基于分形逐层滤波的航空γ能谱矿致异常信息识别方法
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摘要
矿致异常信息识别方法研究是航空γ能谱测量数据后处理的核心技术之一,针对目前航空γ能谱测量中矿致异常信息识别方法普遍基于统计分析,而频率尺度解析尚未大范围应用这一问题,提出一种频率域分形逐层滤波法异常识别方法,此方法以多重分形理论为基础,在频率域下对航空γ能谱实测核素比活度数据进行功率谱分析,并通过多重分形理论定量计算功率谱的截止频率,并依据计算结果对原始数据进行逐层滤波,确定识别矿致异常信息的最佳频段。采用内蒙某测区1:50 000航空γ能谱试生产飞行数据(测区包含已探明金属矿点)对该方法进行验证。结果表明:利用分形逐层滤波法对原始信号的功率谱数据进行逐层滤波,矿致异常信息在各个分形频段内均有信号响应,但飞行误差引起的假异常信号只存在于中、低频段内,采用中高频段带通滤波将其分离和剔除,在f2～f3频率区间(0.308 01～0.406 15 Hz)可有效分离背景噪声和识别已知矿点的矿致异常,且能剔除飞行时域批次性导致的条带状假异常。
[Background] Identification method on ore-caused anomalies information is one of the core technologies of airborne γ-ray spectrum data post-processing. However, the current ore-caused anomalies information identification methods in airborne γ-ray spectrum are generally based on statistical analysis while the frequency scales are ignored. [Purpose] This study aims to propose an anomaly identification method on the frequency scale to discover the structural features of complex systems and identify anomalies. [Methods] Based on multi-fractal theory,the power spectrum of the nuclides specific activity data of the airborne γ-ray spectrum under frequency domain was analyzed. The cut-off frequency of the power spectrum by the multi-fractal theory was quantitatively calculated. The1:50 000 airborne γ-ray spectrum trial production flight data of a certain area in Inner Mongolia(the surveying area contains proved metal ore occurrences) to verify the method, and the original data was filtered by layers to determine and identify the optimal frequency band of the ore-caused anomalies information. [[Results] Through filtering the power spectrum data of original signals in the method of fractal filtering by layers, the signals of the ore-caused anomalies information were found in each fractal frequency band. The results show that background noises in the frequency band of f2～f3(ie 0.308 01～0.406 15 Hz) can be effectively separated, and ore-caused anomalies of known ore occurrences can be identified and band-like false anomalies caused by time domain batches can be removed.[[Conclusion] Due to the false anomaly signals caused by time domain batches only exists in the middle and low frequency bands, the band-pass filtering of medium-high frequency band in fractal filtering by layers proposed in this paper can be used to separate and remove them.
[Background] Identification method on ore-caused anomalies information is one of the core technologies of airborne γ-ray spectrum data post-processing. However, the current ore-caused anomalies information identification methods in airborne γ-ray spectrum are generally based on statistical analysis while the frequency scales are ignored. [Purpose] This study aims to propose an anomaly identification method on the frequency scale to discover the structural features of complex systems and identify anomalies. [Methods] Based on multi-fractal theory,the power spectrum of the nuclides specific activity data of the airborne γ-ray spectrum under frequency domain was analyzed. The cut-off frequency of the power spectrum by the multi-fractal theory was quantitatively calculated. The1:50 000 airborne γ-ray spectrum trial production flight data of a certain area in Inner Mongolia(the surveying area contains proved metal ore occurrences) to verify the method, and the original data was filtered by layers to determine and identify the optimal frequency band of the ore-caused anomalies information. [[Results] Through filtering the power spectrum data of original signals in the method of fractal filtering by layers, the signals of the ore-caused anomalies information were found in each fractal frequency band. The results show that background noises in the frequency band of f2～f3(ie 0.308 01～0.406 15 Hz) can be effectively separated, and ore-caused anomalies of known ore occurrences can be identified and band-like false anomalies caused by time domain batches can be removed.[[Conclusion] Due to the false anomaly signals caused by time domain batches only exists in the middle and low frequency bands, the band-pass filtering of medium-high frequency band in fractal filtering by layers proposed in this paper can be used to separate and remove them.
引文
1万建华,熊盛青,范正国.航空γ能谱测量方法技术现状与展望[J].物探与化探,2012,36(3):386-391.WAN Jianhua,XIONG Shengqing,FAN Zhengguo.The status and prospects of airborne gamma-ray spectrometry technology and its application[J].Geophysical and Geochemical Exploration,2012,36(3):386-391.
