| 频率域反射波全波形速度反演 |
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| 引用本文： | 成景旺,顾汉明,刘春成,刘志斌.频率域反射波全波形速度反演[J].地球科学,2013,38(2):391-397. |
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| 作者姓名： | 成景旺 顾汉明 刘春成 刘志斌 |
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| 作者单位： | 1.中国地质大学地球物理与空间信息学院，湖北武汉 430074 |
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| 摘 要： | 全波形反演不仅利用相位和振幅信息，还利用波形的细节变化，具有刻画模型精确细节的能力.在对稀疏矩阵直接LU分解求解的基础上，采用梯度预处理方法对声波介质速度模型进行了反射波全波形反演.采用误差反向传播算法计算目标函数梯度以及伪Hessian矩阵的对角线元素来做梯度预处理.数值模型的实验结果表明，利用有效的频率段便能反演出分辨率较高的速度结构，用低频反演出的结果作为高频反演的初始模型，减少了解的非唯一性.二维高斯光滑初始模型提供了有利的低频信息，得到较好的反演结果.伪Hessian矩阵的预处理吸收了高斯牛顿法的二次收敛优势，在不增加计算量的前提下，加快收敛速度.
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| 关 键 词： | 全波形反演 梯度预处理 误差反向传播算法 伪Hessian矩阵 |
| 收稿时间： | 2012-04-15 |
Full Waveform Inversion for Velocity Structure from Reflected Wave Seismic Data in the Frequency Domain |
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| CHENG Jing-wang,GU Han-ming,LIU Chun-cheng,LIU Zhi-bin.Full Waveform Inversion for Velocity Structure from Reflected Wave Seismic Data in the Frequency Domain[J].Earth Science-Journal of China University of Geosciences,2013,38(2):391-397. |
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| Authors: | CHENG Jing-wang GU Han-ming LIU Chun-cheng LIU Zhi-bin |
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| Affiliation: | 1.Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China 2.Key Laboratory of Tectonics and Petroleum Resources of Ministry of Education, China University of Geosciences, Wuhan 430074, China 3.CNOOC Research Center, Beijing 100027, China |
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| Abstract: | Full waveform inversion uses not only phase and amplitude information, but also waveform details, revealing precise details of the model. We use the LU factorization technique directly to solve the forward modeling, and show a preconditioned gradient method to inverse the velocity structure using the reflected wave from low-frequency to high-frequency in this study. The numerical structure of the finite difference method and back-propagation algorithm is exploited to develop an algorithm that explicitly calculates the Jacobin matrix utilizing a forward model solution. Furthermore, the diagonal elements of the false Hessian matrix are used as the preconditioned operator. Numerical tests on simple synthetic models find that a good velocity model can be obtained only by several frequency inversions, and the strategy of using low-frequency inversion result as the starting model in the high-frequency inversion can greatly reduce the non-uniqueness of their solutions. The initial model directly affects the imaging result. The smooth two-dimensional Gaussian model provides favorable low-frequency information for a better inversion result. The fast convergence can be achieved by using of the false Hessian matrix without any increase in the premise of computation. |
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