基于单道SVD和振幅比的地面微地震资料去噪方法
|
摘要
针对地面微地震资料强周期干扰和随机干扰突出的特点以及单一去噪方法无法有效压制噪声的问题,提出了基于单道奇异值分解(singular value decomposition,SVD)和振幅比的联合去噪方法。首先利用单道微地震记录构建分解矩阵,使矩阵各维具有较强的相关性,然后对分解矩阵进行奇异值分解,选取数值居中部分奇异值进行矩阵重构,以达到压制单道微地震记录强周期干扰的目的。其次采用具有伸缩特性时窗的振幅比法改善有效信号与随机噪声的统计特性差异,有效压制微地震资料中的随机噪声。理论模型数据和四川某地区地面微地震射孔资料应用结果表明,联合去噪方法有效地压制了微地震记录中的噪声,提高了资料的信噪比,在很大程度上改善了单一去噪方法无法较好突出微地震有效信号的不足,为后期微地震资料的处理与解释奠定了良好的基础。
In view of ground microseismic data with strong periodic disturbance and random noise,single de-noising method cannot suppress noise effectively.Therefore,ajoint denoising method combining single-channel singular value decomposition(SVD)and amplitude ratio is proposed.Initially,a decomposition matrix is constructed using single-channel microseismic record to make the dimensions of the matrix have strong correlation.Next,the SVD is used to the decomposition matrix,then a few of singular values in the middle of singular value sequence are selected for the matrix reconstruction,to suppress the strong periodic disturbance in single-channel in microseismic record.Then,the amplitude ratio method with the expansion time window is adopted to improve the statistical characteristics of effective signal and random noise,to suppress random noise effectively.Testing on both synthetic data and ground microseismic perforation data in a certain area of Sichuan showed that the joint denoising method can highlight effective signals and improve signal-to-noise ratio of microseismic data effectively,which lays a good foundation for the processing and interpretation of microseismic data.
In view of ground microseismic data with strong periodic disturbance and random noise,single de-noising method cannot suppress noise effectively.Therefore,ajoint denoising method combining single-channel singular value decomposition(SVD)and amplitude ratio is proposed.Initially,a decomposition matrix is constructed using single-channel microseismic record to make the dimensions of the matrix have strong correlation.Next,the SVD is used to the decomposition matrix,then a few of singular values in the middle of singular value sequence are selected for the matrix reconstruction,to suppress the strong periodic disturbance in single-channel in microseismic record.Then,the amplitude ratio method with the expansion time window is adopted to improve the statistical characteristics of effective signal and random noise,to suppress random noise effectively.Testing on both synthetic data and ground microseismic perforation data in a certain area of Sichuan showed that the joint denoising method can highlight effective signals and improve signal-to-noise ratio of microseismic data effectively,which lays a good foundation for the processing and interpretation of microseismic data.
引文
[1]龙胜祥,曹艳,朱杰,等.中国页岩气发展前景及相关问题初探[J].石油与天然气地质,2016,37(6):847-853LONG S X,CAO Y,ZHU J,et al.A preliminary study on prospects for shale gas industry in China and relevant issues[J].Oil&Gas Geology,2016,37(6):847-853
[2]王莉,于荣泽,张晓伟,等.中、美页岩气开发现状的对比与思考[J].科技导报,2016,34(23):28-31WANG L,YU R,ZHANG X W,et al.Shale gas development in China and US:Comparison and thinking[J].Science&Technology Review,2016,34(23):28-31
[3]张东晓,杨婷云,吴天昊,等.页岩气开发机理和关键问题[J].科学通报,2016,61(1):62-71ZHANG D X,YANG T Y,WU T H,et al.Recovery mechanisms and key issues in shale gas development[J].Chinese Science Bulletin,2016,61(1):62-71