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3张庆贤,葛良全,谷懿,等.基于极大似然估计的NaI(Tl)晶体仪器谱解析方法研究[J].核技术,2011,34(8):569-574.ZHANG Qingxian,GE Liangquan,GU Yi,et al.The unfolding of NaI(Tl)γ-ray spectrum based on maximum likelihood method[J].Nuclear Techniques,2011,34(8):569-574.
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5吴和喜,葛良全,魏强林,等.航空γ能谱仪无源效率刻度方法研究[J].核技术,2016,39(12):120202.DOI:10.11889/j.0253-3219.2016.hjs.39.120202.WU Hexi,GE Liangquan,WEI Qianglin,et al.Methodology study on the sourceless efficiency calibration of airborne gamma-ray spectrometry[J].Nuclear Techniques,2016,39(12):120202.DOI:10.11889/j.0253-3219.2016.hjs.39.120202.
6 Zuo R,Cheng Q,Agterberg F P,et al.Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data,a case study from Gangdese,Tibet,western China[J].Journal of Geochemical Exploration,2009,101(3):225-235.
7谢淑云,鲍征宇.地球化学场的连续多重分形模式[J].地球化学,2002,31(2):191-200.XIE Shuyun,BAO Zhengyu.Continuous multifractal model of geochemical fields[J].Geochimica,2002,31(2):191-200.
8李庆谋,刘少华.GIS环境下地球物理信号的奇异值分解、多维分形特征与应用[J].地球物理学进展,2003,18(1):97-102.LI Qingmou,LIU Shaohua.Geophysical signal decomposition by singular method and application in GIS[J].Progress in Geophysics,2003,18(1):97-102.
9李庆谋,成秋明.分形奇异(特征)值分解方法与地球物理和地球化学异常重建[J].地球科学,2004,29(1):109-118.LI Qingmou,CHENG Qiuming.Fractal singular-value(egin-value)decomposition method for geophysical and geochemical anomaly reconstruction[J].Earth Science,2004,29(1):109-118.
10成秋明.多重分形与地质统计学方法用于勘查地球化学异常空间结构和奇异性分析[J].地球科学-中国地质大学学报,2001,26(2):55-60.CHENG Qiuming.Multifractal and geostatistic methodsfor characterizing local structure and singularity properties of exploration geochemical anomalies[J].Earth Science-Journal of China University of Geosciences,2001,26(2):55-60.
11 Wang W L,Cheng Q M,Tang J X,et al.Fractal/multifractal analysis in support of mineral exploration in the Duolong mineral district,Tibet,China[J].Geochemistry Exploration Environment Analysis,2017,17(3):261-276.DOI:10.1144/geochem2016-449.
12李庆谋,刘少华.分形噪声、多维分形滤波及地球物理测井曲线处理应用[J].地球物理学进展,2000,15(4):110-116.LI Qingmou,LIU Shaohua.Fractal noise,multifractal filtering and application for well logging data[J].Progress in Geophysics,2000,15(4):110-116.
13成秋明.多维分形理论和地球化学元素分布规律[J].地球科学-中国地质大学学报,2000,25(3):311-318.CHENG Qiuming.Multifractal theory and geochemical element distribution pattern[J].Earth Science-Journal of China University of Geosciences,2000,25(3):311-318.
14谢淑云,鲍征宇.多重分形与地球化学元素的分布规律[J].地球与环境,2003,31(3):97-102.XIE Shuyun,BAO Zhengyu.Multifractal and geochemical element distribution patterns[J].GeologyGeochemistry,2003,31(3):97-102.
15谢淑云,何治亮,钱一雄,等.基于岩石CT图像的碳酸盐岩三维孔隙组构的多重分形特征研究[J].地质学刊,2015,39(1):46-54.XIE Shuyun,HE Zhiliang,QIAN Yixiong,et al.Multifractality of 3D pore structures of carbonate rocks based on CT images[J].Journal of Geology,2015,39(1):46-54.
16谢淑云,成秋明,李增华,等.矿物微观结构的多重分形[J].地球科学-中国地质大学学报,2009,34(2):263-269.XIE Shuyun,CHENG Qiuming,LI Zenghua,et al.Assessing microstructures of ore-minerals by multifractal[J].Earth Science-Journal of China University of Geosciences,2009,34(2):263-269.
17申维.成矿预测中的分形模型分维数估计的新方法[J].吉林大学学报(地),1997,(1):86-91.SHEN Wei.A new method of estimating fractal dimension in fractal model of minerogenetic prediction[J].Journal of Jilin University(Science Edition),1997,(1):86-91.
18张磊,申维.分形方法在澳大利亚新南威尔士地区地球化学异常下限确定中的应用[J].地质通报,2009,28(2):245-249.ZHANG Lei,SHEN Wei.Application of fractal method in lower threshold definition of geochemistry anomaly in New South Wales Area,Australia[J].Geological Bulletin of China,2009,28(2):245-249.
