利用微地震事件重构三维缝网
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摘要
前人大多从定性角度利用微地震事件点分析体积缝网的二维建模,或者利用微地震事件点提取个别裂缝参数以校核基于一定假设的随机离散裂缝网络,但缺乏基于微地震事件的稳健、直接的三维缝网重构方法。为此,根据微地震事件点和裂缝面的几何相关性,使用随机模拟一致性算法(RANSAC)识别裂缝面产状,在裂缝几何模型优选的基础上,开发了一套稳健的三维缝网重构方法(RFM3D)。为了分析算法的有效性和稳健性,提出了缝网相似性评价指标(ADI),使用蒙特卡罗方法生成随机缝网后离散为人工的模拟事件点,在增加不同比例的噪点后进行RFM3D。研究结果表明:①室内压裂实验发现,可用随机多边形模型描述实际裂缝形状。②RFM3D算法易于匹配复杂的裂缝几何模型,在一般条件下该算法至少能克服10%的噪点干扰,可较准确地重构压裂缝网的几何形态,算法具有较好的稳健性。③随着噪点比例增大,ADI随噪点比例满足logistic增长模式;随着缝网中裂缝数目的增多,ADI临界点也随之降低。因此,在重构大规模体积缝网时噪点比例应严格控制在10%以下才能得到稳定、可靠的结果。
Previous research mainly focused on building2 Dfracture models from the point view of qualitative and macroscopic.Microseismic events were often used to deprive some critic parameters to calibrate random discrete fracture model based on certain assumptions.As a result,there is a lack of robust methods to build 3 Dfracture network after fracturing.To solve this problem,we firstly apply the random sample consensus(RANSAC)method to detect fracture planes according to the geometric correlation between microseismic events and real fracture networks.After that,we develop a computing algorithm called robust 3 D fracture reconstruction(RFM3 D)to reconstruct 3 Dfracture network on the basis of building realistic single fracture geometric model.To verify the robustness and effectiveness of the algorithm,we put forward average distance index(ADI)to evaluate the similarity between two fracture networks.Also,analog events generated by Monte Carlo simulation added in noise points of different proportions are used to test the algorithm.The results show that:(1)Convex polygons can be used to describe real fracture geometric shape after fracturing experiments;(2)RFM3 Dis easy to adapt different complex geometric models.It can eliminate effects of 10% noise and give a relatively accurate reconstruction of 3 D fracture network under normal circumstances.Therefore,it has good robustness;(3)The fracture network similarity index(ADI)increase with noise ratio in a logistic pattern and critical ADI value decreased with increase of noise ratio.Accordingly,it is necessary to eliminate noise in events under 10%to obtain an accurate and robust fracture network reconstruction.
Previous research mainly focused on building2 Dfracture models from the point view of qualitative and macroscopic.Microseismic events were often used to deprive some critic parameters to calibrate random discrete fracture model based on certain assumptions.As a result,there is a lack of robust methods to build 3 Dfracture network after fracturing.To solve this problem,we firstly apply the random sample consensus(RANSAC)method to detect fracture planes according to the geometric correlation between microseismic events and real fracture networks.After that,we develop a computing algorithm called robust 3 D fracture reconstruction(RFM3 D)to reconstruct 3 Dfracture network on the basis of building realistic single fracture geometric model.To verify the robustness and effectiveness of the algorithm,we put forward average distance index(ADI)to evaluate the similarity between two fracture networks.Also,analog events generated by Monte Carlo simulation added in noise points of different proportions are used to test the algorithm.The results show that:(1)Convex polygons can be used to describe real fracture geometric shape after fracturing experiments;(2)RFM3 Dis easy to adapt different complex geometric models.It can eliminate effects of 10% noise and give a relatively accurate reconstruction of 3 D fracture network under normal circumstances.Therefore,it has good robustness;(3)The fracture network similarity index(ADI)increase with noise ratio in a logistic pattern and critical ADI value decreased with increase of noise ratio.Accordingly,it is necessary to eliminate noise in events under 10%to obtain an accurate and robust fracture network reconstruction.
引文
[1] 闫鑫,胡天跃,何怡原.地表测斜仪在监测复杂水力裂缝中的应用[J].石油地球物理勘探,2016,51(3):480-486.YAN Xin,HU Tianyue,HE Yiyuan.Application of surface tiltmeter in monitoring complicated hydraulic fractures[J].Oil Geophysical Prospecting,2016,51(3):480-486.
