基于马尔科夫随机场的隧道岩溶发育规律分析
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摘要
岩溶发育规律是岩溶地质灾害最基本的问题,地质分析和地球物理勘探是其常用的方法。为综合考虑物探数据中岩土体物性参数重叠问题,文章从地质学角度出发,利用地层的马尔科夫性质和贝叶斯框架下的最大后验概率进行反演岩相识别。文章以南宁轨道交通2号线石子塘车站岩溶发育区域为例,根据岩溶发育条件和实际钻孔资料对溶洞、溶蚀裂隙等进行解译和验证,结果发现:受地下水水平循环带和断裂构造影响,溶洞以及岩溶裂隙空间展布大致呈现水平方向;溶蚀现象主要发育在泥灰岩中,距离车站底板10 m以外范围,但溶洞尺寸大且连通性好,需要在施工过程中加以重视。
In southwest China,there is a large range of carbonatite areas.With the construction of city infrastructure,especially rail transit,geological disasters related to karst emerge one after another,and it′s critical to understand the law of karst development.As for this issue the geological analysis and geophysical prospecting are the common methods to be adopted.In view of superposition issue of physical property parameters of rock mass in geophysical prospecting,inversive identification of lithofacies was conducted based on maximum posteriori probability under the framework of Bayesian and the Markov property of the strata.Taking the Nanning rail transit line 2 as an example,interpretation and verification of karst cave and grike were carried out on the basis of karst development conditions and documents of drilling holes.The results show that:influenced by horizontal circulation zone of groundwater and fracture structure,the spatial distribution of karst caves and grike goes horizontally;grike often occurs in the marl 10 meters away beyond the station floor,and attention should be paid during construction due to the large size and good connectivity of the karst caves.
In southwest China,there is a large range of carbonatite areas.With the construction of city infrastructure,especially rail transit,geological disasters related to karst emerge one after another,and it′s critical to understand the law of karst development.As for this issue the geological analysis and geophysical prospecting are the common methods to be adopted.In view of superposition issue of physical property parameters of rock mass in geophysical prospecting,inversive identification of lithofacies was conducted based on maximum posteriori probability under the framework of Bayesian and the Markov property of the strata.Taking the Nanning rail transit line 2 as an example,interpretation and verification of karst cave and grike were carried out on the basis of karst development conditions and documents of drilling holes.The results show that:influenced by horizontal circulation zone of groundwater and fracture structure,the spatial distribution of karst caves and grike goes horizontally;grike often occurs in the marl 10 meters away beyond the station floor,and attention should be paid during construction due to the large size and good connectivity of the karst caves.
引文
[1]蒙彦,雷明堂.岩溶区隧道涌水研究现状及建议[J].中国岩溶, 2003, 22(4):38-43.MENG Yan, LEI Mingtang. The Advance and Suggestion for the Study on Discharge Rate in Karst Tunnel Gushing[J]. CarsologicaSinica, 2003, 22(4):38-43.
[2]韩行瑞.岩溶隧道涌水及其专家评判系统[J].中国岩溶, 2004, 23(3):47-52.HAN Xingrui. Karst Water Bursting in Tunnel and Expert Judging System[J]. Carsologica Sinica, 2004, 23(3):47-52.
[3]范威,王川,金晓文,等.吉莲高速公路钟家山隧道涌突水条件分析[J].水文地质工程地质, 2015, 42(2):38-43.FAN Wei, WANG Chuan, JIN Xiaowen, et al. Water Inrush Condition Analysis of the Zhongjiashan Tunnel in the Jilian Highway[J].Hydrogeology&Engineering Geology, 2015, 42(2):38-43.
[4]陈绍林,李茂竹,陈忠恕,等.四川广(安)—渝(重庆)高速公路华蓥山隧道岩溶突水的研究与整治[J].岩石力学与工程学报,2002, 21(9):1344-1349.CHEN Shaolin, LI Maozhu, CHEN Zhongshu, et al. Study and Treatment on Karst Water Outburst in Huayingshan Tunnel for AnyuExpressway from Guang′an of Sichuan to Chongqing[J]. Chinese Journal of Rock Mechanics and Engineering, 2002, 21(9):1344-1349.
[5]李术才,石少帅,李利平,等.三峡库区典型岩溶隧道突涌水灾害防治与应用[J].岩石力学与工程学报, 2014, 33(9):1887-1896.LI Shucai, SHI Shaoshuai, LI Liping, et al. Control of Water Inrush in Typical Karst Tunnels in Three Gorges Reservoir Area and ItsApplication[J]. Chinese Journal of Rock Mechanics and Engineering, 2014, 33(9):1887-1896.
[6]卢平.风险岩溶隧道地质灾害评价与施工控制技术研究[D].成都:成都理工大学, 2014.LU Ping. Geohazard Assessment and Construction Controlling Technology Study of High-risk Karst Tunnel[D]. Chegndu:ChengduUniversity of Technology, 2014.