19 Afzal P,Adib A,Ebadati N.Delineation of seismic zonation using fractal modeling in West Yazd province,Central Iran[J].Journal of Seismology,2018,(22):1377-1393.DOI:10.1007/s10950-018-9770-9.
20於崇文.大型矿床和成矿区(带)在混沌边缘[J].地学前缘,1999,(2):85-102.YU Chongwen.Large ore deposits and metallogenic disteicts at the edge of chaos[J].Earth Science Frontiers,1999,(2):85-102.
21曹梦雪.地质空间数字频谱模型研究及应用[D].吉林:吉林大学,2017.CAO Mengxue.Research and application on geospatial digital spectrum model[D].Jilin:Jilin University,2017.
22李庆忠,魏继东.高密度地震采集中组合效应对高频截止频率的影响[J].石油地球物理勘探,2007,42(4):363-369.LI Qingzhong,WEI Jidong.Influence of array effect on cutoff frequency of high frequency in high-density seismic acquisition[J].Oil Geophysical Prospecting,2007,42(4):363-369.
23曾晟,谭凯旋,雷林,等.某地浸铀矿床低渗透性砂岩孔隙结构特征研究[J].核技术,2013,36(1):37-42.ZENG Sheng,TAN Kaixuan,LEI Lin,et al.Study on the structure characteristic of the low permeable sandstone uranium ore rock[J].Nuclear Techniques,2013,36(1):37-42.
24熊超,葛良全,王卓,等.基于FFT分形滤波的地球化学异常信息提取[J].地质与勘探,2013,49(1):162-166.XIONG Chao,GE Liangquan,WANG Zhuo,et al.Extraction of geochemical anomaly information based on fractal filtering with fast fourier transform[J].Geology and Exploration,2013,49(1):162-166.
2葛良全,熊盛青,曾国强,等.航空γ能谱探测技术与应用[M].北京:科学出版社,2016.GE Liangquan,XIONG Shengqing,ZENG Guoqiang,et al.Airborne gamma-ray spectrum detection and application[M].Beijing:Science Press,2016.
3张庆贤,葛良全,谷懿,等.基于极大似然估计的NaI(Tl)晶体仪器谱解析方法研究[J].核技术,2011,34(8):569-574.ZHANG Qingxian,GE Liangquan,GU Yi,et al.The unfolding of NaI(Tl)γ-ray spectrum based on maximum likelihood method[J].Nuclear Techniques,2011,34(8):569-574.
4吴和喜,葛良全,罗耀耀,等.基于最小二乘法的航空γ能谱解析[J].核技术,2016,39(11):110201.DOI:10.11889/j.0253-3219.2016.hjs.39.110201.WU Hexi,GE Liangquan,LUO Yaoyao,et al.Analyzing airborne gamma-ray spectrum by the least square method[J].Nuclear Techniques,2016,39(11):110201.DOI:10.11889/j.0253-3219.2016.hjs.39.110201.
5吴和喜,葛良全,魏强林,等.航空γ能谱仪无源效率刻度方法研究[J].核技术,2016,39(12):120202.DOI:10.11889/j.0253-3219.2016.hjs.39.120202.WU Hexi,GE Liangquan,WEI Qianglin,et al.Methodology study on the sourceless efficiency calibration of airborne gamma-ray spectrometry[J].Nuclear Techniques,2016,39(12):120202.DOI:10.11889/j.0253-3219.2016.hjs.39.120202.
6 Zuo R,Cheng Q,Agterberg F P,et al.Application of singularity mapping technique to identify local anomalies using stream sediment geochemical data,a case study from Gangdese,Tibet,western China[J].Journal of Geochemical Exploration,2009,101(3):225-235.
7谢淑云,鲍征宇.地球化学场的连续多重分形模式[J].地球化学,2002,31(2):191-200.XIE Shuyun,BAO Zhengyu.Continuous multifractal model of geochemical fields[J].Geochimica,2002,31(2):191-200.
8李庆谋,刘少华.GIS环境下地球物理信号的奇异值分解、多维分形特征与应用[J].地球物理学进展,2003,18(1):97-102.LI Qingmou,LIU Shaohua.Geophysical signal decomposition by singular method and application in GIS[J].Progress in Geophysics,2003,18(1):97-102.
9李庆谋,成秋明.分形奇异(特征)值分解方法与地球物理和地球化学异常重建[J].地球科学,2004,29(1):109-118.LI Qingmou,CHENG Qiuming.Fractal singular-value(egin-value)decomposition method for geophysical and geochemical anomaly reconstruction[J].Earth Science,2004,29(1):109-118.