[4]朱海波,杨心超,廖如刚,等.基于微地震裂缝参数反演的解释与应用研究[J].石油物探,2017,56(1):150-157ZHU H B,YANG X C,LIAO R G.Microseismic fracture interpretation and application based on parameters inversion[J].Geophysical Prospecting for Petroleum,2017,56(1):150-157
[5]李金磊.涪陵焦石坝页岩气层压力预测技术研究[J].石油物探,2017,56(4):567-574LI J L.Pressure prediction of Jiaoshiba shale gas reservoir in the Fuling Shale Gasfield[J].Geophysical Prospecting for Petroleum,2017,56(4):567-574
[6] LIN Y,ZHANG H J.Imaging hydraulic fractures by microseismic migration for downhole monitoring system[J].Physics of the Earth and Planetary Interiors,2016,261(12):88-97
[7] TANG C A,LI L C,XU N W,et al.Microseismic monitoring and numerical simulation on the stability of high-steep rock slope in hydropower engineering[J].Journal of Rock Mechanics and Geotechnical Engineering,2015,7(5):493-508
[8]崔庆辉,尹成,刁瑞,等.地面微地震监测数据处理难点及对策[J].油气藏评价与开发,2017,7(1):7-13CUI Q H,YIN C,DIAO R,et al.Difficulties and countermeasure of surface microseismic monitoring data processing[J].Reservoir Evaluation and Development,2017,7(1):7-13
[9]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):31-37YANG R Z,LI D W,PANG H L,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
[10]毛庆辉,王彦春,王鹏,等.改进的微震事件反演重定位方法及其应用[J].石油物探,2015,54(3):359-366MAO Q H,WANG Y C,WANG P,et al.The improved microseismic event relocation method and its application[J].Geophysical Prospecting for Petroleum,2015,54(3):359-366
[11]马永生,张建宁,赵培荣,等.物探技术需求分析及攻关方向思考——以中国石化油气勘探为例[J].石油物探,2016,55(1):1-9MA Y S,ZHANG J N,ZHAO P R,et al.Requirement analysis and research direction for the geophysical prospecting technology of SINOPEC[J].Geophysical Prospecting for Petroleum,2016,55(1):1-9
[12] ZHENG Y K,WANG Y B,CHANG X.Wave equation based microseismic source location and velocity inversion[J].Physics of the Earth and Planetary Interiors,2016,261(12):46-53
[13] ZHANG J Z,LIU H,ZOU Z H,et al.Velocity modeling and inversion techniques for locating microseismic events in unconventional reservoirs[J].Journal of Earth Science,2015,26(4):495-501
[14]秦晅,蔡建超,刘少勇,等.基于经验模态分解互信息熵与同步压缩变换的微地震信号去噪方法研究[J].石油物探,2017,56(4):658-666QIN X,CAI J C,LIU S Y,et al.Microseismic data denoising method based on EMD mutual information entropy and synchrosqueezing transform[J].Geophysical Prospecting for Petroleum,2017,56(5):658-666
[15]郭奇,曾昭发,于晨霞,等.基于高精度字典学习算法的地震随机噪声压制[J].物探与化探,2017,41(5):907-913GUO Q,ZENG Z F,YU C X,et al.Seismic random noise suppression based on the high-precision dictionary learning algorithm[J].Geophysical and Geochemical Exploration,2017,41(5):907-913
[16]宋维琪,刘太伟.地面微地震资料τ-p变换噪声压制[J].石油地球物理勘探,2015,50(1):48-53SONG W Q,LIU T W.Surface microseismic noise suppression withτ-ptransform[J].Oil Geophysical Prospecting,2015,50(1):48-53
[17]曹静杰,杨志权,杨勇,等.一种基于曲波变换的自适应地震随机噪声消除方法[J].石油物探,2018,57(1):72-78CAO J J,YANG Z Q,YANG Y,et al.An adaptive seismic random noise elimination method based on Curvelet transform[J].Geophysical Prospecting for Petroleum,2018,57(1):72-78
[18]刁瑞,单联瑜,尚新民,等.微地震监测数据时频域去噪方法[J].物探与化探,2015,39(1):112-117DIAO R,SHAN L Y,SHANG X M,et al.The denoising method for microseismic monitoring data in timefrequency domain[J].Geophysical and Geochemical Exploration,2015,39(1):112-117
[19]刁瑞,吴国忱,尚新民,等.地面阵列式微地震数据盲源分离去噪方法[J].物探与化探,2017,41(3):521-526DIAO R,WU G C,SHANG X M,et al.The blind separation denoising method for surface array micro-seismic data[J].Geophysical and Geochemical Exploration,2017,41(3):521-526
