A meaningful solution to an inversion problem should be composed of the preferred
inversion model and its uncertainty and resolution estimates. The model uncertainty …

The Earth below ground is the subject of interest for many geophysical as well as geological
investigations. Even though most practitioners would agree that all available information …

Full-waveform inversion (FWI) enables us to obtain high-resolution subsurface images;
however, estimating model uncertainties associated with this technique is still a challenging …

Bayesian inference for high-dimensional inverse problems is computationally costly and
requires selecting a suitable prior distribution. Amortized variational inference addresses …

The nonuniqueness problem in geophysical inversion, especially potential-field inversion, is
widely recognized. It is argued that uncertainty analysis of a recovered model should be as …

In statistical inverse problems, the objective is a complete statistical description of unknown
parameters from noisy observations to quantify uncertainties in unknown parameters. We …

Seismic imaging is conventionally performed using noisy data and a presumably inexact
velocity model. Uncertainties in the input parameters propagate directly into the final image …

In our first paper (Part 1) about the square-root variable metric (SRVM) method we
presented the basic theory and validation of the inverse algorithm applicable to large-scale …

Time-lapse seismic monitoring using full-wavefield methods aims to accurately and robustly
image rock and fluid changes within a reservoir. These changes are typically small and …

Distributed acoustic sensing (DAS) technologies are now becoming widespread, particularly
in vertical seismic profiling (VSP). Being a spatially densely sampled recording of the …