谱分解和C3相干联合识别煤层小断层研究
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摘要
C3相干具有较好的煤层小断层识别能力,但其易受随机噪声的影响,在信噪比较低的情况下容易产生假异常.另一方面,基于S变换的谱分解可以提高地震资料的时频分辨率,并对随机噪声具有一定的压制作用.为提高煤矿采区煤层小断层解释精度,结合谱分解技术与C3相干技术,以提高煤层小断层的解释精度和可靠性.本文分别利用正演剖面和实际三维地震数据,对所提出的方法进行了验证.首先建立了含不同落差的单一煤层模型,利用正演模拟方法获得了其正演剖面和含白噪声剖面.对于这两类剖面,利用S变换获得了其对应于不同频率的谱分解剖面.通过沿煤层反射波提取C3相干属性,获得了不同剖面所对应的C3相干值.对于无噪声地震剖面来说,文中所述方法能明显提高小断层的识别率;对于含白噪声的地震剖面来说,文中所述方法能显著提高所有落差断层的识别率,并基本克服了C3相干算法在低信噪比低情况下容易产生假异常的缺点.将文中所述方法应用到济宁二号煤矿15301工作面的实际三维地震数据中,发现较高频段的谱分解剖面所计算的C3相干同样比常规剖面所计算的C3相干有更好的小断层识别能力.对于煤系地层地质构造较简单的采区来说,利用较高频段谱分解剖面计算的C3相干对落差小于3m的小断层有明显反映.经过井巷工程的实际验证,所解释小断层的可靠性和精度都较高.但当煤系地层地质构造较复杂时,识别落差小于3m小断层的难度较大,还需进一步研究.总之,将谱分解技术和C3相干技术相结合,利用较高频段谱分解剖面计算C3相干,能够明显压制低信噪比所产生的假相干异常,提高煤层小断层的识别精度和可靠性.
According to coal seismic data,C3 coherent technique has good detectability of coal bed's fine faults,but the results is easy affected by random noise.On the other hand,the Spectral Decomposition of S-Transform can improve the resolution of seismic data and suppress random noise.So we combined them together and formed a new technology to make a better interpretation of coal bed's faults.In order to validate the feasibility of this technology,we utilized both forward modeling sections and actual 3D seismic data.At first,we established a geological model containing a single coal bed,and obtained its forward modeling section.After that,10% random noise was added into this section,and we achieved a new section containing white noise.Then,C3 coherences along coal bed's reflection of all sections,including seismic sections and their ISO-frequency sections,were extracted along coal bed.By comparing the C3 coherences of forward modeling section and its ISO-frequency section,we found that the interpreted fine faults of coal bed from ISO-frequency section have higher reliability and precision than normal seismic section.Comparatively to seismic section containing white noise,the detected fine faults from its ISO-frequency section with middle-high frequency were not seriously affected by random noise,and basically avoided the false anomalies of C3 coherence.After applied above method to actual 3D seismic data on 15301 workface in Jilin-2 coalmine,we also found that the ISO-frequency section with middle-high frequency has better identifiable ability than normal seismic section in fine faults detecting.That is to say,in relatively simple condition of coal geological structure,fine faults which fault throws are less than 3m are detectable by middle-high ISO-frequency section.By underground validating,the precision and reliability of interpreted fine faults are acceptable and reasonable.On the contrary,when geological conditions of coal-bearing strata are relatively complex,it is very hard to detect these kinds of fine faults.Thus,some further research is necessary.In a sum,the joint technique of spectral decomposition and C3 coherence can improve the detecting precision and reliability of fine faults of coal bed.However,it is still a long way to go to fully identify the fine faults which fault throws are less than 3 m.
