基于Chirp源浅地层剖面资料计算海底反射损失
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摘要
本文详细描述了基于Chirp源浅地层剖面资料计算海底反射损失的方法.首先,在没有震源标定实验的条件下,利用浅地层剖面系统的声源级及Chirp脉冲的相关参数来模拟震源信号,并以相应的振幅值来表示声压强度.然后,结合浅地层剖面中拾取的海底反射信号及其对应的双程走时,根据反射波和入射波的振幅信息来计算海底反射系数(损失).以中国台湾海峡西海岸某条测线为例,对该方法进行验证,并与文献中常用方法(利用海底一次波和二次波)的计算结果进行对比,结果表明后者在浅水资料中的应用存在着明显缺陷.此外,将计算的海底反射损失与该海域的底质分类结果进行比对,低反射损失与细颗粒沉积物对应,高反射损失与粗颗粒沉积物对应,与前人的相关研究结论基本一致.本文为浅水区域海底反射损失的估算提供了新的技术.
This paper details estimating seabed reflection loss on the basis of sound pressure level and normal reflection seismic data acquired with chirp sub-bottom profiler. Without the source calibration experiment, the source signature is deduced from the sound pressure level and the parameters of the transmitted Chirp pulse. Then the incident wave is deduced according to the effective sound pressure of the source and also the water depth, and the reflected wave is derived from the seismic data. Afterwards, it is able to calculate the seabed reflection coefficient in light of incident wave and reflected wave. The method has also been applied to practical data, which was acquired in the west coast of Taiwan Strait. The results are compared with those of the method commonly used in the literature, which calculates the seabed reflection coefficient according to the primary and secondary seabed reflection. However, the common method is not suitable for seismic data of shallow water. Hence, we compare the calculated reflection coefficient with the results of geological sampling and find that fine particles correspond to a lower reflection loss while coarse particles correspond to a higher reflection loss, which are consistent with the previous studies. This work would provide a direct way to estimate seabed reflectivity and contribute to mining more information from the Chirp seismic data. The results are also meaningful for the research of marine sediment acoustics and sediment classification, especially in shallow water.
This paper details estimating seabed reflection loss on the basis of sound pressure level and normal reflection seismic data acquired with chirp sub-bottom profiler. Without the source calibration experiment, the source signature is deduced from the sound pressure level and the parameters of the transmitted Chirp pulse. Then the incident wave is deduced according to the effective sound pressure of the source and also the water depth, and the reflected wave is derived from the seismic data. Afterwards, it is able to calculate the seabed reflection coefficient in light of incident wave and reflected wave. The method has also been applied to practical data, which was acquired in the west coast of Taiwan Strait. The results are compared with those of the method commonly used in the literature, which calculates the seabed reflection coefficient according to the primary and secondary seabed reflection. However, the common method is not suitable for seismic data of shallow water. Hence, we compare the calculated reflection coefficient with the results of geological sampling and find that fine particles correspond to a lower reflection loss while coarse particles correspond to a higher reflection loss, which are consistent with the previous studies. This work would provide a direct way to estimate seabed reflectivity and contribute to mining more information from the Chirp seismic data. The results are also meaningful for the research of marine sediment acoustics and sediment classification, especially in shallow water.
引文
Buckingham M J.1998.Theory of compressional and shear waves in fluidlike marine sediments [J].Journal of the Acoustical Society of America,103(1):288-299,doi:10.1121/1.421091.
Bull J M,Quinn R,Dix J K.1998.Reflection coefficient calculation from marine high resolution seismic reflection (Chirp) data and application to an archaeological case study [J].Marine Geophysical Researches,20(1):1-11,doi:10.1023/A:1004373106696.
Chen S,Yan P,Wang Y L.2016.Inversion of the physical properties of the seabed using Chirp sub-bottom data in mud volcanoes field of the south west of Dongsha Islands [J].Earth Sicence (in Chinese),41(3):425- 432,doi:10.3799/dqkx.2016.034.
Chiu L Y S,Chang A,Lin Y T,et al.2015.Estimating geoacoustic properties of surficial sediments in the North Mien-Hua canyon region with a Chirp sonar profiler[J].IEEE Journal of Oceanic Engineering,40(1):222-236,doi:10.1109/JOE.2013.2296362.
EdgeTech.2003.Technical & User’s Manual for Discover Sub-bottom.EdgeTech,West Wareham.
