基于小波变换的航空γ能谱异常信息线单元校正方法
|
摘要
针对航空γ能谱测量工作时矿致异常信息在时域批次性干扰下难以有效提取的问题,结合小波变换理论与测线标准差变异系数理论,提出一种新的线单元校正方法。该方法利用小波变换擅长处理非稳态采样数据信号的特性,采用小波变换对线单元数据进行多尺度分解,通过软阈值滤除近似信号,有效去除含有时域批次性干扰的非地质背景信息,并对表征异常的细节信息进行重构,实现对时域批次性干扰的线单元校正。通过对实测数据的校正处理验证,结合航空伽马能谱地面异常查证结果及矿区地质简图,表明该方法削弱时域批次性效果明显,缩小了异常范围,提高了矿致异常点识别准确性,且异常形态与地面查证结果一致,客观还原测区的放射性核素分布情况。
[Background] Due to different measuring time, the measured data may fluctuate abnormally. Therefore, it is not easy to extract anomalous information caused by ores effectively in airborne gamma spectrometry. [Purpose] The aim was to reduce the impact caused by different measurement time, low background field, highlight anomalies, and help in guiding for metallogenic prognosis. [Methods] Since the wavelet transform is good at dealing with unsteady sampled data signals, this method used wavelet transform to perform multi-scale decomposition on the data of each measurement line unit. According to the coefficient of variation, the wavelet basis function was selected to transform the measured data, and the approximate signal was filtered by soft threshold to reconstruct the detail signal. [Results] After the approximate signals were filtered by soft thresholds, the non-geological background information containing data influenced by different measurement time can be effectively removed, and the detail information can be reconstructed to reduce the impact caused by different measurement time. [Conclusion] Through verifying the corrected measured data, combined with the ground anomaly inspection result of airborne gamma spectrum and the geological map of the mining area, the result shows that this method can significantly weaken the error caused by time domain batches, narrow the anomaly ranges, and improve the recognition accuracy of ore-causing anomaly points. Moreover, the shape of anomalies is consistent with the ground anomaly inspection result and the distribution of radionuclides can be restored in the survey area.
[Background] Due to different measuring time, the measured data may fluctuate abnormally. Therefore, it is not easy to extract anomalous information caused by ores effectively in airborne gamma spectrometry. [Purpose] The aim was to reduce the impact caused by different measurement time, low background field, highlight anomalies, and help in guiding for metallogenic prognosis. [Methods] Since the wavelet transform is good at dealing with unsteady sampled data signals, this method used wavelet transform to perform multi-scale decomposition on the data of each measurement line unit. According to the coefficient of variation, the wavelet basis function was selected to transform the measured data, and the approximate signal was filtered by soft threshold to reconstruct the detail signal. [Results] After the approximate signals were filtered by soft thresholds, the non-geological background information containing data influenced by different measurement time can be effectively removed, and the detail information can be reconstructed to reduce the impact caused by different measurement time. [Conclusion] Through verifying the corrected measured data, combined with the ground anomaly inspection result of airborne gamma spectrum and the geological map of the mining area, the result shows that this method can significantly weaken the error caused by time domain batches, narrow the anomaly ranges, and improve the recognition accuracy of ore-causing anomaly points. Moreover, the shape of anomalies is consistent with the ground anomaly inspection result and the distribution of radionuclides can be restored in the survey area.
引文
1万建华,熊盛青,范正国.航空伽马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.
2刘裕华,顾仁康,候振荣.航空放射性测量[J].物探与化探,2002,26(4):250-252.LIU Yuhua,GU Renkang,HOU Zhenrong.Airborne radiometrics survey[J].Geophysical and Geochemical Exploration,2002,26(4):250-252.
3葛良全,熊盛青,曾国强,等.航空伽马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.
4熊超.航空伽马能谱异常信息提取方法研究[D].成都:成都理工大学,2016.XIONG Chao.The research on anomaly information extraction method of airborne gamma-ray spectrum survey[D].Chengdu:Chengdu University of Technology,2016.