According to coal seismic data,C3 coherent technique has good detectability of coal bed's fine faults,but the results is easy affected by random noise.On the other hand,the Spectral Decomposition of S-Transform can improve the resolution of seismic data and suppress random noise.So we combined them together and formed a new technology to make a better interpretation of coal bed's faults.In order to validate the feasibility of this technology,we utilized both forward modeling sections and actual 3D seismic data.At first,we established a geological model containing a single coal bed,and obtained its forward modeling section.After that,10% random noise was added into this section,and we achieved a new section containing white noise.Then,C3 coherences along coal bed's reflection of all sections,including seismic sections and their ISO-frequency sections,were extracted along coal bed.By comparing the C3 coherences of forward modeling section and its ISO-frequency section,we found that the interpreted fine faults of coal bed from ISO-frequency section have higher reliability and precision than normal seismic section.Comparatively to seismic section containing white noise,the detected fine faults from its ISO-frequency section with middle-high frequency were not seriously affected by random noise,and basically avoided the false anomalies of C3 coherence.After applied above method to actual 3D seismic data on 15301 workface in Jilin-2 coalmine,we also found that the ISO-frequency section with middle-high frequency has better identifiable ability than normal seismic section in fine faults detecting.That is to say,in relatively simple condition of coal geological structure,fine faults which fault throws are less than 3m are detectable by middle-high ISO-frequency section.By underground validating,the precision and reliability of interpreted fine faults are acceptable and reasonable.On the contrary,when geological conditions of coal-bearing strata are relatively complex,it is very hard to detect these kinds of fine faults.Thus,some further research is necessary.In a sum,the joint technique of spectral decomposition and C3 coherence can improve the detecting precision and reliability of fine faults of coal bed.However,it is still a long way to go to fully identify the fine faults which fault throws are less than 3 m.
引文
[1]陈同俊,崔若飞,郎玉泉,等.煤田采区三维地震精细构造解释方法[J].地球物理学进展,2007,22(2):573-578.Chen T J,Cui R F,Lang Y Q,et al.Detail structuralinterpretation methods of coal 3-D seismic[J].Progress inGeophysics(in Chinese),2007,22(2):573-578.
[2]许丽,刘磊,刑延团.小波分析与C3相干体在小断层解释中的应用[J].煤田地质与勘探,2005,33(6):71-73.Xu L,Liu L,Xin Y T.Application of wavelet analysis and C3coherence cube to interpretation of small faults[J].CoalGeology&Exploration(in Chinese),2005,33(6):71-73.
[3]王新,崔若飞,陈同俊.粗糙集与神经网络技术预测煤厚及小断层的方法[J].煤田地质与勘探,2010,38(3):66-68,72.Wang X,Cui R F,Chen T J.Method to predict coal seamthickness and small fault using RS and NN[J].Coal Geology&Exploration(in Chinese),2010,38(3):66-68,72.
[4]于鹏飞,董守华,杨小慧,等.基于突变理论的煤层不连续性检测技术[J].煤田地质与勘探,2011,39(1):57-60.Yu P F,Dong S H,Yang X H,et al.Technology fordetection of coal seam discontinuity based on catastrophetheory[J].Coal Geology&Exploration(in Chinese),2011,39(1):57-60.
[5]王赟,芦俊,于光明.能识别煤层中垂直断距小于3m的断层吗?[J].煤炭学报,2010,35(4):629-634.Wang Z,Lu J,Yu G M.A normal fault in coal seams withdrop height less than 3m can be identified in seismicexploration?[J].Journal of China Coal Society(in Chinese),2010,35(4):629-634.
[6]王怀洪,王秀东,田育鑫.利用相干体技术探测煤矿微小构造方法研究[J].地球物理学进展,2007,22(5):1642-1649.Wang H H,Wang X D,Tian Y X.Study on the method toidentify minor structure of coal mines with the coherencetechnology[J].Progress in Geophysics(in Chinese),2007,22(5):1642-1649.
[7]张绍聪,董守华,程彦.高阶相干技术在煤田断层检测中的应用[J].煤田地质与勘探,2009,37(5):65-67.Zhang S C,Dong S H,Chen Y.Application of high ordercoherence technique in the fault detection in coal field[J].CoalGeology&Exploration(in Chinese),2009,37(5):65-67.
[8]吕霖.淮南矿区三维地震探采对比效果与实例分析[J].煤田地质与勘探,2010,38(4):69-71,76.LüL.Comparing 3D seismic prospecting with miningverification and case study in Huainan coal mine[J].CoalGeology&Exploration(in Chinese),2010,38(4):69-71,76.