[7]孙正兵,岳健,赖新军,等.高速铁路上郭关隧道施工遭遇大型溶洞的处理方案研究[J].铁道标准设计, 2015, 59(11):83-87.SUN Zhengbing, YUE Jian, LAI Xinjun, et al. Study on Treatment of Large Karst Cave during Construction of Shangguoguan HighSpeed Railway Tunnel[J]. Railway Standard Design, 2015, 59(11):83-87.
[8]龙艳魁.长沙地铁1号线工程岩溶洞穴稳定性及其病害处理研究[D].长沙:中南大学, 2012.LONG Yankui. The study of Stability and Processing Technology of Karst Caves in Changsha Metro Line 1[D]. Changsha:CentralSouth University, 2012.
[9]李术才,李树忱,张庆松,等.岩溶裂隙水与不良地质情况超前预报研究[J].岩石力学与工程学报, 2007, 26(2):217-225.LI Shucai, LI Shuchen, ZHANG Qingsong, et al. Forecast of Karst-fractured Groundwater and Defective Geological Conditions[J].Chinese Journal of Rock Mechanics and Engineering, 2007, 26(2):217-225.
[10]李来林,吴青岭,等.用马尔可夫一贝叶斯方法预测孔隙度的分布[J].石油物探, 1995, 34(4):33-41.LI Lailin, WU Qingling, et al. Markov-Bayes Method in Its Estimation of Porosity Distribution[J]. Geophysical Prospecting for Pe?troleum, 1995, 34(4):33-41.
[11]胡华锋,印兴耀,吴国忱.基于贝叶斯分类的储层物性参数联合反演方法[J].石油物探, 2012, 51(3):225-232.HU Huafeng, YIN Xingyao, WU Guochen. Joint Inversion of Petrophysical Parameters Based on Bayesian Classification[J]. Geo?physical Prospecting for Petroleum, 2012, 51(3):225-232.
[12]王芳芳,李景叶,陈小宏.基于马尔科夫链先验模型的贝叶斯岩相识别[J].石油地球物理勘探, 2014, 49(1):183-189.WANG Fangfang, LI Jingye, CHEN Xiaohong. Bayesian Facies Identification Based on Markov-chain prior Model[J]. Oil Geophysi?cal Prospecting, 2014, 49(1):183-189.
[13]铁道部第二勘测设计院.岩溶工程地质[M].北京:中国铁道出版社, 1984.The No. 2 Survey and Design Research Institute of the Ministry of Railways. Karst Engineering Geology[M]. Beijing:China RailwayPublishing House, 1984.
[14]漆立新,云露.塔河油田奥陶系碳酸盐岩岩溶发育特征与主控因素[J].石油与天然气地质, 2010, 31(1):1-12.QI Lixin, YUN Lu. Development Characteristics and Main Controlling Factors of the Ordovician Carbonate Karst in Tahe Oilfield[J]. Oil&Gasgeology, 2010, 31(1):1-12.
[15]刘帆.轮古7井区奥陶系鹰山组风化壳岩溶发育特征及主控因素分析[D].南充:西南石油大学, 2015.LIU Fan. Analysis of Development Features and Master Control Factor of Weathering Crust Karst on Ordovician Strata of Lungu 7Wellblock Yingshan Group[D]. Nanchong:Southwest Petroleum University, 2015.
[16]高玉飞.塔河油田四区奥陶系裂缝精细描述及分布预测[D].北京:中国石油大学, 2009.GAO Yufei. Detailed Description and Distribution Predicting of Ordovician Fractures in Block 4 of Tahe Oilfield[D]. Beijing:ChinaUniversity of Petroleum, 2009.
[17] GEMAN S, GEMAN D. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images[J]. IEEE Transactionson Pattern Analysis&Machine Intelligence, 1984, 6(6):721-741.
[18] PéREZ P. Markov Random Fields and Images[J]. Cwi Quarterly, 1998, 11(4):413-437.
[19]李旭超,朱善安.图像分割中的马尔可夫随机场方法综述[J].中国图象图形学报, 2007, 12(5):789-798.LI Xuchao, ZHU Shan′an. A Survey of the Markov Random Field Method for Image Segmentation[J]. Journal of Image and Graphics,2007, 12(5):789-798.
[20]李龙燕.基于内容的遥感图像分割研究[D].上海:上海交通大学, 2003.LI Longyan. Study on Content-based Segmentation of Remote Sensing Image[D]. Shagnhai:Shanghai Jiaotong University, 2003.
[21]汪宏兵.基于马尔科夫场灰度图像分割的研究[D].合肥:安徽大学, 2014.WANG Hongbing. Research on Gray Image with Markov Random Field[D]. Hefei:Anhui University, 2014.
