Waveform modelling of teleseismicS, Sp, SsPmP, and shear-coupled PL waves for crust- and upper-mantle velocity structure beneath Africa

Abstract

S U M M A R YWe describe a waveform modelling technique and demonstrate its application to determine the crust-and upper-mantle velocity structure beneath Africa. Our technique uses a parallelized reflectivity method to compute synthetic seismograms and fits the observed waveforms by a global optimization technique based on a Very Fast Simulated Annealing (VFSA). We match the S, Sp, SsPmP and shear-coupled PL phases in seismograms of deep (200-800 km), moderateto-large magnitude (5.5-7.0) earthquakes recorded teleseismically at permanent broad-band seismic stations in Africa. Using our technique we produce P-and S-wave velocity models of crust and upper mantle beneath Africa. Additionally, our use of the shear-coupled PL phase, wherever observed, improves the constraints for lower crust-and upper-mantle velocity structure beneath the corresponding seismic stations. Our technique retains the advantages of receiver function methods, uses a different part of the seismogram, is sensitive to both P-and S-wave velocities directly, and obtains helpful constraints in model parameters in the vicinity of the Moho. The resulting range of crustal thicknesses beneath Africa (21-46 km) indicates that the crust is thicker in south Africa, thinner in east Africa and intermediate in north and west Africa. Crustal P-(4.7-8 km s −1 ) and S-wave velocities (2.5-4.7 km s −1 ) obtained in this study show that in some parts of the models, these are slower in east Africa and faster in north, west and south Africa. Anomalous crustal low-velocity zones are also observed in the models for seismic stations in the cratonic regions of north, west and south Africa. Overall, the results of our study are consistent with earlier models and regional tectonics of Africa.

Spatial variations of crustal characteristics beneath the Hoggar swell, Algeria, revealed by systematic analyses of receiver functions from a single seismic station

“…The Figure 6a, demonstrating the significance of the peak which is marked by the black dot in Figure 6a. crustal thickness is similar to that obtained by Sandvol et al [1998] and Gangopadhyay et al [2007], and is almost identical to the value used by Ayadi et al [2000] in their tomographic inversion. The crustal P-wave velocity of 6.5 km/s is chosen based on active-source seismic surveys conducted in stable parts of Africa such as the Kaapvaal craton [Durrheim and Green, 1992] and the average crustal P-wave velocity from the RF studies of Sandvol et al [1998] and Gangopadhyay et al [2007].…”

“…Sandvol et al [1998] concluded that the crustal structure beneath the station is very homogeneous. Similarly, under the assumption of a laterally homogeneous crust, Gangopadhyay et al [2007] revealed a crustal thickness of 36 km and a P-and S-wave velocity range of 6.25-6.8 km/s and 3.1-3.9 km/s, respectively, using data from 6 events. As shown below, our results suggest a dramatic contrast in Moho characteristics between the Tefedest and Laouni terranes sampled by the 1386 events used in the study, highlighting the importance of additional data and that of a data analysis approach that is beyond the common assumption of laterally homogeneous crust beneath a station.…”

Lithospheric structure of the Texas‐Gulf of Mexico passive margin from surface wave dispersion and migrated Ps receiver functions

“…Linear methods, such as least squares methods, are best suited to finding models that are quite similar to the starting model, rather than the single, best fitting model within a given model space. Therefore, in this analysis, we employ a stochastic, nonlinear, global optimization technique known as Very Fast Simulated Annealing (VFSA), which is weakly dependent on the choice of initial model [ Sen and Stoffa , ; Gangopadhyay et al ., ; Agrawal et al ., ; Zhao et al ., ; Ingber , ]. VFSA is a variant of Simulated Annealing (SA) that is aimed at making computations more efficient [ Ingber , ; Sen and Stoffa , ].…”

Forward waveform modelling procedure for 1-D crustal velocity structure and its application to the southern Korean Peninsula

“…Monte Carlo technique) to address this problem. Many authors have previously described the use of this method in waveform inversion, such as simulated annealing (Sen & Stoffa 1991; Riepl et al 1995; Steck 1995; Zhao et al 1996; Gangopadhyay et al . 2007), the genetic algorithm (Noves et al 1996; Shibutani et al 1996; Bhattacharyya et al 1999; Chang & Baag 2006; Li et al 2007; Lee & Baag 2008) and the neighbourhood algorithm (Sambridge 1999a,b; Yoshizawa & Kennett 2002).…”