Jackson D R,Richardson M D.2007.High-Frequency Seafloor Acoustics [M].New York,USA,Springer Science+Business Media,LLC.
Leblanc L R,Mayer L,Rufino M,et al.1992.Marine sediment classification using the chirp sonar [J].Journal of the Acoustical Society of America,91(1):107-115,doi:10.1121/1.402758.
Li C Z,Yang Y,Wang R,et al.2017.Inversion of river-bottom sediment parameters using mechanically sampled specimens and subbottom profiling data [J].Applied Geophysics (in Chinese),14(2):225-235,doi:10.1007/s11770- 017- 0621-1.
Panda S,Leblanc L R,Schock S G.1994.Sediment classification based on impedance and attenuation estimation [J].Journal of the Acoustical Society of America,96(5):3022-3035,doi:10.1121/1.411266.
Rakotonarivo S,Legris M,Desmare R,et al.2011.Forward modeling for marine sediment characterization using chirp sonars [J].Geophysics,76(4):T91-T99,doi:10.1190/1.3590717.
Richardson M D,Young D K.1980.Geoacoustic models and bioturbation [J].Marine Geology,38(1-3):205-218,doi:10.1016/0025-3227(80)90059- 6.
Schock S G.2004a.A method for estimating the physical and acoustic properties of the sea bed using chirp sonar data [J].IEEE Journal of Oceanic Engineering,29(4):1200-1217,doi:10.1109/JOE.2004.841421.
Schock S G.2004b.Remote estimates of physical and acoustic sediment properties in the South China Sea using chirp sonar data and the biot model [J].IEEE Journal of Oceanic Engineering,29(4):1218-1230,doi:10.1109/JOE.2004.842253.
Schock S G,Leblanc L R,Mayer L A.1989.Chirp subbottom profiler for quantitative sediment analysis [J].Geophysics,54(4):445- 450,doi:10.1190/1.1442670.
SHI Jian,LIU Jun,CHEN Gang,et al.2017.Surface-related multiple suppression in the shallow water area of continental shelf[J].Progress in Geophysics (in Chinese),32(2):902-910,doi:10.6038/pg20170262.
Stevenson I R,Mccann C,Runciman P B.2002.An attenuation-based sediment classification technique using Chirp sub-bottom profiler data and laboratory acoustic analysis [J].Marine Geophysical Researches,23(4):277-298,doi:10.1023/A:1025708024518.
Theuillon G,Stephan Y,Pacault A.2008.High-resolution geoacoustic characterization of the seafloor using a subbottom profiler in the Gulf of Lion [J].IEEE Journal of Oceanic Engineering,33(3):240-254,doi:10.1109/JOE.2008.926958.
Tseng Y T,Ding J J,Liu C S.2012.Analysis of attenuation measurements in ocean sediments using normal incidence Chirp sonar [J].IEEE Journal of Oceanic Engineering,37(3):533-543,doi:10.1109/JOE.2012.2200377.
YANG Zhen,PENG Lu,ZHANG Ru-wei.2018.Method of identifying MTD and BSR through AVO theory[J].Progress in Geophysics (in Chinese),33(3):1289-1296,doi:10.6038/pg2018BB0205.
Zheng H B,Yan P,Chen J,et al.2012.Seabed sediment classification in the northern South China Sea using inversion method [J].Applied Ocean Research,39(1):131-136,doi:10.1016/j.apor.2012.11.002.
陈森,阎贫,王彦林.2016.东沙群岛西南泥火山区Chirp浅剖数据的海底物性反演[J].地球科学-中国地质大学学报,41(3):425- 432,doi:10.3799/dqkx.2016.034.
施剑,刘俊,陈刚,等.2017.陆架浅水区自由表面多次波压制方法[J].地球物理学进展,32(2):902-910,doi:10.6038/pg20170262.
杨振,彭璐,张如伟.2018.利用AVO理论识别MTD与BSR的技术方法[J].地球物理学进展,33(3):1289-1296,doi:10.6038/pg2018BB0205.
Bull J M,Quinn R,Dix J K.1998.Reflection coefficient calculation from marine high resolution seismic reflection (Chirp) data and application to an archaeological case study [J].Marine Geophysical Researches,20(1):1-11,doi:10.1023/A:1004373106696.
Chen S,Yan P,Wang Y L.2016.Inversion of the physical properties of the seabed using Chirp sub-bottom data in mud volcanoes field of the south west of Dongsha Islands [J].Earth Sicence (in Chinese),41(3):425- 432,doi:10.3799/dqkx.2016.034.