[22]李军,郝天珧,刘建,等.基于不同邻域系统的马尔可夫链模型的储层岩相随机模拟[J].现代地质, 2006, 20(4):621-627.LI Jun, HAO Tianyao, LIU Jian, et al. Stochastic Simulation of Reservoir Lithofacies Based on Markov Chain Models with DifferentNeighborhood Systems[J]. Geoscience, 2006, 20(4):621-627.
[23]李军,杨晓娟,张晓龙,等.基于三维马尔可夫链模型的岩性随机模拟[J].石油学报, 2012, 33(5):846-853.LI Jun, YANG Xiaojuan, ZHANG Xiaolong, et al. Lithologic Stochastic Simulation Based on the Three-dimensional Markov ChainModel[J]. Acta Petrolei Sinica, 2012, 33(5):846-853.
[24] MARTIN G S. The Marmousi2 Model, Elastic Synthetic Data, and an Analysis of Imaging and Avo in a Structurally Complex Envi?ronment[D]. Houston:University of Houston, 2004.
[25]田玉昆,周辉,袁三一.基于马尔科夫随机场的岩性识别方法[J].地球物理学报, 2013, 56(4):1360-1368.TIAN Yukun, ZHOU Hui, YUAN Sanyi. Lithologic Discrimination Method Based on Markov Random Field[J]. Chinese Journal ofGeophysics, 2013, 56(4):1360-1368.
[2]韩行瑞.岩溶隧道涌水及其专家评判系统[J].中国岩溶, 2004, 23(3):47-52.HAN Xingrui. Karst Water Bursting in Tunnel and Expert Judging System[J]. Carsologica Sinica, 2004, 23(3):47-52.
[3]范威,王川,金晓文,等.吉莲高速公路钟家山隧道涌突水条件分析[J].水文地质工程地质, 2015, 42(2):38-43.FAN Wei, WANG Chuan, JIN Xiaowen, et al. Water Inrush Condition Analysis of the Zhongjiashan Tunnel in the Jilian Highway[J].Hydrogeology&Engineering Geology, 2015, 42(2):38-43.
[4]陈绍林,李茂竹,陈忠恕,等.四川广(安)—渝(重庆)高速公路华蓥山隧道岩溶突水的研究与整治[J].岩石力学与工程学报,2002, 21(9):1344-1349.CHEN Shaolin, LI Maozhu, CHEN Zhongshu, et al. Study and Treatment on Karst Water Outburst in Huayingshan Tunnel for AnyuExpressway from Guang′an of Sichuan to Chongqing[J]. Chinese Journal of Rock Mechanics and Engineering, 2002, 21(9):1344-1349.
[5]李术才,石少帅,李利平,等.三峡库区典型岩溶隧道突涌水灾害防治与应用[J].岩石力学与工程学报, 2014, 33(9):1887-1896.LI Shucai, SHI Shaoshuai, LI Liping, et al. Control of Water Inrush in Typical Karst Tunnels in Three Gorges Reservoir Area and ItsApplication[J]. Chinese Journal of Rock Mechanics and Engineering, 2014, 33(9):1887-1896.
[6]卢平.风险岩溶隧道地质灾害评价与施工控制技术研究[D].成都:成都理工大学, 2014.LU Ping. Geohazard Assessment and Construction Controlling Technology Study of High-risk Karst Tunnel[D]. Chegndu:ChengduUniversity of Technology, 2014.
[7]孙正兵,岳健,赖新军,等.高速铁路上郭关隧道施工遭遇大型溶洞的处理方案研究[J].铁道标准设计, 2015, 59(11):83-87.SUN Zhengbing, YUE Jian, LAI Xinjun, et al. Study on Treatment of Large Karst Cave during Construction of Shangguoguan HighSpeed Railway Tunnel[J]. Railway Standard Design, 2015, 59(11):83-87.
[8]龙艳魁.长沙地铁1号线工程岩溶洞穴稳定性及其病害处理研究[D].长沙:中南大学, 2012.LONG Yankui. The study of Stability and Processing Technology of Karst Caves in Changsha Metro Line 1[D]. Changsha:CentralSouth University, 2012.
[9]李术才,李树忱,张庆松,等.岩溶裂隙水与不良地质情况超前预报研究[J].岩石力学与工程学报, 2007, 26(2):217-225.LI Shucai, LI Shuchen, ZHANG Qingsong, et al. Forecast of Karst-fractured Groundwater and Defective Geological Conditions[J].Chinese Journal of Rock Mechanics and Engineering, 2007, 26(2):217-225.