[9]刘彦,孟小红.断层识别技术及其在MB油气田的应用[J].地球物理学进展,2008,23(2):515-521.Liu Y,Meng X H.Faults identifying technique and it’sapplication in MB oil-gas field[J].Progress in Geophysics(inChinese),2008,23(2):515-521.
[10]刘喜武,宁俊瑞.地震时频属性及其在油气地震地质技术中应用的综述[J].勘探地球物理进展,2009,32(1):18-22.Liu X W,Lin J R.A review of time frequency attributes andtheir applications in seismic data interpretation for oil&gasgeology[J].Progress in Exploration Geophysics(inChinese),2009,32(1):18-22.
[11]陈香明,韩国庆,田建华,等.地震属性技术在郭局子洼陷沙二段岩性油藏描述中的应用[J].地球物理学进展,2008,23(3):846-851.Chen X M,Han G Q,Tian J H,et al.Seismic attributeapplication to the lithologic reservoir of Es2 member of theGuojuzi sag[J].Progress in Geophysics(in Chinese),2008,23(3):846-851.
[12]李阳,李占东,于亚楠,等.相干体技术识别小断层-以宋芳屯油田芳231区块为例[J].油气地球物理,2009,7(2):25-28.Li Y,Li Z D,Yu Y N,et al.Identifying small faults bycoherent body technique:A case study for Fang 231Area ofSong fang-tun Oilfield[J].Petroleum Geophysics(inChinese),2009,7(2):25-28.
[13]刘峰,牟中海,蒋裕强,等.小断层的地震识别[J].地球物理学进展,2011,26(6):2210-2215.Liu F,Mu Z H,Jiang Y Q,et al.Seismic identification ofsmall fault[J].Progress in Geophysics(in Chinese),2011,26(6):2210-2215.
[14]王彦君,雍学善,刘应如,等.小断层识别技术研究及应用[J].勘探地球物理进展,2007,30(2):135-139.Wang Y J,Yong X S,Liu Y R,et al.Identification of minorfault and its applications[J].Progress in ExplorationGeophysics(in Chinese),2007,30(2):135-139.
[15]朱振宇,吕丁友,桑淑云,等.基于物理小波的频谱分解方法及应用研究[J].地球物理学报,2009,52(8):2152-2157.Zhu Z Y,LüD Y,Song S Y,et al.Research of spectrumdecomposition method based on physical wavelet transformand its application[J].Chinese J.Geophys.(in Chinese),2009,52(8):2152-2157.
[16]张延庆,魏小东,王亚楠,等.谱分解技术在QL油田小断层识别与解释中的应用[J].石油地球物理勘探,2006,41(5):584-586.Zhang Y Q,Wei X D,Wang Y N,et al.Application ofspectral factorization in recognition and interpretation ofminor faults in QL oilfield[J].Oil Geophysical Prospecting(in Chinese),2006,41(5):584-586.
[17]陈波,魏小东,任敦占,等.基于谱分解技术的小断层识别[J].石油地球物理勘探,2010,45(6):890-894.Chen B,Wei X D,Ren D Z,et al.Small fault identificationbased on spectrum decomposition technique[J].OilGeophysical Prospecting(in Chinese),2010,45(6):890-894.
[18]Prakash A,Husain R,Sajer A H A.Delineation of sub-seismic faults-a new approach:Kuwait Example[J].Geophysics,2010,29(3):1352-1356.
[19]Castagna J P,Sun S J,Siegfried R W.Instantaneous spectralanalysis:detection of low-frequency shadows associated withhydrocarbons[J].The Leading Edge,2003,22(2):127-129.
[20]Odebeatu E,Zhang J H,Chapman M,et al.Application ofspectral decomposition to detection of dispersion anomaliesassociated with gas saturation[J].The Leading Edge,2006,25(2):205-210.
[21]Partyka G,Gridley J,Lopez L.Interpretational applicationsof spectral decomposition in reservoir characterization[J].The Leading Edge,1999,18(3):353-360.
[22]Rocha-Legorreta F J.Seismic evidence and geologicaldistinctiveness related to gas hydrates in Mexico[J].TheLeading Edge,2009,28(6):714-717.