Chiu L Y S,Chang A,Lin Y T,et al.2015.Estimating geoacoustic properties of surficial sediments in the North Mien-Hua canyon region with a Chirp sonar profiler[J].IEEE Journal of Oceanic Engineering,40(1):222-236,doi:10.1109/JOE.2013.2296362.
EdgeTech.2003.Technical & User’s Manual for Discover Sub-bottom.EdgeTech,West Wareham.
Jackson D R,Richardson M D.2007.High-Frequency Seafloor Acoustics [M].New York,USA,Springer Science+Business Media,LLC.
Leblanc L R,Mayer L,Rufino M,et al.1992.Marine sediment classification using the chirp sonar [J].Journal of the Acoustical Society of America,91(1):107-115,doi:10.1121/1.402758.
Li C Z,Yang Y,Wang R,et al.2017.Inversion of river-bottom sediment parameters using mechanically sampled specimens and subbottom profiling data [J].Applied Geophysics (in Chinese),14(2):225-235,doi:10.1007/s11770- 017- 0621-1.
Panda S,Leblanc L R,Schock S G.1994.Sediment classification based on impedance and attenuation estimation [J].Journal of the Acoustical Society of America,96(5):3022-3035,doi:10.1121/1.411266.
Rakotonarivo S,Legris M,Desmare R,et al.2011.Forward modeling for marine sediment characterization using chirp sonars [J].Geophysics,76(4):T91-T99,doi:10.1190/1.3590717.
Richardson M D,Young D K.1980.Geoacoustic models and bioturbation [J].Marine Geology,38(1-3):205-218,doi:10.1016/0025-3227(80)90059- 6.
Schock S G.2004a.A method for estimating the physical and acoustic properties of the sea bed using chirp sonar data [J].IEEE Journal of Oceanic Engineering,29(4):1200-1217,doi:10.1109/JOE.2004.841421.
Schock S G.2004b.Remote estimates of physical and acoustic sediment properties in the South China Sea using chirp sonar data and the biot model [J].IEEE Journal of Oceanic Engineering,29(4):1218-1230,doi:10.1109/JOE.2004.842253.
Schock S G,Leblanc L R,Mayer L A.1989.Chirp subbottom profiler for quantitative sediment analysis [J].Geophysics,54(4):445- 450,doi:10.1190/1.1442670.
SHI Jian,LIU Jun,CHEN Gang,et al.2017.Surface-related multiple suppression in the shallow water area of continental shelf[J].Progress in Geophysics (in Chinese),32(2):902-910,doi:10.6038/pg20170262.
Stevenson I R,Mccann C,Runciman P B.2002.An attenuation-based sediment classification technique using Chirp sub-bottom profiler data and laboratory acoustic analysis [J].Marine Geophysical Researches,23(4):277-298,doi:10.1023/A:1025708024518.
Theuillon G,Stephan Y,Pacault A.2008.High-resolution geoacoustic characterization of the seafloor using a subbottom profiler in the Gulf of Lion [J].IEEE Journal of Oceanic Engineering,33(3):240-254,doi:10.1109/JOE.2008.926958.
Tseng Y T,Ding J J,Liu C S.2012.Analysis of attenuation measurements in ocean sediments using normal incidence Chirp sonar [J].IEEE Journal of Oceanic Engineering,37(3):533-543,doi:10.1109/JOE.2012.2200377.
YANG Zhen,PENG Lu,ZHANG Ru-wei.2018.Method of identifying MTD and BSR through AVO theory[J].Progress in Geophysics (in Chinese),33(3):1289-1296,doi:10.6038/pg2018BB0205.
Zheng H B,Yan P,Chen J,et al.2012.Seabed sediment classification in the northern South China Sea using inversion method [J].Applied Ocean Research,39(1):131-136,doi:10.1016/j.apor.2012.11.002.
陈森,阎贫,王彦林.2016.东沙群岛西南泥火山区Chirp浅剖数据的海底物性反演[J].地球科学-中国地质大学学报,41(3):425- 432,doi:10.3799/dqkx.2016.034.
施剑,刘俊,陈刚,等.2017.陆架浅水区自由表面多次波压制方法[J].地球物理学进展,32(2):902-910,doi:10.6038/pg20170262.
杨振,彭璐,张如伟.2018.利用AVO理论识别MTD与BSR的技术方法[J].地球物理学进展,33(3):1289-1296,doi:10.6038/pg2018BB0205.