5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.
6吴和喜,葛良全,罗耀耀,等.基于最小二乘法的航空伽马能谱解析[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.
7吴和喜,葛良全,魏强林,等.航空伽马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.
8 Courbin F,Magain P,Kirkove M,et al.A method for spatial deconvolution of spectra[J].OALib Journal,1999,529(2):1136-1144.DOI:10.1086/308291.
9 Billings S D,Minty B R,Newsam G N,et al.Deconvolution and spatial resolution of airborne gamma-ray surveys[J].Geophysics,2003,68(4):1257-1266.DOI:10.1190/1.1598118.
10 Eugene D.Processing of airborne gamma-ray spectrometry using inversions[C].25th International Geophysical Conference and Exhibition,2016:1033?1040.
11 Brian M,Ross B.The 3D inversion of airborne gamma-ray spectrometric data[C].Exploration Geophysics,2016,47(2):150?157.
12米耀辉,范正国,周锡华,等.航空伽马能谱测量地形影响改正实现方法[J].物探与化探,2013,37(6):1034-1038.DOI:10.11720/j.issn.1000-8918.2013.6.15.MI Yaohui,FAN Zhengguo,ZHOU Xihua,et al.The terrain correction method for airborne gamma-ray spectrometry survey[J].Geophysical and Geochemical Exploration,2013,37(6):1034-1038.DOI:10.11720/j.issn.1000-8918.2013.6.15.
13孙海仁,李毅,曾晶荣,等.大气氡变化对航空伽马能谱测量的影响[J].物探与化探,2017,41(2):283-290.DOI:10.11720/wtyht.2017.2.14.SUN Hairen,LI Yi,ZENG Jingrong,et al.The influence of the radon on the airborne gamma-ray spectrometry survey[J].Geophysical and Geochemical Exploration,2017,41(2):283-290.DOI:10.11720/wtyht.2017.2.14.
14葛良全,谷懿,张庆贤,等.航空伽马能谱测量谱线比法大气氡校正的理论研究[J].核技术,2010,33(11):844-848.GE Liangquan,GU Yi,ZHANG Qingxian,et al.Radon background correlation using spectral-ratio method in natural gamma-ray spectrometry[J].Nuclear Techniques,2010,33(11):844-848.
15谷懿,葛良全,熊盛青,等.基于康普顿散射本底扣除的航空伽马能谱测量谱线比大气氡校正方法[J].原子能科学技术,2014,48(1):147-151.DOI:10.7538/yzk.2014.48.01.0147.GU Yi,GE Liangquan,XIONG Shengqing,et al.Spectral-ratio radon background correction method in airborne gamma-ray spectrometry based on Compton scattering deduction[J].Atomic Energy Science and Technology,2014,48(1):147-151.DOI:10.7538/yzk.2014.48.01.0147.
16 Ingrid Daubechies.小波十讲[M].北京:国防工业出版社,2011.Ingrid Daubechies.Ten lectures on wavelets[M].Beijing:National Defend Industry Press,2011.
17孙中任.变异系数用于标本磁参数统计工作的研究[J].地质与勘探,2009,45(1):65-69.SUN Zhongren.Study on usage of coefficient of variation for statistics of magnetic parameters of samples[J].Geology and Prospecting,2009,45(1):65-69.
18张文斌,熊盛青.一种有用的解释参数--航空伽玛能谱变异系数[J].物探与化探,1990,14(4):276-284.ZHANG Wenbin,XIONG Shengqing.Airborne gamma-ray spectrometric variation coefficient-a useful parameter for interpretation[J].Geophysical and Geochemical Exploration,1990,14(4):276-284.
19 Cressie N.Statistics for spatial data[J].Terra Nova,1992,35(3):321-323.
2刘裕华,顾仁康,候振荣.航空放射性测量[J].物探与化探,2002,26(4):250-252.LIU Yuhua,GU Renkang,HOU Zhenrong.Airborne radiometrics survey[J].Geophysical and Geochemical Exploration,2002,26(4):250-252.