[23]Puryear C I,Castagna J P.Layer-thickness determination andstratigraphic interpretation using spectral inversion:Theoryand application[J].Geophysics,2008,73(2):R37-R48.
[24]Hall.Predicting bed thickness with cepstral decomposition[J].The Leading Edge,2006,25(2):199-204.
[25]Sierra J,Marín W,Bonilla M,et al.Structural and stratigraphicinterpretation using spectral decomposition:Applications indeepwater settings[J].SEG Technical Program ExpandedAbstracts,2009,28(4):1850-1854.
[26]Castagna J P,Sun S J.Comparison of spectral decompositionmethods[J].First Break,2006,24(3):75-79.
[27]Stockwell R G,Mansinha L,Lowe R P.Localization of thecomplex spectrum:the S transform[J].IEEE Transactionson Signal Processing,1996,44(4):998-1001.
[2]许丽,刘磊,刑延团.小波分析与C3相干体在小断层解释中的应用[J].煤田地质与勘探,2005,33(6):71-73.Xu L,Liu L,Xin Y T.Application of wavelet analysis and C3coherence cube to interpretation of small faults[J].CoalGeology&Exploration(in Chinese),2005,33(6):71-73.
[3]王新,崔若飞,陈同俊.粗糙集与神经网络技术预测煤厚及小断层的方法[J].煤田地质与勘探,2010,38(3):66-68,72.Wang X,Cui R F,Chen T J.Method to predict coal seamthickness and small fault using RS and NN[J].Coal Geology&Exploration(in Chinese),2010,38(3):66-68,72.
[4]于鹏飞,董守华,杨小慧,等.基于突变理论的煤层不连续性检测技术[J].煤田地质与勘探,2011,39(1):57-60.Yu P F,Dong S H,Yang X H,et al.Technology fordetection of coal seam discontinuity based on catastrophetheory[J].Coal Geology&Exploration(in Chinese),2011,39(1):57-60.
[5]王赟,芦俊,于光明.能识别煤层中垂直断距小于3m的断层吗?[J].煤炭学报,2010,35(4):629-634.Wang Z,Lu J,Yu G M.A normal fault in coal seams withdrop height less than 3m can be identified in seismicexploration?[J].Journal of China Coal Society(in Chinese),2010,35(4):629-634.
[6]王怀洪,王秀东,田育鑫.利用相干体技术探测煤矿微小构造方法研究[J].地球物理学进展,2007,22(5):1642-1649.Wang H H,Wang X D,Tian Y X.Study on the method toidentify minor structure of coal mines with the coherencetechnology[J].Progress in Geophysics(in Chinese),2007,22(5):1642-1649.
[7]张绍聪,董守华,程彦.高阶相干技术在煤田断层检测中的应用[J].煤田地质与勘探,2009,37(5):65-67.Zhang S C,Dong S H,Chen Y.Application of high ordercoherence technique in the fault detection in coal field[J].CoalGeology&Exploration(in Chinese),2009,37(5):65-67.
[8]吕霖.淮南矿区三维地震探采对比效果与实例分析[J].煤田地质与勘探,2010,38(4):69-71,76.LüL.Comparing 3D seismic prospecting with miningverification and case study in Huainan coal mine[J].CoalGeology&Exploration(in Chinese),2010,38(4):69-71,76.
[9]刘彦,孟小红.断层识别技术及其在MB油气田的应用[J].地球物理学进展,2008,23(2):515-521.Liu Y,Meng X H.Faults identifying technique and it’sapplication in MB oil-gas field[J].Progress in Geophysics(inChinese),2008,23(2):515-521.
[10]刘喜武,宁俊瑞.地震时频属性及其在油气地震地质技术中应用的综述[J].勘探地球物理进展,2009,32(1):18-22.Liu X W,Lin J R.A review of time frequency attributes andtheir applications in seismic data interpretation for oil&gasgeology[J].Progress in Exploration Geophysics(inChinese),2009,32(1):18-22.
[11]陈香明,韩国庆,田建华,等.地震属性技术在郭局子洼陷沙二段岩性油藏描述中的应用[J].地球物理学进展,2008,23(3):846-851.Chen X M,Han G Q,Tian J H,et al.Seismic attributeapplication to the lithologic reservoir of Es2 member of theGuojuzi sag[J].Progress in Geophysics(in Chinese),2008,23(3):846-851.
