2011,35(5):474-478.
[10]潘荣,朱筱敏,张剑锋,等.基于主成分分析的储层质量综合评价模型:以克拉苏构造带巴什基奇克组为例[J].石油实验地质,2012,27(4):1640-1647.Pan Rong,Zhu Xiaomin,Zhang Jianfeng,et al.AModel for Comprehensive Evaluation of Reservoir Quality Based on Principal Component Analysis:ACase Study of Bashijiqike Formation in Kelasu Tectonic Zone[J].Petroleum Geology&Experiment,2012,27(4):1640-1647.
[11]李超,印兴耀,张广智,等.基于贝叶斯理论的孔隙流体模量叠前AVA反演[J].石油物探,2015,54(4):467-476.Li Chao,Yin Xingyao,Zhang Guangzhi,et al.Prestack AVA Inversion for Pore Fluid Modulus Based on the Bayesian Theory[J].Geophysical Prospecting for Petroleum,2015,54(4):467-476.
[12]胡素云,郭秋麟,谌卓恒,等.油气空间分布预测方法[J].石油勘探与开发,2007,34(1):113-117.Hu Suyun,Guo Qiulin,Chen Zhuoheng,et al.AMethod of Predicting Petroleum Resource Spatial Distribution and Its Application[J].Petroleum Exploration and Devlepment,2007,34(1):113-117.
[13]袁志发,宋世德.多元统计分析[M].北京:科学出版社,2009.Yuan Zhifa,Song Shide.Mutlivariate Statistical Alalysis[M].Beijing:Science Press,2009.
[14]刘爱疆,左烈,李景景,等.主成分分析法在碳酸盐岩岩性识别中的应用:以YH地区寒武系碳酸盐岩储层为例[J].石油与天然气地质,2013,34(2):192-196.Liu Aijiang,Zuo Lie,Li Jingjing,et al.Application of Principal Component Analysis in Carbon Lithology Identification:A Case Study of the Cambrian Carbonate Reservoir in YH Field[J].Oil&Gas Geology,2013,34(2):192-196.
[15]吴昀昭,田庆久,陈骏,等.基于主成分分析的反射光谱在岩石学中的应用:以哈密地区为例[J].岩石学报,2003,19(4):761-766.Wu Yunzhao,Tian Qingjiu,Chen Jun,et al.Application of Rock Laboratorial Reflectance Spectra in Hami Area Based on Principal Component Analysis.[J].Acta Petrologica Sinica,2003,19(4):761-766.
[16]郑静静,王延光,杜磊,等.基于概率核主成分分析的属性优化方法及其应用[J].石油地球物理勘探,2014,49(3):567-571.Zheng Jingjing,Wang Yanguang,Du Lei,et al.Attribute Optimization Based on the Probability Kernel Principal Component Analysis[J].Oil Geophysical Prospecting,2014,49(3):567-571.
[17]刘倩茹,薛林福,潘保芝,等.梨树断陷砂砾岩测井岩性识别[J].测井技术,2014,37(3):269-274.Liu Qianru,Xue Linfu,Pan Baozhi,et al.Study on Glutenite Reservoir Lithology Identification in Lishu Fault[J].Well Logging Technology,2013,37(3):269-274.
[18]叶涛,韦阿娟,邓辉,等.基于常规测井资料的火山岩岩性识别方法研究:以渤海海域中生界为例[J].地球物理学进展,2013,37(3):269-274.Ye Tao,Wei Ajuan,Deng Hui,et al.Study on Volcanic Lithology Identification Methods Based on the Data of Conventional Well Logging Data:A Case from Mesozoic Volcanic Rocks in Bohai Bay Area[J].Progress in Geophysics,2017,32(4):1842-1848.
[19]叶涛,韦阿娟,高坤顺,等.渤海海域中生界火山岩测井-地质岩性综合识别方法[J].中国海上油气,2016,28(1):48-53.Ye Tao,Wei Ajuan,Gao Kunshun,et al.Lithology Comprehensive Identification Method with LoggingGeology Data of Mesozoic Volcanic Rocks in Bohai Sea[J].China Offshore Oil and Gas,2016,28(1):48-53.
[2]Chen Zhenyan,Yan Huo,Li Junsheng,et al.Relationship Between Tertiary Volcanic Rocks and Hydrocarbons in the Liaohe Basin,Peoples Republic of China[J].AAPG,1999,83(6):1004-1014.
[3]叶涛,韦阿娟,祝春荣,等.渤海海域基底“改造型火山机构”特征及油气成藏意义[J].石油学报,2016,37(11):1370-1380,1434.Ye Tao,Wei Ajuan,Zhu Chunrong,et al.Characteristic and Hydrocarbon Accumulation Significance of Reformed Volcanic Edifice in the Basement of Bohai Sea[J].Acta Petrolei Sinica,2016,37(11):1370-1380,1434.
[4]Feng Zhiqiang.Volcanic Rocks As Prolific Gas Reservoir:A Case Study from the Qingshen Gas Field in the Songliao Basin,NE China[J].Marine and Petroleum Geology,2008,25:416-432.
[5]潘保芝,李舟波,付有升,等.测井资料在松辽盆地火成岩岩性识别和储层评价中的应用[J].石油物探,2009,48(1):48-56.Pan Baozhi,Li Zhoubo,Fu Yousheng,et al.Application of Logging Data in Lithology Identification and Reservoir Evaluation of Igneous Rock in Songliao Basin[J].Geophysical Prospecting for Petroleum,2009,48(1):48-56.