3葛良全,熊盛青,曾国强,等.航空伽马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.
4熊超.航空伽马能谱异常信息提取方法研究[D].成都:成都理工大学,2016.XIONG Chao.The research on anomaly information extraction method of airborne gamma-ray spectrum survey[D].Chengdu:Chengdu University of Technology,2016.
5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.
6吴和喜,葛良全,罗耀耀,等.基于最小二乘法的航空伽马能谱解析[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.
7吴和喜,葛良全,魏强林,等.航空伽马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.
8 Courbin F,Magain P,Kirkove M,et al.A method for spatial deconvolution of spectra[J].OALib Journal,1999,529(2):1136-1144.DOI:10.1086/308291.
9 Billings S D,Minty B R,Newsam G N,et al.Deconvolution and spatial resolution of airborne gamma-ray surveys[J].Geophysics,2003,68(4):1257-1266.DOI:10.1190/1.1598118.
10 Eugene D.Processing of airborne gamma-ray spectrometry using inversions[C].25th International Geophysical Conference and Exhibition,2016:1033?1040.
11 Brian M,Ross B.The 3D inversion of airborne gamma-ray spectrometric data[C].Exploration Geophysics,2016,47(2):150?157.
12米耀辉,范正国,周锡华,等.航空伽马能谱测量地形影响改正实现方法[J].物探与化探,2013,37(6):1034-1038.DOI:10.11720/j.issn.1000-8918.2013.6.15.MI Yaohui,FAN Zhengguo,ZHOU Xihua,et al.The terrain correction method for airborne gamma-ray spectrometry survey[J].Geophysical and Geochemical Exploration,2013,37(6):1034-1038.DOI:10.11720/j.issn.1000-8918.2013.6.15.
13孙海仁,李毅,曾晶荣,等.大气氡变化对航空伽马能谱测量的影响[J].物探与化探,2017,41(2):283-290.DOI:10.11720/wtyht.2017.2.14.SUN Hairen,LI Yi,ZENG Jingrong,et al.The influence of the radon on the airborne gamma-ray spectrometry survey[J].Geophysical and Geochemical Exploration,2017,41(2):283-290.DOI:10.11720/wtyht.2017.2.14.
14葛良全,谷懿,张庆贤,等.航空伽马能谱测量谱线比法大气氡校正的理论研究[J].核技术,2010,33(11):844-848.GE Liangquan,GU Yi,ZHANG Qingxian,et al.Radon background correlation using spectral-ratio method in natural gamma-ray spectrometry[J].Nuclear Techniques,2010,33(11):844-848.
15谷懿,葛良全,熊盛青,等.基于康普顿散射本底扣除的航空伽马能谱测量谱线比大气氡校正方法[J].原子能科学技术,2014,48(1):147-151.DOI:10.7538/yzk.2014.48.01.0147.GU Yi,GE Liangquan,XIONG Shengqing,et al.Spectral-ratio radon background correction method in airborne gamma-ray spectrometry based on Compton scattering deduction[J].Atomic Energy Science and Technology,2014,48(1):147-151.DOI:10.7538/yzk.2014.48.01.0147.
16 Ingrid Daubechies.小波十讲[M].北京:国防工业出版社,2011.Ingrid Daubechies.Ten lectures on wavelets[M].Beijing:National Defend Industry Press,2011.
17孙中任.变异系数用于标本磁参数统计工作的研究[J].地质与勘探,2009,45(1):65-69.SUN Zhongren.Study on usage of coefficient of variation for statistics of magnetic parameters of samples[J].Geology and Prospecting,2009,45(1):65-69.
18张文斌,熊盛青.一种有用的解释参数--航空伽玛能谱变异系数[J].物探与化探,1990,14(4):276-284.ZHANG Wenbin,XIONG Shengqing.Airborne gamma-ray spectrometric variation coefficient-a useful parameter for interpretation[J].Geophysical and Geochemical Exploration,1990,14(4):276-284.
19 Cressie N.Statistics for spatial data[J].Terra Nova,1992,35(3):321-323.