Harnessing sedimentary reverberations: A joint inversion approach for enhanced crustal imaging

Summary P-wave receiver functions (RFs), which utilize P-wave conversions to probe subsurface structures, face significant challenges in sedimentary environments. Specifically, strong reverberations generated by ultra-low-velocity sedimentary layers distort RF waveforms and obscure crustal signals, posing challenges for robust shallow crustal imaging. We develop a novel Bayesian joint inversion framework that simultaneously utilizes three complementary datasets—reverberant receiver functions, dereverberated receiver functions, and surface wave dispersion—to address this challenge. Our approach employs Unscented Kalman Inversion, a derivative-free method that efficiently handles nonlinear joint inversion problems. Synthetic tests demonstrate that our joint inversion recovers sediment thickness and Moho depth with uncertainties of ±0.50 km and ±1.0 km, respectively. Application to real data from the Songliao Basin verifies the approach, successfully reconstructing sediment thickness and Moho depth beneath sedimentary cover. This methodology demonstrates potential for advancing crustal investigations in complex sedimentary settings, such as continental rift basins and oceanic margins, where sedimentary sequences of variable thickness often obscure deeper structures.