[6]寇彧,师永民,李柏任,等.克拉美丽气田石炭系火山岩复杂岩性岩电特征[J].岩石学报,2010,26(1):291-300.Kou Yu,Shi Yongmin,Li Boren,et al.The Complex Lithology Rock-Electricity Features of Volcanic Rocks in Kelameili Gas Field[J].Acta Petrologica Sinica,2010,26(1):291-300.
[7]范超颖,陈玉平,张洋洋.松辽盆地长岭断陷营城组火山岩测井响应特征与岩性识别[J].吉林大学学报(地球科学版),2010,40(增刊):87-91.Fan Chaoying,Chen Yuping,Zhang Yangyang.The Logging Response Characteristics and Identification of Yingcheng Formation Volcanic Rocks in Changling Fault Depression,Songliao Basin[J].Journal of Jilin University(Earth Science Edition),2010,40(Sup.):87-91.
[8]张建民,李超炜,张继业,等.长深1井区火成岩岩性识别方法及应用[J].吉林大学学报(地球科学版),2008,38(增刊):106-109.Zhang Jianmin,Li Chaowei,Zhang Jiye,et al.ALithological Identification Method of Igneous Rocks and Its Application in Changling Area[J].Journal of Jilin University(Earth Science Edition),2008,38(Sup.):106-109.
[9]张莹,潘保芝.多种岩性分类方法在火山岩岩性识别中的应用[J].测井技术,2011,35(5):474-478.Zhang Ying,Pan Baozhi.Application of Various Lithology Classification Methods to Volcanic Rock Identification[J].Well Logging Technology,2011,35(5):474-478.
[10]潘荣,朱筱敏,张剑锋,等.基于主成分分析的储层质量综合评价模型:以克拉苏构造带巴什基奇克组为例[J].石油实验地质,2012,27(4):1640-1647.Pan Rong,Zhu Xiaomin,Zhang Jianfeng,et al.AModel for Comprehensive Evaluation of Reservoir Quality Based on Principal Component Analysis:ACase Study of Bashijiqike Formation in Kelasu Tectonic Zone[J].Petroleum Geology&Experiment,2012,27(4):1640-1647.
[11]李超,印兴耀,张广智,等.基于贝叶斯理论的孔隙流体模量叠前AVA反演[J].石油物探,2015,54(4):467-476.Li Chao,Yin Xingyao,Zhang Guangzhi,et al.Prestack AVA Inversion for Pore Fluid Modulus Based on the Bayesian Theory[J].Geophysical Prospecting for Petroleum,2015,54(4):467-476.
[12]胡素云,郭秋麟,谌卓恒,等.油气空间分布预测方法[J].石油勘探与开发,2007,34(1):113-117.Hu Suyun,Guo Qiulin,Chen Zhuoheng,et al.AMethod of Predicting Petroleum Resource Spatial Distribution and Its Application[J].Petroleum Exploration and Devlepment,2007,34(1):113-117.
[13]袁志发,宋世德.多元统计分析[M].北京:科学出版社,2009.Yuan Zhifa,Song Shide.Mutlivariate Statistical Alalysis[M].Beijing:Science Press,2009.
[14]刘爱疆,左烈,李景景,等.主成分分析法在碳酸盐岩岩性识别中的应用:以YH地区寒武系碳酸盐岩储层为例[J].石油与天然气地质,2013,34(2):192-196.Liu Aijiang,Zuo Lie,Li Jingjing,et al.Application of Principal Component Analysis in Carbon Lithology Identification:A Case Study of the Cambrian Carbonate Reservoir in YH Field[J].Oil&Gas Geology,2013,34(2):192-196.
[15]吴昀昭,田庆久,陈骏,等.基于主成分分析的反射光谱在岩石学中的应用:以哈密地区为例[J].岩石学报,2003,19(4):761-766.Wu Yunzhao,Tian Qingjiu,Chen Jun,et al.Application of Rock Laboratorial Reflectance Spectra in Hami Area Based on Principal Component Analysis.[J].Acta Petrologica Sinica,2003,19(4):761-766.
[16]郑静静,王延光,杜磊,等.基于概率核主成分分析的属性优化方法及其应用[J].石油地球物理勘探,2014,49(3):567-571.Zheng Jingjing,Wang Yanguang,Du Lei,et al.Attribute Optimization Based on the Probability Kernel Principal Component Analysis[J].Oil Geophysical Prospecting,2014,49(3):567-571.
[17]刘倩茹,薛林福,潘保芝,等.梨树断陷砂砾岩测井岩性识别[J].测井技术,2014,37(3):269-274.Liu Qianru,Xue Linfu,Pan Baozhi,et al.Study on Glutenite Reservoir Lithology Identification in Lishu Fault[J].Well Logging Technology,2013,37(3):269-274.
[18]叶涛,韦阿娟,邓辉,等.基于常规测井资料的火山岩岩性识别方法研究:以渤海海域中生界为例[J].地球物理学进展,2013,37(3):269-274.Ye Tao,Wei Ajuan,Deng Hui,et al.Study on Volcanic Lithology Identification Methods Based on the Data of Conventional Well Logging Data:A Case from Mesozoic Volcanic Rocks in Bohai Bay Area[J].Progress in Geophysics,2017,32(4):1842-1848.
[19]叶涛,韦阿娟,高坤顺,等.渤海海域中生界火山岩测井-地质岩性综合识别方法[J].中国海上油气,2016,28(1):48-53.Ye Tao,Wei Ajuan,Gao Kunshun,et al.Lithology Comprehensive Identification Method with LoggingGeology Data of Mesozoic Volcanic Rocks in Bohai Sea[J].China Offshore Oil and Gas,2016,28(1):48-53.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |