2016
DOI: 10.1111/1365-2478.12477
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First‐arrival traveltime tomography with modified total‐variation regularization

Abstract: First‐arrival traveltime tomography is a robust tool for near‐surface velocity estimation. A common approach to stabilizing the ill‐posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a first‐arrival traveltime tomography method with modified total‐variation regularization to preserve sharp velocity contrasts and improve the accuracy of velocit… Show more

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Cited by 28 publications
(19 citation statements)
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“…Thus, in the course of seismic data acquisition and processing, we encountered difficulties (Chen et al 2015) of crossing obstacles, removing harmful scattered waves, and building complex near-surface velocity models. To address those problems, targeted techniques such as cross-obstacle seismic geometry design, angle-domain vector resolution based scattered wave removal (Liu 2013;He et al 2015), and an acoustic wave equation-based inversion method jointly utilizing both the travel time and waveform of first arrival waves (Luo and Schuster 1991;Jiang and Zhang 2016;Yao et al 2019), were adopted.…”
Section: Edited By Jie Haomentioning
confidence: 99%
“…Thus, in the course of seismic data acquisition and processing, we encountered difficulties (Chen et al 2015) of crossing obstacles, removing harmful scattered waves, and building complex near-surface velocity models. To address those problems, targeted techniques such as cross-obstacle seismic geometry design, angle-domain vector resolution based scattered wave removal (Liu 2013;He et al 2015), and an acoustic wave equation-based inversion method jointly utilizing both the travel time and waveform of first arrival waves (Luo and Schuster 1991;Jiang and Zhang 2016;Yao et al 2019), were adopted.…”
Section: Edited By Jie Haomentioning
confidence: 99%
“…Tomographic inversion algorithms originate from medical CT imaging technology, also known as image reconstruction technology. The purpose is to obtain the internal profile image of the detected object based on the path data obtained by forward calculation, inversion calculation and velocity distribution diagrams [27], [28]. However, it is very difficult to calculate the solution of the large linear equations formed by forward calculation accurately because of the large amount of data, incompatibility and ill-condition of the equations.…”
Section: Principle Of Saga Tomographic Inversion Algorithmmentioning
confidence: 99%
“…Researchers around the globe have made numerous attempts to suppress staircase artifacts and improve imaging accuracy. ese improvements can be divided into the following categories: (1) generalize the difference of operation in TV to a higher-order difference [18][19][20] or fractional-order difference [21] such as high-order TV [18][19][20][21], total generalized variation [22], and fractional-order TV [23,24]; (2) extend the L1 norm in TV to the Lp quasinorm (0<p < 1) that can obtain sparser solution than the L1 norm, such as TpV [11,17,25,27]; (3) generalize the gradient in TV to the overlapping combination gradient information, such as overlapping group sparsity total variation [28][29][30][31][32]; (4) use Tikhonov regularization and TV regularization to solve the objective function in an alternative way, such as modified TV [33][34][35]; and (5) generalize the two-directional gradient to multidirectional gradient in TV, such as multidirectional TV [3,4,36]. TV can be divided into isotropic total variation (ITV) and anisotropic total variation (ATV) [10,37].…”
Section: Introductionmentioning
confidence: 99%