scholarly journals Optimized Refraction Travel Time Tomography

2019 ◽  
Vol 9 (24) ◽  
pp. 5439 ◽  
Author(s):  
Sixin Liu ◽  
Zhuo Jia ◽  
Yinuo Zhu ◽  
Xueran Zhao ◽  
Siyuan Cheng

In seismic refraction exploration, travel time tomography is the most widely used method in engineering and environmental geophysical exploration. In this paper, we mainly optimize the travel time tomography of refraction. First, with respect to the forward algorithm, we introduce a new travel time calculation method to improve the accuracy and efficiency of forward calculation. Based on the fast marching method (FMM), we introduce an improved forward calculation method called the multi-stencil fast marching method (MSFM). In the process of inversion, we propose a dynamic prior model composite constraint (DPMCC) method based on the T0 difference method from the idea of multi-scale inversion. Meanwhile, we use the prior information to improve the accuracy of inversion. Furthermore, we use the dynamic regularization factor selection method to make the inversion solution more stable and reliable. Finally, we test and analyze the synthetic data and the measured data to verify the effectiveness of the optimized travel time tomography algorithm.

2018 ◽  
Vol 22 (4) ◽  
pp. 327-334 ◽  
Author(s):  
Hui Sun ◽  
Fanchang Meng ◽  
Zhihou Zhang ◽  
Cheng Gao ◽  
Mingchen Liu

Fast Marching Method (FMM) boasts high calculation efficiency and strong adaptability and stability while being applied to seismic traveltime. However, when it is applied to the largescale model, the calculation precision of FMM is insufficient. FMM has poor calculation precision near the source, which is an essential reason for the low accuracy of the whole algorithm. This paper puts forward a joint traveltime calculation method to address the problem. Wavefront Construction (WFC) with a relatively high calculation accuracy rather than FMM is adopted for calculation of the grid nodes’ traveltime near the source. After that, FMM is used to calculate the seismic traveltime in the remaining area. Joint traveltime calculation method greatly improves the calculation accuracy of the source’s surrounding area and the calculation accuracy of FMM. According to the new method, FMM is still adopted for the calculation of most grid nodes in the model, so the high calculation efficiency of FMM is maintained. Multiple numerical models are utilized to verify the above conclusions in the paper. 


Open Physics ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 281-284
Author(s):  
Fanchang Meng ◽  
Mingchen Liu ◽  
Ping Zhang ◽  
Junjie Yang ◽  
Meng Li ◽  
...  

Abstract The fast marching method (FMM) is an efficient, stable and adaptable travel time calculation method. In the realization of this method, it is necessary to select the minimum travel time node from the narrow band many times. The selection method has an important influence on the calculation efficiency of FMM. Traditional FMM adopts the binary tree heap sorting method to achieve this step. Fibonacci heap sort method to FMM will be applied in this study. Compared with the binary tree heap sorting method, the Fibonacci heap sort method can realize the minimum travel time node selection in the narrow band in a more efficient way when the number of the narrow-band nodes is huge. The new method will be verified through error analysis and two numerical model calculations.


2013 ◽  
Vol 51 (6) ◽  
pp. 2999-3035 ◽  
Author(s):  
E. Carlini ◽  
M. Falcone ◽  
Ph. Hoch

2018 ◽  
Vol 7 (3) ◽  
pp. 1233
Author(s):  
V Yuvaraj ◽  
S Rajasekaran ◽  
D Nagarajan

Cellular automata is the model applied in very complicated situations and complex problems. It involves the Introduction of voronoi diagram in tsunami wave propagation with the help of a fast-marching method to find the spread of the tsunami waves in the coastal regions. In this study we have modelled and predicted the tsunami wave propagation using the finite difference method. This analytical method gives the horizontal and vertical layers of the wave run up and enables the calculation of reaching time.  


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