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First-Arrival Tomography with Fast Sweeping Method Solving the Factored Eikonal Equation

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First-Arrival Tomography with Fast Sweeping Method Solving the Factored Eikonal Equation Exploration Geophysics ISSN: 0812-3985 (Print) 1834-7533 (Online) Journal homepage: https://www.tandfonline.com/loi/texg20 First-arrival tomography with fast sweeping method solving the factored eikonal equation Guangnan Huang, Songting Luo, Tryggvason Ari, Hongxing Li & David C. Nobes To cite this article: Guangnan Huang, Songting Luo, Tryggvason Ari, Hongxing Li & David C. Nobes (2019): First-arrival tomography with fast sweeping method solving the factored eikonal equation, Exploration Geophysics To link to this article: https://doi.org/10.1080/08123985.2019.1577110 Published online: 26 Feb 2019. Submit your article to this journal View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=texg20 EXPLORATION GEOPHYSICS https://doi.org/10.1080/08123985.2019.1577110 First-arrival tomography with fast sweeping method solving the factored eikonal equation Guangnan Huanga,b,c, Songting Luoc, Tryggvason Arid, Hongxing Lia,b and David C. Nobesa,b aState Key Laboratory of Nuclear Resources and Environment, East China University of Technology, Nanchang, China; bDepartment of Geophysics, East China University of Technology, Nanchang, China; cDepartment of Mathematics, Iowa State University, Ames, IA, USA; dDepartment of Earth Science, Uppsala University, Uppsala, Sweden ABSTRACT ARTICLE HISTORY This paper presents a first-arrival tomography incorporating a fast sweeping method (FSM) solv- Received 16 June 2018 ing the factored eikonal equation (factored FSM). The traveltime calculation method plays a Accepted 25 January 2019 significant role in velocity inversion. However, for a point source condition, all finite-difference KEYWORDS based eikonal solvers suffer from the source singularity problem. Numerical error caused by seismic tomography; fast source singularity will propagate from the source to all computational domains, and makes sweeping method; factored traveltimes inaccurate. A FSM solving the factored eikonal equation can deal with the source sin- eikonal equation gularity problem very well. Therefore, a first-arrival tomography is developed by incorporating 2D and 3D factored FSMs to provide more accurate traveltimes in velocity inversion. For com- parison, an open source package PStomo_eq is used to invert the same data set. It incorporates the traveltime calculation algorithms fdtime2d.c and fdtime3d.c. Traveltime accuracy tests show that factored FSM can generate more accurate traveltimes than FSM, fdtime2d.c and fdtime3d.c. Numerical and field data tests show that inversion with factored FSM can acquire much better tomograms than inversion with fdtime2d.c and fdtime3d.c. Therefore, it is worthwhile using a more accurate traveltime computation method in velocity inversion. Introduction Methods of traveltime computation are well devel- Seismic traveltime tomography can invert a few param- oped, for example, the shooting and bending method, eters (velocity of longitudinal wave and shear wave, shortest path method, wavefront reconstruction quality factor, anisotropic parameters, etc.) by use of method and finite-difference based eikonal solver. The large numbers of arrival times. In seismology and geo- ray-tracing method can provide accurate traveltimes, dynamics, earth structures can be obtained by use of but it is difficult to pass through shadow zones when seismic events received continuously from stations (Aki the model is complicated (Cerveny 2001). The shortest and Lee 1976; Engdahl, Hilst, and Buland 1998). Velocity path method is based on graph theory (Nakanishi and information can be used to investigate oceanic ridges, Yamaguchi 1986; Moser 1991; Fischer and Lees 1993; continental plate subduction zones, volcanic channels, Zhou and Greenhalgh 2006; Huang et al. 2014, 2017). It geological faults, and the interface between the man- has good numerical stability, but low accuracy and effi- tle and the core (Lees 1992; Kennett, Engdahl, and ciency (Cheng and House 1996; Leidenfrost et al. 1999). Buland 1995; Calvert and Fisher 2001; Rawlinson and The wavefront reconstruction method uses a local ray- Fishwick 2012). In resource exploration, seismic travel- tracing method for the current wavefront repeatedly time tomography is used successfully in exploring oil to obtain a new wavefront, until all traveltimes are and gas reservoirs, coal and nonferrous metal deposits. computed for the whole computational domain (Vinje, Statics and seismic migration rely greatly on an accurate Iversen, and Gjoystdal 1993, 1999; Ettrich and Gajewski velocity model which can be obtained from traveltime 1996; Lambare, Lucio, and Hanyga 1996). This method tomography (Vesnaver