Globally, groundwater represents a critical natural resource that is affected by changes in
natural supply and renewal, as well as by increasing human demand and consumption …

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

We present a novel method for joint inversion of receiver functions and surface wave
dispersion data, using a transdimensional Bayesian formulation. This class of algorithm …

Non-linear inverse problems in the geosciences often involve probabilistic sampling of
multimodal density functions or global optimization and sometimes both. Efficient algorithmic …

Seismic full-waveform inversion (FWI) provides high resolution images of the subsurface by
exploiting information in the recorded seismic waveforms. This is achieved by solving a …

A meaningful interpretation of seismic measurements requires a rigorous quantification of
the uncertainty. In an inverse problem, the data noise determines how accurately …

We tested a new robust concept for the calculation of depth of investigation (DOI) that is valid
for any 1D electromagnetic (EM) geophysical model. A good estimate of DOI is crucial when …

Conventional geophysical inversion techniques suffer from several limitations including
computational cost, nonlinearity, non-uniqueness and dimensionality of the inverse problem …

Inversion of electromagnetic data finds applications in many areas of geophysics. The
inverse problem is commonly solved with either deterministic optimization methods (such as …

Seismologists construct images of the Earth's interior structure using observations, derived
from seismograms, collected at the surface. A common approach to such inverse problems …