[10]李来林,吴青岭,等.用马尔可夫一贝叶斯方法预测孔隙度的分布[J].石油物探, 1995, 34(4):33-41.LI Lailin, WU Qingling, et al. Markov-Bayes Method in Its Estimation of Porosity Distribution[J]. Geophysical Prospecting for Pe?troleum, 1995, 34(4):33-41.
[11]胡华锋,印兴耀,吴国忱.基于贝叶斯分类的储层物性参数联合反演方法[J].石油物探, 2012, 51(3):225-232.HU Huafeng, YIN Xingyao, WU Guochen. Joint Inversion of Petrophysical Parameters Based on Bayesian Classification[J]. Geo?physical Prospecting for Petroleum, 2012, 51(3):225-232.
[12]王芳芳,李景叶,陈小宏.基于马尔科夫链先验模型的贝叶斯岩相识别[J].石油地球物理勘探, 2014, 49(1):183-189.WANG Fangfang, LI Jingye, CHEN Xiaohong. Bayesian Facies Identification Based on Markov-chain prior Model[J]. Oil Geophysi?cal Prospecting, 2014, 49(1):183-189.
[13]铁道部第二勘测设计院.岩溶工程地质[M].北京:中国铁道出版社, 1984.The No. 2 Survey and Design Research Institute of the Ministry of Railways. Karst Engineering Geology[M]. Beijing:China RailwayPublishing House, 1984.
[14]漆立新,云露.塔河油田奥陶系碳酸盐岩岩溶发育特征与主控因素[J].石油与天然气地质, 2010, 31(1):1-12.QI Lixin, YUN Lu. Development Characteristics and Main Controlling Factors of the Ordovician Carbonate Karst in Tahe Oilfield[J]. Oil&Gasgeology, 2010, 31(1):1-12.
[15]刘帆.轮古7井区奥陶系鹰山组风化壳岩溶发育特征及主控因素分析[D].南充:西南石油大学, 2015.LIU Fan. Analysis of Development Features and Master Control Factor of Weathering Crust Karst on Ordovician Strata of Lungu 7Wellblock Yingshan Group[D]. Nanchong:Southwest Petroleum University, 2015.
[16]高玉飞.塔河油田四区奥陶系裂缝精细描述及分布预测[D].北京:中国石油大学, 2009.GAO Yufei. Detailed Description and Distribution Predicting of Ordovician Fractures in Block 4 of Tahe Oilfield[D]. Beijing:ChinaUniversity of Petroleum, 2009.
[17] GEMAN S, GEMAN D. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images[J]. IEEE Transactionson Pattern Analysis&Machine Intelligence, 1984, 6(6):721-741.
[18] PéREZ P. Markov Random Fields and Images[J]. Cwi Quarterly, 1998, 11(4):413-437.
[19]李旭超,朱善安.图像分割中的马尔可夫随机场方法综述[J].中国图象图形学报, 2007, 12(5):789-798.LI Xuchao, ZHU Shan′an. A Survey of the Markov Random Field Method for Image Segmentation[J]. Journal of Image and Graphics,2007, 12(5):789-798.
[20]李龙燕.基于内容的遥感图像分割研究[D].上海:上海交通大学, 2003.LI Longyan. Study on Content-based Segmentation of Remote Sensing Image[D]. Shagnhai:Shanghai Jiaotong University, 2003.
[21]汪宏兵.基于马尔科夫场灰度图像分割的研究[D].合肥:安徽大学, 2014.WANG Hongbing. Research on Gray Image with Markov Random Field[D]. Hefei:Anhui University, 2014.
[22]李军,郝天珧,刘建,等.基于不同邻域系统的马尔可夫链模型的储层岩相随机模拟[J].现代地质, 2006, 20(4):621-627.LI Jun, HAO Tianyao, LIU Jian, et al. Stochastic Simulation of Reservoir Lithofacies Based on Markov Chain Models with DifferentNeighborhood Systems[J]. Geoscience, 2006, 20(4):621-627.
[23]李军,杨晓娟,张晓龙,等.基于三维马尔可夫链模型的岩性随机模拟[J].石油学报, 2012, 33(5):846-853.LI Jun, YANG Xiaojuan, ZHANG Xiaolong, et al. Lithologic Stochastic Simulation Based on the Three-dimensional Markov ChainModel[J]. Acta Petrolei Sinica, 2012, 33(5):846-853.
[24] MARTIN G S. The Marmousi2 Model, Elastic Synthetic Data, and an Analysis of Imaging and Avo in a Structurally Complex Envi?ronment[D]. Houston:University of Houston, 2004.
[25]田玉昆,周辉,袁三一.基于马尔科夫随机场的岩性识别方法[J].地球物理学报, 2013, 56(4):1360-1368.TIAN Yukun, ZHOU Hui, YUAN Sanyi. Lithologic Discrimination Method Based on Markov Random Field[J]. Chinese Journal ofGeophysics, 2013, 56(4):1360-1368.