[2] 严永新,张永华,陈祥,等.微地震技术在裂缝监测中的应用研究[J].地学前缘,2013,20(3): 270-274.YAN Yongxin,ZHANG Yonghua,CHEN Xiang,et al.The application of microseismic technology in fracture monitoring[J].Earth Science Frontiers,2013,20(3):270-274.
[3] 刘博,梁雪莉,容娇君,等.非常规油气层压裂微地震监测技术及应用[J].石油地质与工程,2016,30(1):142-145.LIU Bo,LIANG Xueli,RONG Jiaojun,et al.Microseismic monitoring technology and its application in unconventional reservoir fracturing[J].Petroleum Geology and Engineering,2016,30(1):142-145.
[4] 容娇君,李彦鹏,徐刚,等.微地震裂缝检测技术应用实例[J].石油地球物理勘探,2015,50(5):919-924.RONG Jiaojun,LI Yanpeng,XU Gang,et al.Fracture detection with microseismic[J].Oil Geophysical Prospecting,2015,50(5):919-924.
[5] 张山,刘清林,赵群,等.微地震监测技术在油田开发中的应用[J].石油物探,2002,41(2):226-231.ZHANG Shan,LIU Qinglin,ZHAO Qun,et al.Application of microseismic monitoring technology in development of oil field[J].Geophysical Prospecting for Petroleum,2002,41(2):226-231.
[6] 唐杰,方兵,蓝阳,等.压裂诱发的微地震震源机制及信号传播特性[J].石油地球物理探,2015,50(4):643-649.TANG Jie,FANG Bing,LAN Yang,et al.Focal mechanism of micro-seismic induced by hydro-fracture and its signal propagation[J].Oil Geophysical Prospecting,2015,50(4):643-649.
[7] Cai M,Kaiser P K,Martin C D.Quantification of rock mass damage in underground excavations from microseismic event monitoring[J].International Journal of Rock Mechanics and Mining Sciences,2001,38(8):1135-1145.
[8] Sherilyn W,Ozgen C,Billingsley R L.Methods to cali-brate low-amplitude surface monitoring microseismic results via integration of geology,production data and reservoir simulation[J].CSEG Recorder,2012,37(8):32-38.
[9] Maxwell S C,Weng X,Kresse O,et al.Modeling microseismic hydraulic fracture deformation[C].SPE Annual Technical Conference and Exhibition,2013,1-10.
[10] 赵争光,秦月霜,杨瑞召.地面微地震监测致密砂岩储层水力裂缝[J].地球物理学进展,2014,29(5):2136-2139.ZHAO Zhengguang,QIN Yueshuang,YANG Ruizhao.Hydraulic fracture mapping for a tight sands reservoir by surface based microseismic monitoring[J].Progress in Geophysics,2014,29(5):2136-2139.
[11] Yu X,Rutledge J,Leaney S,et al.Discrete fracture network generation from microseismic data by use of moment tensor and event location constrained hough transforms[J].SPE Journal,2016,21(1):221-232.
[12] 杨瑞召,李德伟,庞海玲,等.页岩气压裂微地震监测中的裂缝成像方法[J].天然气工业,2017,37(5):31-37.YANG Ruizhao,LI Dewei,PANG Hailing,et al.Fracture imaging of the surface based microseismic monitoring in shale gas fracking:methods and application[J].Natural Gas Industry,2017,37(5):31-37.
[13] 张云银,刘海宁,李红梅,等.应用微地震监测数据估算储层压裂改造体积[J].石油地球物理勘探,2017,52(2):309-314.ZHANG Yunyin,LIU Haining,LI Hongmei,et al.Reservoir fracturing volume estimation with micro-seismic monitoring data[J].Oil Geophysical Prospecting,2017,52(2):309-314.
[14] 宋维琪,冯超.微地震有效事件自动识别与定位方法[J].石油地球物理勘探,2013,48(2):283-288.SONG Weiqi,FENG Chao.Automatic identification and localization of microseismic effective events[J].Oil Geophysical Prospecting,2013,48(2):283-288.
