Monte Carlo inversion techniques were first used by Earth scientists more than 30 years
ago. Since that time they have been applied to a wide range of problems, from the inversion …

We review the current state-of-the-art of diffuse optical imaging, which is an emerging
technique for functional imaging of biological tissue. It involves generating images using …

State-of-the-art computer codes for simulating real physical systems are often characterized
by vast number of input parameters. Performing uncertainty quantification (UQ) tasks with …

Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at
New Mexico Tech and is designed to be accessible to typical graduate students in the …

Providing an up-to-date overview of the most popular global optimization methods used in
interpreting geophysical observations, this new edition includes a detailed description of the …

In this self-contained survey/review paper, we systematically investigate the roots of
Bayesian filtering as well as its rich leaves in the literature. Stochastic filtering theory is …

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

We present a reformulation of the Bayesian approach to inverse problems, that seeks to
accelerate Bayesian inference by using polynomial chaos (PC) expansions to represent …

This paper presents the results of integrating microseismic fracture map** with numerical
production modeling of fracture networks in the Barnett shale. Microseismic fracture …

Surface-wave dispersion analysis is widely used in geophysics to infer a shear wave
velocity model of the subsoil for a wide variety of applications. A shear-wave velocity model …