Geophysical Journal International

SummarySeismological inversion traditionally targets either source parameters, such as location and moment tensor, or structural parameters, such as velocity and anisotropy. However, the natural formulation of Full-Waveform Inversion, often used for high-resolution structural model estimation, is to jointly invert for source and structural parameters. The common practice of holding source parameters, after initial estimation, fixed throughout the inversion inherently leads to biased solutions of the structural model, and vice versa. Whereas a joint inversion suffers from severe non-uniqueness, we demonstrate that leveraging the large amounts of data available from Distributed Acoustic Sensing (DAS) can yield robust and unbiased estimations of source and structural parameters, provided an appropriate misfit function and optimisation scheme are used. We show how the size of the data space and eventual convergence can be improved by supplementing the phase misfit objective function with amplitude information. To this end, we formulate a new misfit function, the normalised envelope. To support native DAS data implementations, we calculate the adjoint sources for the new misfit function when defined directly on strain or strain-rate data. We also show how a new approach to preconditioning as part of the L-BFGS optimisation scheme allows for effective updates of all parameters in the same iteration, despite enormous differences in their relative importance. We test our approach in a challenging synthetic noisy 2D scenario, showing a considerable reduction in source parameter errors and an improved S-wave velocity model. We also show a 3D synthetic case with an idealised DAS recording array, demonstrating a significant reduction of source parameter errors using realistic initial estimates and structural model errors. We argue that the proposed methodology can be used to improve the quality of earthquake catalogues and high-resolution structural models in seismically active regions, especially at the local-to-regional scale. None the less, computational cost remains a major challenge of the method.

SummaryTo understand the melt source of hotlines with asynchronous volcanoes, we investigate the lithospheric structure of the Cameroon Volcanic Line (CVL), an intraplate hotline without age progression stretching from the Atlantic Ocean into Central Africa. We analyze Bouguer gravity anomalies from the World Gravity Model 2012 using the 2‐D power spectrum techniques and 2-D forward modeling to estimate the crustal and lithospheric thickness. We find: (1) thin crust (20–30 km) beneath the oceanic CVL; (2) thick crust (30–43 km) beneath the continental CVL and the Oubanguides Belt, and thicker crust (43–50 km) beneath the Congo Craton; (3) thin lithosphere (90–120 km) beneath the oceanic CVL and thinner lithosphere (75–90 km) beneath the continental CVL; and (4) thicker lithosphere (150–234 km) beneath the Congo Craton. Our seismically constrained forward models reveal a delaminated body beneath the continental CVL and a sharp transition from thick lithosphere beneath the Congo Craton to thin lithosphere beneath the Oubanguides Belt. We interpret that the thin lithosphere beneath the continental CVL is a result of lithospheric delamination. The delaminated body in the uppermost mantle deflects rising mantle plume material, resulting in the Y-shaped distribution of continental volcanoes. Edge-Driven Convection (EDC) resulting from the sharp gradient in lithospheric thickness between the Congo Craton and the Oubanguides Belt focuses the plume material beneath thin lithosphere, producing the continental CVL. The southern volcanoes of the continental CVL are formed from the southward deflection of plume material by the delaminated body, with melt ascent facilitated by the lithospheric-scale Central African Shear Zone. The northward-directed plume material forms the distinct Biu Plateau, and the eastward-deflected plume material forms the Adamawa Plateau. With a continuous influx of plume material beneath the thin continental lithosphere, for mass to be conserved, part of the plume material defiles the gradient of the thicker oceanic lithosphere adjacent to the Congo Craton to flow oceanward. The oceanward flow of plume material is modulated by upwellings from EDC, producing the oceanic CVL, which explains the oceanward decrease in the timing of the onset of volcanism. We therefore conclude that only the continental CVL lacks age progression resulting from the complex interaction of the rising plume with the delaminated body and the lithospheric architecture.

SummaryInferring the spatio-temporal distribution of slip during earthquakes remains a significant challenge due to the high dimensionality and ill-posed nature of the inverse problem. As a result, finite-source inversions typically rely on simplified assumptions. Moreover, in the absence of ground-truth measurements, the performance of inversion methods can only be evaluated through synthetic tests. Laboratory earthquakes offer a valuable alternative by providing “simulated real data” and ground truth observations under controlled conditions, enabling a more reliable evaluation of source inversion procedures. In this study, we present static and quasi-static slip inversion results from data recorded during laboratory earthquakes. Each event is instrumented with 20 accelerometers along the fault, and the recorded acceleration data are used to invert for the slip history. We consider two different types of Green’s functions (GF): simplistic GF assuming a homogeneous elastic half-space and realistic GF computed by finite element modeling of the experimental setup. The inversion results are then compared to direct observations of fault slip and rupture velocity obtained independently during the experiments. Our results show that, regardless of the GF used, the inversions fit well with the data and result in small formal uncertainties of model parameters. However, only the inversion with realistic GF yields slip distributions consistent with the true fault slip measurements and successfully recovers the distribution of rupture velocity along the fault. These findings emphasize the critical role of GF selection in accurately resolving slip dynamics and highlight an important distinction in Bayesian inversion: while posterior uncertainty quantification is essential, it does not guarantee accuracy, especially if forward modeling uncertainties are not properly accounted for. Thus, confidence in inversion results must be paired with careful modeling choices to ensure physical reliability.