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时频域振幅相位联合的最小二乘逆时偏移
引用本文:胡勇,潘冬明,吴如山,韩立国,段超然.时频域振幅相位联合的最小二乘逆时偏移[J].地球物理学报,2021,64(1):209-223.
作者姓名:胡勇  潘冬明  吴如山  韩立国  段超然
作者单位:中国矿业大学,资源与地球科学学院,徐州221008;中国矿业大学,资源与地球科学学院,徐州221008;Modeling and Imaging Laboratory,University of California,Santa Cruz 95060,USA;吉林大学,地球探测科学与技术学院,长春130026;常州工学院,土木建筑工程学院,常州213000
基金项目:中央高校基本科研业务费专项资金(2020QN32)资助.
摘    要:最小二乘逆时偏移方法具有复杂地质构造成像精度高、成像振幅准确等优点.但是,当地下存在强散射介质时,最小二乘逆时偏移方法很难透过上覆强散射地质体获得深部构造的高精度成像结果.本文为了提高深部精细构造的成像质量,提出时频域振幅相位联合的最小二乘逆时偏移方法.该方法主要通过构建时频域振幅相位联合目标函数,减弱振幅信息对成像结果的影响,提高深部弱散射地震信号的可成像精度.首先,对地震信号进行时频变换,构建时频域最小二乘偏移目标函数;其次,在目标函数中引入振幅权重因子,调节时频域振幅相位权重;最后,推导时频域振幅相位联合目标函数对模型参数的梯度,并利用L-BFGS局部优化算法对成像结果进行迭代.Marmousi模型和盐丘模型测试结果表明,本文方法能够很好地利用弱散射地震信号的时频域振幅相位信息,实现透过上覆强散射地质体进行深部高精度成像的目标.

关 键 词:最小二乘逆时偏移  振幅相位  目标函数  时频域
收稿时间:2020-06-01

Joint least square reverse time migration of phase and amplitude in the time-frequency domain
HU Yong,PAN DongMing,WU RuShan,HAN LiGuo,DUAN ChaoRan.Joint least square reverse time migration of phase and amplitude in the time-frequency domain[J].Chinese Journal of Geophysics,2021,64(1):209-223.
Authors:HU Yong  PAN DongMing  WU RuShan  HAN LiGuo  DUAN ChaoRan
Institution:1. School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221008, China;2. Modeling and Imaging Laboratory, University of California, Santa Cruz 95060, USA;3. College of Geo-Exploration science and Technology, Jilin University, Changchun 130026, China;4. School of Civil Engineering and Architecture, Changzhou Institude of Technology, Changzhou 213000, China
Abstract:Least Square Reverse Time Migration (LSRTM) has the advantages of high-resolution imaging and accurate amplitude in complex geological structures. However, if subsurface exist strong-scattering bodies, this method is difficult to penetrate these overlying media to obtain high-resolution imaging results. To improve the imaging quality of deep structures, a joint LSRTM of Phase and Amplitude Method (PA-LSRTM) in the time-frequency domain is proposed in this paper. It establishes a time-frequency phase and amplitude misfit to weaken the effect of amplitude components on the imaging results, thus the imaging resolution of deep weak scattering seismic signal can be improved. Firstly, the shot recorded seismic data are transformed into that in the time-frequency domain to establish a PA-LSRTM misfit. Then, an amplitude factor is introduced in the PA-LSRTM misfit to adjust the weight of time-frequency phase and amplitude. Finally, it takes derivative with respect to the model parameter, and uses the L-BFGS optimization algorithm to update the imaging result. The numerical tests on Marmousi and salt models demonstrate that the PA-LSRTM can take good use of the time-frequency domain phase and amplitude information to penetrate overlying strong scattering bodies and improve the imaging results of sub-bottom and sub-salt structures.
Keywords:Least Square Reverse Time Migration (LSRTM)  Phase and amplitude  Misfit function  Time-frequency domain  
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