10成秋明.多重分形与地质统计学方法用于勘查地球化学异常空间结构和奇异性分析[J].地球科学-中国地质大学学报,2001,26(2):55-60.CHENG Qiuming.Multifractal and geostatistic methodsfor characterizing local structure and singularity properties of exploration geochemical anomalies[J].Earth Science-Journal of China University of Geosciences,2001,26(2):55-60.
11 Wang W L,Cheng Q M,Tang J X,et al.Fractal/multifractal analysis in support of mineral exploration in the Duolong mineral district,Tibet,China[J].Geochemistry Exploration Environment Analysis,2017,17(3):261-276.DOI:10.1144/geochem2016-449.
12李庆谋,刘少华.分形噪声、多维分形滤波及地球物理测井曲线处理应用[J].地球物理学进展,2000,15(4):110-116.LI Qingmou,LIU Shaohua.Fractal noise,multifractal filtering and application for well logging data[J].Progress in Geophysics,2000,15(4):110-116.
13成秋明.多维分形理论和地球化学元素分布规律[J].地球科学-中国地质大学学报,2000,25(3):311-318.CHENG Qiuming.Multifractal theory and geochemical element distribution pattern[J].Earth Science-Journal of China University of Geosciences,2000,25(3):311-318.
14谢淑云,鲍征宇.多重分形与地球化学元素的分布规律[J].地球与环境,2003,31(3):97-102.XIE Shuyun,BAO Zhengyu.Multifractal and geochemical element distribution patterns[J].GeologyGeochemistry,2003,31(3):97-102.
15谢淑云,何治亮,钱一雄,等.基于岩石CT图像的碳酸盐岩三维孔隙组构的多重分形特征研究[J].地质学刊,2015,39(1):46-54.XIE Shuyun,HE Zhiliang,QIAN Yixiong,et al.Multifractality of 3D pore structures of carbonate rocks based on CT images[J].Journal of Geology,2015,39(1):46-54.
16谢淑云,成秋明,李增华,等.矿物微观结构的多重分形[J].地球科学-中国地质大学学报,2009,34(2):263-269.XIE Shuyun,CHENG Qiuming,LI Zenghua,et al.Assessing microstructures of ore-minerals by multifractal[J].Earth Science-Journal of China University of Geosciences,2009,34(2):263-269.
17申维.成矿预测中的分形模型分维数估计的新方法[J].吉林大学学报(地),1997,(1):86-91.SHEN Wei.A new method of estimating fractal dimension in fractal model of minerogenetic prediction[J].Journal of Jilin University(Science Edition),1997,(1):86-91.
18张磊,申维.分形方法在澳大利亚新南威尔士地区地球化学异常下限确定中的应用[J].地质通报,2009,28(2):245-249.ZHANG Lei,SHEN Wei.Application of fractal method in lower threshold definition of geochemistry anomaly in New South Wales Area,Australia[J].Geological Bulletin of China,2009,28(2):245-249.
19 Afzal P,Adib A,Ebadati N.Delineation of seismic zonation using fractal modeling in West Yazd province,Central Iran[J].Journal of Seismology,2018,(22):1377-1393.DOI:10.1007/s10950-018-9770-9.
20於崇文.大型矿床和成矿区(带)在混沌边缘[J].地学前缘,1999,(2):85-102.YU Chongwen.Large ore deposits and metallogenic disteicts at the edge of chaos[J].Earth Science Frontiers,1999,(2):85-102.
21曹梦雪.地质空间数字频谱模型研究及应用[D].吉林:吉林大学,2017.CAO Mengxue.Research and application on geospatial digital spectrum model[D].Jilin:Jilin University,2017.
22李庆忠,魏继东.高密度地震采集中组合效应对高频截止频率的影响[J].石油地球物理勘探,2007,42(4):363-369.LI Qingzhong,WEI Jidong.Influence of array effect on cutoff frequency of high frequency in high-density seismic acquisition[J].Oil Geophysical Prospecting,2007,42(4):363-369.
23曾晟,谭凯旋,雷林,等.某地浸铀矿床低渗透性砂岩孔隙结构特征研究[J].核技术,2013,36(1):37-42.ZENG Sheng,TAN Kaixuan,LEI Lin,et al.Study on the structure characteristic of the low permeable sandstone uranium ore rock[J].Nuclear Techniques,2013,36(1):37-42.
24熊超,葛良全,王卓,等.基于FFT分形滤波的地球化学异常信息提取[J].地质与勘探,2013,49(1):162-166.XIONG Chao,GE Liangquan,WANG Zhuo,et al.Extraction of geochemical anomaly information based on fractal filtering with fast fourier transform[J].Geology and Exploration,2013,49(1):162-166.
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