[20]刘昕,陈祖斌,王东鹤,等.基于非下采样shearlet变换的微地震随机噪声压制[J].煤炭技术,2016,35(1):128-129LIU X,CHEN Z B,WANG D H,et al.Microseismic random noise attenuation based on non-subsampled shearlet transform[J].Coal Technology,2016,35(1):128-129
[21]胡永泉,尹成,潘树林,等.基于单道奇异值分解的微地震资料去噪方法[J].石油天然气学报,2013,35(4):64-69HU Y Q,YIN C,PAN S L,et al.The denoising method based on single-channel SVD for microseismic data[J].Journal of Oil and Gas Technology,2013,35(4):64-69
[22]邵婕,孙成禹,唐杰,等.基于字典训练的小波域稀疏表示微地震去噪方法[J].石油地球物理勘探,2016,51(2):254-260SHAO J,SUN C Y,TANG J,et al.The wavelet domain sparse representation microseismic denoising method based on dictionary training[J].Oil Geophysical Prospeccting,2016,51(2):254-260
[23]黄艳林.SVD与EMD联合去噪方法在地震勘探数据处理中的研究与应用[J].地震工程学报,2016,38(2):323-326HUANG Y L.Application of joint denoising using empirical mode decomposition and singular value decomposition in seismic data processing[J].China Earthquake Engineering Journal,2016,38(2):323-326
[24]詹毅,赵波.自动追踪SVD压制线性干扰方法的改进[J].石油地球物理勘探,2008,43(2):158-160ZHAN Y,ZHAO B.Improvement of suppressing linear interference by automatically tracing SVD[J].Oil Geophysical Prospecting,2008,43(2):158-160
[25]詹毅,周熙襄.小波包分析与奇异值分解(SVD)叠前去噪方法[J].石油地球物理勘探,2004,39(4):394-397ZHAN Y,ZHOU X X.Analysis of wavelet package and prestack noise-suppressed method in singular value decomposition(SVD)[J].Oil Geophysical Prospecting,2004,39(4):394-397
[2]王莉,于荣泽,张晓伟,等.中、美页岩气开发现状的对比与思考[J].科技导报,2016,34(23):28-31WANG L,YU R,ZHANG X W,et al.Shale gas development in China and US:Comparison and thinking[J].Science&Technology Review,2016,34(23):28-31
[3]张东晓,杨婷云,吴天昊,等.页岩气开发机理和关键问题[J].科学通报,2016,61(1):62-71ZHANG D X,YANG T Y,WU T H,et al.Recovery mechanisms and key issues in shale gas development[J].Chinese Science Bulletin,2016,61(1):62-71
[4]朱海波,杨心超,廖如刚,等.基于微地震裂缝参数反演的解释与应用研究[J].石油物探,2017,56(1):150-157ZHU H B,YANG X C,LIAO R G.Microseismic fracture interpretation and application based on parameters inversion[J].Geophysical Prospecting for Petroleum,2017,56(1):150-157
[5]李金磊.涪陵焦石坝页岩气层压力预测技术研究[J].石油物探,2017,56(4):567-574LI J L.Pressure prediction of Jiaoshiba shale gas reservoir in the Fuling Shale Gasfield[J].Geophysical Prospecting for Petroleum,2017,56(4):567-574
[6] LIN Y,ZHANG H J.Imaging hydraulic fractures by microseismic migration for downhole monitoring system[J].Physics of the Earth and Planetary Interiors,2016,261(12):88-97
[7] TANG C A,LI L C,XU N W,et al.Microseismic monitoring and numerical simulation on the stability of high-steep rock slope in hydropower engineering[J].Journal of Rock Mechanics and Geotechnical Engineering,2015,7(5):493-508
[8]崔庆辉,尹成,刁瑞,等.地面微地震监测数据处理难点及对策[J].油气藏评价与开发,2017,7(1):7-13CUI Q H,YIN C,DIAO R,et al.Difficulties and countermeasure of surface microseismic monitoring data processing[J].Reservoir Evaluation and Development,2017,7(1):7-13
[9]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):31-37YANG R Z,LI D W,PANG H L,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
[10]毛庆辉,王彦春,王鹏,等.改进的微震事件反演重定位方法及其应用[J].石油物探,2015,54(3):359-366MAO Q H,WANG Y C,WANG P,et al.The improved microseismic event relocation method and its application[J].Geophysical Prospecting for Petroleum,2015,54(3):359-366
