Crustal structure of Sri Lanka derived from joint inversion of surface wave dispersion and receiver functions using a Bayesian approach

Abstract

We study the crustal structure of Sri Lanka by analyzing data from a temporary seismic network deployed in 2016--2017 to shed light on the amalgamation process from a geophysical perspective. Rayleigh wave phase dispersion curves from ambient noise cross-correlation and receiver functions were jointly inverted using a transdimensional Bayesian approach.The Moho depths in Sri Lanka range between 30 and 40~km, with the thickest crust (38-40 km) beneath the central Highland Complex (HC). The thinnest crust (30-35 km) is found along the west coast, which experienced crustal thinning associated with the formation of the Mannar Basin. Vp/Vs ratios lie within a range of 1.60-1.82 and predominantly favor a felsic to intermediate bulk crustal composition with a significant silica content of the rocks.A major intra-crustal (18-27~km), slightly westward dipping (~4.3$^\circ$) interface with high Vs (~4 km/s) underneath is prominent in the central HC, continuing into the western Vijayan Complex (VC). The discontinuity might have been part of the respective units prior to the collision and could be an indicator for the proposed tilting of the WC/HC crustal sections. It might also be related to the deep crustal HC/VC thrust contact with the VC as an indenting promontory of high Vs. A low velocity zone in the central HC could have been caused by fluid influx generated by the thrusting process.

Joint Inversion of Receiver Functions and Apparent Incidence Angles to Determine the Crustal Structure of Mars

“…A Markov‐chain Monte Carlo (McMC) transdimensional Bayesian inversion method based on Bodin et al. (2012) (Dreiling & Tilmann, 2019) was used for the joint inversion of the mean RF and $${v}_{{S}_{,app}}$$ curve. In this formulation, the number of layers itself becomes an unknown and is also inverted for along with the other model parameters.…”

Joint Inversion of receiver functions and apparent incidence angles to determine the crustal structure of Mars

“…A Markov-chain Monte Carlo (McMC) transdimensional Bayesian inversion method based on Bodin et al (2012) (Dreiling & Tilmann, 2019) was used for the joint inversion of the mean RF and v S,app curve. In this formulation, the number of layers itself becomes an unknown and is also inverted for along with the other model parameters.…”

Shallow Crustal Shear Velocity and Vp/Vs Across Southern California: Joint Inversion of Short‐Period Rayleigh Wave Ellipticity, Phase Velocity, and Teleseismic Receiver Functions

“…In order to provide a model with resolution of Vs and Vp/Vs in the upper few km, we combine the complementary sensitivities of Rayleigh‐wave phase velocities (upper crust), ellipticity (upper few km), and the initial pulse of teleseismic receiver functions (shallow Vp/Vs ratio and shallow interfaces) to create a self‐consistent model at the regional scale across southern California. The idea to combine receiver functions and surface wave data in a Bayesian joint inversion to determine Vs and Vp/Vs is relatively new (Dreiling et al., 2020; Ojo et al., 2019), and only recently shown to be promising in resolving near‐surface Vs and Vp/Vs in sediments (Li et al., 2019). By including Vp/Vs as a parameter we are able to fit receiver functions on a regional scale for the first time across 231 Southern California stations, including in basins where receiver functions have long been discarded as nuisance signals or “corrected” with ad‐hoc models, as reverberations overprint Moho and other crustal signatures (e.g., Yeck et al., 2013).…”