In the adjoint-state method, the forward-propagated source wavefield and the backward-propagated receiver wavefield must be available simultaneously either for seismic imaging in migration or for gradient calculation ...In the adjoint-state method, the forward-propagated source wavefield and the backward-propagated receiver wavefield must be available simultaneously either for seismic imaging in migration or for gradient calculation in inversion. A feasible way to avoid the excessive storage demand is to reconstruct the source wavefield backward in time by storing the entire history of the wavefield in perfectly matched layers. In this paper, we make full use of the elementwise global property of the Laplace operator of the spectral element method (SEM) and propose an efficient source wavefield reconstruction method at the cost of storing the wavefield history only at single boundary layer nodes. Numerical experiments indicate that the accuracy of the proposed method is identical to that of the conventional method and is independent of the order of the Lagrange polynomials, the element type, and the temporal discretization method. In contrast, the memory-saving ratios of the conventional method versus our method is at least N when using either quadrilateral or hexahedron elements, respectively, where N is the order of the Lagrange polynomials used in the SEM. A higher memorysaving ratio is achieved with triangular elements versus quadrilaterals. The new method is applied to reverse time migration by considering the Marmousi model as a benchmark. Numerical results demonstrate that the method is able to provide the same result as the conventional method but with about 1/25 times lower storage demand. With the proposed wavefield reconstruction method, the storage demand is dramatically reduced;therefore, in-core memory storage is feasible even for large-scale three-dimensional adjoint inversion problems.展开更多
在城市中应用微动H/V谱比方法面对大量且复杂的人文噪声干扰,需要对噪声强度较大的微动数据进行去噪处理或信号分析。本文针对现有方法难以处理干扰较大的微动数据以及信号提取过程繁琐的问题,提出基于XGBoost(extreme gradient boosti...在城市中应用微动H/V谱比方法面对大量且复杂的人文噪声干扰,需要对噪声强度较大的微动数据进行去噪处理或信号分析。本文针对现有方法难以处理干扰较大的微动数据以及信号提取过程繁琐的问题,提出基于XGBoost(extreme gradient boosting)的多重加权谱比降噪方法。首先对采集的微动数据进行幅值和频率分析,建立幅值加权谱比、频率加权谱比和多重加权谱比;然后根据建立的多重加权谱比,通过XGBoost方法获得降噪后的谱比曲线。将本文方法与传统STA/LTA(short time average/long time average)方法进行实际高噪声数据对比分析,结果表明相比于STA/LTA方法,本文方法对高噪声数据提取效果更好。展开更多
基金financial support for this work contributed by the National Key Research and Development Program of China (grant numbers 2016YFC0600101 and 2016YFC 0600201)the National Natural Science Foundation of China (grant numbers 41874065, 41604076, 41674102, 41674095, 41522401, 41574082, and 41774097)
文摘In the adjoint-state method, the forward-propagated source wavefield and the backward-propagated receiver wavefield must be available simultaneously either for seismic imaging in migration or for gradient calculation in inversion. A feasible way to avoid the excessive storage demand is to reconstruct the source wavefield backward in time by storing the entire history of the wavefield in perfectly matched layers. In this paper, we make full use of the elementwise global property of the Laplace operator of the spectral element method (SEM) and propose an efficient source wavefield reconstruction method at the cost of storing the wavefield history only at single boundary layer nodes. Numerical experiments indicate that the accuracy of the proposed method is identical to that of the conventional method and is independent of the order of the Lagrange polynomials, the element type, and the temporal discretization method. In contrast, the memory-saving ratios of the conventional method versus our method is at least N when using either quadrilateral or hexahedron elements, respectively, where N is the order of the Lagrange polynomials used in the SEM. A higher memorysaving ratio is achieved with triangular elements versus quadrilaterals. The new method is applied to reverse time migration by considering the Marmousi model as a benchmark. Numerical results demonstrate that the method is able to provide the same result as the conventional method but with about 1/25 times lower storage demand. With the proposed wavefield reconstruction method, the storage demand is dramatically reduced;therefore, in-core memory storage is feasible even for large-scale three-dimensional adjoint inversion problems.
文摘在城市中应用微动H/V谱比方法面对大量且复杂的人文噪声干扰,需要对噪声强度较大的微动数据进行去噪处理或信号分析。本文针对现有方法难以处理干扰较大的微动数据以及信号提取过程繁琐的问题,提出基于XGBoost(extreme gradient boosting)的多重加权谱比降噪方法。首先对采集的微动数据进行幅值和频率分析,建立幅值加权谱比、频率加权谱比和多重加权谱比;然后根据建立的多重加权谱比,通过XGBoost方法获得降噪后的谱比曲线。将本文方法与传统STA/LTA(short time average/long time average)方法进行实际高噪声数据对比分析,结果表明相比于STA/LTA方法,本文方法对高噪声数据提取效果更好。