[11]马永生,张建宁,赵培荣,等.物探技术需求分析及攻关方向思考——以中国石化油气勘探为例[J].石油物探,2016,55(1):1-9MA Y S,ZHANG J N,ZHAO P R,et al.Requirement analysis and research direction for the geophysical prospecting technology of SINOPEC[J].Geophysical Prospecting for Petroleum,2016,55(1):1-9
[12] ZHENG Y K,WANG Y B,CHANG X.Wave equation based microseismic source location and velocity inversion[J].Physics of the Earth and Planetary Interiors,2016,261(12):46-53
[13] ZHANG J Z,LIU H,ZOU Z H,et al.Velocity modeling and inversion techniques for locating microseismic events in unconventional reservoirs[J].Journal of Earth Science,2015,26(4):495-501
[14]秦晅,蔡建超,刘少勇,等.基于经验模态分解互信息熵与同步压缩变换的微地震信号去噪方法研究[J].石油物探,2017,56(4):658-666QIN X,CAI J C,LIU S Y,et al.Microseismic data denoising method based on EMD mutual information entropy and synchrosqueezing transform[J].Geophysical Prospecting for Petroleum,2017,56(5):658-666
[15]郭奇,曾昭发,于晨霞,等.基于高精度字典学习算法的地震随机噪声压制[J].物探与化探,2017,41(5):907-913GUO Q,ZENG Z F,YU C X,et al.Seismic random noise suppression based on the high-precision dictionary learning algorithm[J].Geophysical and Geochemical Exploration,2017,41(5):907-913
[16]宋维琪,刘太伟.地面微地震资料τ-p变换噪声压制[J].石油地球物理勘探,2015,50(1):48-53SONG W Q,LIU T W.Surface microseismic noise suppression withτ-ptransform[J].Oil Geophysical Prospecting,2015,50(1):48-53
[17]曹静杰,杨志权,杨勇,等.一种基于曲波变换的自适应地震随机噪声消除方法[J].石油物探,2018,57(1):72-78CAO J J,YANG Z Q,YANG Y,et al.An adaptive seismic random noise elimination method based on Curvelet transform[J].Geophysical Prospecting for Petroleum,2018,57(1):72-78
[18]刁瑞,单联瑜,尚新民,等.微地震监测数据时频域去噪方法[J].物探与化探,2015,39(1):112-117DIAO R,SHAN L Y,SHANG X M,et al.The denoising method for microseismic monitoring data in timefrequency domain[J].Geophysical and Geochemical Exploration,2015,39(1):112-117
[19]刁瑞,吴国忱,尚新民,等.地面阵列式微地震数据盲源分离去噪方法[J].物探与化探,2017,41(3):521-526DIAO R,WU G C,SHANG X M,et al.The blind separation denoising method for surface array micro-seismic data[J].Geophysical and Geochemical Exploration,2017,41(3):521-526
[20]刘昕,陈祖斌,王东鹤,等.基于非下采样shearlet变换的微地震随机噪声压制[J].煤炭技术,2016,35(1):128-129LIU X,CHEN Z B,WANG D H,et al.Microseismic random noise attenuation based on non-subsampled shearlet transform[J].Coal Technology,2016,35(1):128-129
[21]胡永泉,尹成,潘树林,等.基于单道奇异值分解的微地震资料去噪方法[J].石油天然气学报,2013,35(4):64-69HU Y Q,YIN C,PAN S L,et al.The denoising method based on single-channel SVD for microseismic data[J].Journal of Oil and Gas Technology,2013,35(4):64-69
[22]邵婕,孙成禹,唐杰,等.基于字典训练的小波域稀疏表示微地震去噪方法[J].石油地球物理勘探,2016,51(2):254-260SHAO J,SUN C Y,TANG J,et al.The wavelet domain sparse representation microseismic denoising method based on dictionary training[J].Oil Geophysical Prospeccting,2016,51(2):254-260
[23]黄艳林.SVD与EMD联合去噪方法在地震勘探数据处理中的研究与应用[J].地震工程学报,2016,38(2):323-326HUANG Y L.Application of joint denoising using empirical mode decomposition and singular value decomposition in seismic data processing[J].China Earthquake Engineering Journal,2016,38(2):323-326
[24]詹毅,赵波.自动追踪SVD压制线性干扰方法的改进[J].石油地球物理勘探,2008,43(2):158-160ZHAN Y,ZHAO B.Improvement of suppressing linear interference by automatically tracing SVD[J].Oil Geophysical Prospecting,2008,43(2):158-160
[25]詹毅,周熙襄.小波包分析与奇异值分解(SVD)叠前去噪方法[J].石油地球物理勘探,2004,39(4):394-397ZHAN Y,ZHOU X X.Analysis of wavelet package and prestack noise-suppressed method in singular value decomposition(SVD)[J].Oil Geophysical Prospecting,2004,39(4):394-397
© 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 |