scholarly journals A multichannel deconvolution method to retrieve source–time functions: application to the regional Lg wave

2020 ◽  
Vol 223 (1) ◽  
pp. 323-347
Author(s):  
Andrea Gallegos ◽  
Jiakang Xie

SUMMARY The retrieval of high-frequency seismic source–time functions (STFs) of similar earthquakes tends to be an ill-posed problem, causing unstable solutions. This is particularly true when waveforms are complex and band-limited, such as the regional phase Lg. We present a new procedure implementing the multichannel deconvolution (MCD) method to retrieve robust and objective STF solutions. The procedure relies on well-developed geophysical inverse theory to obtain stable STF solutions that jointly minimize the residual misfit, model roughness and data underfitting. MCD is formulated as a least-squares inverse problem with a Tikhonov regularization. The problem is solved using a convex optimization algorithm which rapidly converges to the global minimum while accommodating physical solution constraints including positivity, causality, finiteness and known seismic moments. We construct two L-shaped curves showing how the solution residual and roughness vary with trial solution durations. The optimal damping is chosen when the curves have acceptable levels while exhibiting no oscillations caused by solution instability. The optimal solution duration is chosen to avoid a rapidly decaying segment of the residual curve caused by parameter underfitting. We apply the MCD method to synthetic Lg data constructed by convolving a real Lg waveform with five pairs of simulated STFs. Four pairs consist of single triangular or parabolic pulses. The remaining pair consists of multipulse STFs with a complex, four-spike large STF. Without noise, the larger STFs in all single-pulse cases are well-recovered with Tikhonov regularization. Shape distortions are minor and duration errors are within 5 per cent. The multipulse case is a rare well-posed problem for which the true STFs are recovered without regularization. When a noise of ∼20 per cent is added to the synthetic data, the MCD method retrieves large single-pulse STFs with minor shape distortions and small duration errors (from 0 to 18 per cent). For the multipulse case, the retrieved large STF is overly smeared, losing details in the later portion. The small STF solutions for all cases are less resilient. Finally, we apply the MCD method to Lg data from two pairs of moderate earthquakes in central Asia. The problem becomes more ill-posed owing to lower signal-to-noise ratios (as low as 3) and non-identical Green's functions. A shape constraint of the small STF is needed. For the larger events with M5.7 and 5.8, the retrieved STFs are asymmetric, rising sharply and lasting about 2.0 and 2.5 s. We estimate radiated energies of 2.47 × 1013 and 2.53 × 1013 J and apparent stresses of 1.4 and 1.9 MPa, which are very reasonable. Our results are very consistent with those obtained in a previous study that used a very different, less objective ‘Landweber deconvolution’ method and a pre-fixed small STF duration. Novel improvements made by our new procedure include the application of a convex algorithm rather than a Newton-like method, a procedure for simultaneously optimizing regularization and solution duration parameters, a shape constraint for the smaller STF, and application to the complex Lg wave.

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Nengjian Wang ◽  
Chunping Ren ◽  
Chunsheng Liu

This paper presents a novel inverse technique to provide a stable optimal solution for the ill-posed dynamic force identification problems. Due to ill-posedness of the inverse problems, conventional numerical approach for solutions results in arbitrarily large errors in solution. However, in the field of engineering mathematics, there are famous mathematical algorithms to tackle the ill-posed problem, which are known as regularization techniques. In the current study, a novel fractional Tikhonov regularization (NFTR) method is proposed to perform an effective inverse identification, then the smoothing functional of the ill-posed problem processed by the proposed method is regarded as an optimization problem, and finally a stable optimal solution is obtained by using an improved super-memory gradient (ISMG) method. The result of the present method is compared with that of the standard TR method and FTR method; new findings can be obtained; that is, the present method can improve accuracy and stability of the inverse identification problem, robustness is stronger, and the rate of convergence is faster. The applicability and efficiency of the present method in this paper are demonstrated through a mathematical example and an engineering example.


2020 ◽  
Vol 18 (1) ◽  
pp. 1685-1697
Author(s):  
Zhenyu Zhao ◽  
Lei You ◽  
Zehong Meng

Abstract In this paper, a Cauchy problem for the Laplace equation is considered. We develop a modified Tikhonov regularization method based on Hermite expansion to deal with the ill posed-ness of the problem. The regularization parameter is determined by a discrepancy principle. For various smoothness conditions, the solution process of the method is uniform and the convergence rate can be obtained self-adaptively. Numerical tests are also carried out to verify the effectiveness of the method.


2008 ◽  
Vol 8 (1) ◽  
pp. 86-98 ◽  
Author(s):  
S.G. SOLODKY ◽  
A. MOSENTSOVA

Abstract The problem of approximate solution of severely ill-posed problems given in the form of linear operator equations of the first kind with approximately known right-hand sides was considered. We have studied a strategy for solving this type of problems, which consists in combinating of Morozov’s discrepancy principle and a finite-dimensional version of the Tikhonov regularization. It is shown that this combination provides an optimal order of accuracy on source sets


2013 ◽  
Vol 416-417 ◽  
pp. 1393-1398
Author(s):  
Chao Zhong Ma ◽  
Yong Wei Gu ◽  
Ji Fu ◽  
Yuan Lu Du ◽  
Qing Ming Gui

In a large number of measurement data processing, the ill-posed problem is widespread. For such problems, this paper introduces the solution of ill-posed problem of the unity of expression and Tikhonov regularization method, and then to re-collinearity diagnostics and metrics based on proposed based on complex collinearity diagnostics and the metric regularization method is given regularization matrix selection methods and regularization parameter determination formulas. Finally, it uses a simulation example to verify the effectiveness of the method.


Sign in / Sign up

Export Citation Format

Share Document