[15] Baecher G B.Statistical analysis of rock mass fracturing[J].Journal of the International Association for Mathematical Geology,1983,15(2):329-348.
[16] Geier J E,Lee K,Dershowitz W S.Field validation of conceptual models for fracture geometry[J].Transactions of American Geophysical Union,1988,69(44):1177.
[17] Dershowitz W S.Rock Joint Systems[D].Massachu-setts Institute of Technology,Massachusetts,USA,1984,520-534.
[18] Stsub I,Fredriksson A,Outters N.Strategy for a rock mechanics site descriptive model[R].SKB Report R-02-02,Swedish Nuclear Fuel and Waste Management Co,2002,25-26.
[19] Alghalandis Y F.ADFNE:Open source software for discrete fracture network engineering,two and three-dimensional applications[J].Computers & Geosciences,2017,102(5):1-11.
[20] Liang J,Edelsbrunner H,Fu P,et al.Analytical shape computation of macromolecules:I.Molecular area andvolume through alpha shape[J].Proteins,1998,33(1):1-17.
[21] Fisvhler M A,Bolles R C.Random sample consensus: a paradigm for model fitting with applications to ima-ge analysis and automated cartography[J].Communications of the ACM,1981,24(6):381-395.
[22] 刘宏申,秦锋.确定轮廓形状匹配中形状描述函数的方法[J].华中科技大学学报(自然科学版),2005,33(4):13-16.LIU Hongshen,QIN Feng.Method of determining the function of description of shape in shape matching[J].Journal of Huazhong University of Science & Technology (Nature Science Edition),2005,33(4):13-16.
[23] 黄继新,彭仕宓,王小军,等.成像测井资料在裂缝和地应力研究中的应用[J].石油学报,2006,27(6):65-69.HUANG Jixin,PENG Shimi,WANG Xiaojun,et al.Applications of imaging logging data in the research of fracture and ground stress[J].Acta Petrolei Sinica,2006,27(6):65-69.
[24] 李亚男.页岩气储层测井评价及其应用——以川南地区为例[D].北京:中国矿业大学(北京),2014.
[25] Peng Tan,Yan Jin,Ke Han,et al.Analysis of hydraulic fracture initiation and vertical propagation behavior in laminated shale formation[J].Fuel,2017,206(10):482-493.
[2] 严永新,张永华,陈祥,等.微地震技术在裂缝监测中的应用研究[J].地学前缘,2013,20(3): 270-274.YAN Yongxin,ZHANG Yonghua,CHEN Xiang,et al.The application of microseismic technology in fracture monitoring[J].Earth Science Frontiers,2013,20(3):270-274.
[3] 刘博,梁雪莉,容娇君,等.非常规油气层压裂微地震监测技术及应用[J].石油地质与工程,2016,30(1):142-145.LIU Bo,LIANG Xueli,RONG Jiaojun,et al.Microseismic monitoring technology and its application in unconventional reservoir fracturing[J].Petroleum Geology and Engineering,2016,30(1):142-145.
[4] 容娇君,李彦鹏,徐刚,等.微地震裂缝检测技术应用实例[J].石油地球物理勘探,2015,50(5):919-924.RONG Jiaojun,LI Yanpeng,XU Gang,et al.Fracture detection with microseismic[J].Oil Geophysical Prospecting,2015,50(5):919-924.
[5] 张山,刘清林,赵群,等.微地震监测技术在油田开发中的应用[J].石油物探,2002,41(2):226-231.ZHANG Shan,LIU Qinglin,ZHAO Qun,et al.Application of microseismic monitoring technology in development of oil field[J].Geophysical Prospecting for Petroleum,2002,41(2):226-231.
[6] 唐杰,方兵,蓝阳,等.压裂诱发的微地震震源机制及信号传播特性[J].石油地球物理探,2015,50(4):643-649.TANG Jie,FANG Bing,LAN Yang,et al.Focal mechanism of micro-seismic induced by hydro-fracture and its signal propagation[J].Oil Geophysical Prospecting,2015,50(4):643-649.
[7] Cai M,Kaiser P K,Martin C D.Quantification of rock mass damage in underground excavations from microseismic event monitoring[J].International Journal of Rock Mechanics and Mining Sciences,2001,38(8):1135-1145.