et al. 2003; Bergman, Tryggva- costs too much in terms of computational time for son, and Juhlin 2004;Zhou2006). In engineering inves- the same level of accuracy, compared with the finite- tigations, seismic traveltime tomography is used widely difference based eikonal solver (Leidenfrost et al. 1999). in the detection of dam water leakage and underground The eikonal solver is the most promising method. Vidale water pollution, foundation investigations, etc. (Ajo- (1988, 1990) is a pioneer of the use of a finite-difference Franklin, Urban, and Harris 2006; Zelt, Azaria, and Levan- scheme to calculate traveltimes. This method has been der 2006; Marti, Carbonell, and Flecha 2008). developed and modified further by many geophysi- CONTACT Guangnan Huang [email protected] Department of Geophysics, East China University of Technology, Nanchang, 330013, China © 2019 Australian Society of Exploration Geophysics 2 G. HUANG ET AL. cists (Podvin and Lecomte 1991; Van Trier and Symes 1991; Qin, Luo, and Olsen 1992;HoleandZelt1995; Kim and Cook 1999). Among these methods, the fast- marching method (FMM) (Sethian and Popovici 1999) and fast sweeping method (FSM) (Tsai Cheng, Osher, and Zhao 2003;Zhao2005) are the most promising. FMM incorporates an upwind finite-difference scheme, narrow-band technique and heap-sorting algorithm to describe wavefront expansion. Its computational com- plexity is O(NlogN), where N is total number of grid Figure 1. 2D rectangular mesh. points. FSM is an iterative method. It incorporates an upwind finite-difference scheme and Gauss–Seidel iter- ation with alternating sweeping orderings. Its computa- tional complexity is O(N). There are two important features in seismic trav- eltime tomography: (1) the traveltime computation method; and (2) a regularised inversion algorithm to reduce the discrepancy between observed and cal- culated traveltimes. Therefore, traveltime accuracy is very important in seismic traveltime tomography. For a point source condition, traveltimes calculated by eikonal solver suffer from the source singularity prob- lem (Qian and Symes 2002a; Waheed and Alkhalifah 2017). The numerical error of a finite-difference approx- imation near the source point is very large. This error Figure 2. Traveltime calculation for transmission wave. s and s can spread from the source to the whole computational are the slowness of the current cell and its adjacent cell. domain and renders all finite-difference based eikonal solvers first-order convergence at most. One approach to dealing with the source singularity problem is to set a homogeneous velocity block near the source point to calculate analytical solutions for these points (Qian and Symes 2001;Han,Zhang,andZhang2017). Another approach is to refine the grid near the source point to reduce large truncation errors (Kim and Cook 1999; Qian and Symes 2002b). Fomel, Luo, and Zhao (2009)pro- Figure 3. Traveltime calculation for diffracted waves. A local posed a FSM to solve the factored eikonal equation, shadow zone is presented and corner Q acts as a secondary which deals with the source singularity problem very source. well. Here, we introduce a FSM to solve 2D and 3D fac- velocity model are used for comparison. (3) 2D and 3D tored eikonal equations. It breaks down the solution factored FSMs, fdtime2d.c and fdtime3d.c areusedinthe of the eikonal equation into two factors: one factor PStomo_eq program to invert 2D and 3D checkerboard is calculated analytically, and the other is a necessary velocity models. (4) the PStomo_eq program incorpo- modification (smoothing) in the neighbourhood of the rating different traveltime computation algorithms is source point. For comparison, we use the PStomo_eq used to invert 2D and 3D field data sets. (5) Conclu- program to implement velocity inversion incorporating sions are drawn about factored FSM and its application fdtime2d.c and fdtime3d.c. 2D and 3D factored FSMs are in numerical and field examples. used to replace fdtime2d.c and fdtime3d.c in PStomo_eq to provide more accurate traveltimes for velocity inver- sion. The traveltimes of P- and S-waves are used in trav- Methodology eltime tomography to resolve the non-uniqueness of Seismic traveltime tomography the inverse problem. The remainder of this paper is organised as follows: Linearisation and discretisation are used in seismic trav- (1) We introduce the methodology of seismic travel- eltime tomography (Lees and Crosson 1989). The com- time tomography, factored FSM and the principle of putational domain is often discretised with a certain fdtime2d.c are also recalled briefly. (2) An analytical solu- mesh size. The slowness of each cell or grid is assumed tion and traveltimes calculated using the factored FSMs, to be constant. The ray path and traveltime for each FSMs, fdtime2d.c and fdtime3d.c of a constant gradient
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