[12]李阳,李占东,于亚楠,等.相干体技术识别小断层-以宋芳屯油田芳231区块为例[J].油气地球物理,2009,7(2):25-28.Li Y,Li Z D,Yu Y N,et al.Identifying small faults bycoherent body technique:A case study for Fang 231Area ofSong fang-tun Oilfield[J].Petroleum Geophysics(inChinese),2009,7(2):25-28.
[13]刘峰,牟中海,蒋裕强,等.小断层的地震识别[J].地球物理学进展,2011,26(6):2210-2215.Liu F,Mu Z H,Jiang Y Q,et al.Seismic identification ofsmall fault[J].Progress in Geophysics(in Chinese),2011,26(6):2210-2215.
[14]王彦君,雍学善,刘应如,等.小断层识别技术研究及应用[J].勘探地球物理进展,2007,30(2):135-139.Wang Y J,Yong X S,Liu Y R,et al.Identification of minorfault and its applications[J].Progress in ExplorationGeophysics(in Chinese),2007,30(2):135-139.
[15]朱振宇,吕丁友,桑淑云,等.基于物理小波的频谱分解方法及应用研究[J].地球物理学报,2009,52(8):2152-2157.Zhu Z Y,LüD Y,Song S Y,et al.Research of spectrumdecomposition method based on physical wavelet transformand its application[J].Chinese J.Geophys.(in Chinese),2009,52(8):2152-2157.
[16]张延庆,魏小东,王亚楠,等.谱分解技术在QL油田小断层识别与解释中的应用[J].石油地球物理勘探,2006,41(5):584-586.Zhang Y Q,Wei X D,Wang Y N,et al.Application ofspectral factorization in recognition and interpretation ofminor faults in QL oilfield[J].Oil Geophysical Prospecting(in Chinese),2006,41(5):584-586.
[17]陈波,魏小东,任敦占,等.基于谱分解技术的小断层识别[J].石油地球物理勘探,2010,45(6):890-894.Chen B,Wei X D,Ren D Z,et al.Small fault identificationbased on spectrum decomposition technique[J].OilGeophysical Prospecting(in Chinese),2010,45(6):890-894.
[18]Prakash A,Husain R,Sajer A H A.Delineation of sub-seismic faults-a new approach:Kuwait Example[J].Geophysics,2010,29(3):1352-1356.
[19]Castagna J P,Sun S J,Siegfried R W.Instantaneous spectralanalysis:detection of low-frequency shadows associated withhydrocarbons[J].The Leading Edge,2003,22(2):127-129.
[20]Odebeatu E,Zhang J H,Chapman M,et al.Application ofspectral decomposition to detection of dispersion anomaliesassociated with gas saturation[J].The Leading Edge,2006,25(2):205-210.
[21]Partyka G,Gridley J,Lopez L.Interpretational applicationsof spectral decomposition in reservoir characterization[J].The Leading Edge,1999,18(3):353-360.
[22]Rocha-Legorreta F J.Seismic evidence and geologicaldistinctiveness related to gas hydrates in Mexico[J].TheLeading Edge,2009,28(6):714-717.
[23]Puryear C I,Castagna J P.Layer-thickness determination andstratigraphic interpretation using spectral inversion:Theoryand application[J].Geophysics,2008,73(2):R37-R48.
[24]Hall.Predicting bed thickness with cepstral decomposition[J].The Leading Edge,2006,25(2):199-204.
[25]Sierra J,Marín W,Bonilla M,et al.Structural and stratigraphicinterpretation using spectral decomposition:Applications indeepwater settings[J].SEG Technical Program ExpandedAbstracts,2009,28(4):1850-1854.
[26]Castagna J P,Sun S J.Comparison of spectral decompositionmethods[J].First Break,2006,24(3):75-79.
[27]Stockwell R G,Mansinha L,Lowe R P.Localization of thecomplex spectrum:the S transform[J].IEEE Transactionson Signal Processing,1996,44(4):998-1001.
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