[8] Sherilyn W,Ozgen C,Billingsley R L.Methods to cali-brate low-amplitude surface monitoring microseismic results via integration of geology,production data and reservoir simulation[J].CSEG Recorder,2012,37(8):32-38.
[9] Maxwell S C,Weng X,Kresse O,et al.Modeling microseismic hydraulic fracture deformation[C].SPE Annual Technical Conference and Exhibition,2013,1-10.
[10] 赵争光,秦月霜,杨瑞召.地面微地震监测致密砂岩储层水力裂缝[J].地球物理学进展,2014,29(5):2136-2139.ZHAO Zhengguang,QIN Yueshuang,YANG Ruizhao.Hydraulic fracture mapping for a tight sands reservoir by surface based microseismic monitoring[J].Progress in Geophysics,2014,29(5):2136-2139.
[11] Yu X,Rutledge J,Leaney S,et al.Discrete fracture network generation from microseismic data by use of moment tensor and event location constrained hough transforms[J].SPE Journal,2016,21(1):221-232.
[12] 杨瑞召,李德伟,庞海玲,等.页岩气压裂微地震监测中的裂缝成像方法[J].天然气工业,2017,37(5):31-37.YANG Ruizhao,LI Dewei,PANG Hailing,et al.Fracture imaging of the surface based microseismic monitoring in shale gas fracking:methods and application[J].Natural Gas Industry,2017,37(5):31-37.
[13] 张云银,刘海宁,李红梅,等.应用微地震监测数据估算储层压裂改造体积[J].石油地球物理勘探,2017,52(2):309-314.ZHANG Yunyin,LIU Haining,LI Hongmei,et al.Reservoir fracturing volume estimation with micro-seismic monitoring data[J].Oil Geophysical Prospecting,2017,52(2):309-314.
[14] 宋维琪,冯超.微地震有效事件自动识别与定位方法[J].石油地球物理勘探,2013,48(2):283-288.SONG Weiqi,FENG Chao.Automatic identification and localization of microseismic effective events[J].Oil Geophysical Prospecting,2013,48(2):283-288.
[15] Baecher G B.Statistical analysis of rock mass fracturing[J].Journal of the International Association for Mathematical Geology,1983,15(2):329-348.
[16] Geier J E,Lee K,Dershowitz W S.Field validation of conceptual models for fracture geometry[J].Transactions of American Geophysical Union,1988,69(44):1177.
[17] Dershowitz W S.Rock Joint Systems[D].Massachu-setts Institute of Technology,Massachusetts,USA,1984,520-534.
[18] Stsub I,Fredriksson A,Outters N.Strategy for a rock mechanics site descriptive model[R].SKB Report R-02-02,Swedish Nuclear Fuel and Waste Management Co,2002,25-26.
[19] Alghalandis Y F.ADFNE:Open source software for discrete fracture network engineering,two and three-dimensional applications[J].Computers & Geosciences,2017,102(5):1-11.
[20] Liang J,Edelsbrunner H,Fu P,et al.Analytical shape computation of macromolecules:I.Molecular area andvolume through alpha shape[J].Proteins,1998,33(1):1-17.
[21] Fisvhler M A,Bolles R C.Random sample consensus: a paradigm for model fitting with applications to ima-ge analysis and automated cartography[J].Communications of the ACM,1981,24(6):381-395.
[22] 刘宏申,秦锋.确定轮廓形状匹配中形状描述函数的方法[J].华中科技大学学报(自然科学版),2005,33(4):13-16.LIU Hongshen,QIN Feng.Method of determining the function of description of shape in shape matching[J].Journal of Huazhong University of Science & Technology (Nature Science Edition),2005,33(4):13-16.
[23] 黄继新,彭仕宓,王小军,等.成像测井资料在裂缝和地应力研究中的应用[J].石油学报,2006,27(6):65-69.HUANG Jixin,PENG Shimi,WANG Xiaojun,et al.Applications of imaging logging data in the research of fracture and ground stress[J].Acta Petrolei Sinica,2006,27(6):65-69.
[24] 李亚男.页岩气储层测井评价及其应用——以川南地区为例[D].北京:中国矿业大学(北京),2014.
[25] Peng Tan,Yan Jin,Ke Han,et al.Analysis of hydraulic fracture initiation and vertical propagation behavior in laminated shale formation[J].Fuel,2017,206(10):482-493.