Probabilistic inversion of seismic data for reservoir petrophysical characterization: Review and examples

D Grana, L Azevedo, L De Figueiredo, P Connolly… - Geophysics, 2022 - library.seg.org
The physics that describes the seismic response of an interval of saturated porous rocks with
known petrophysical properties is relatively well understood and includes rock physics …

[HTML][HTML] 4D seismic history matching

DS Oliver, K Fossum, T Bhakta, I Sandø… - Journal of Petroleum …, 2021 - Elsevier
Reservoir simulation models are used to forecast future reservoir behavior and to optimally
manage reservoir production. These models require specification of hundreds of thousands …

[HTML][HTML] Geology-driven modeling: A new probabilistic approach for incorporating uncertain geological interpretations in 3D geological modeling

RB Madsen, AS Høyer, LT Andersen, I Møller… - Engineering …, 2022 - Elsevier
Combining different sources of information about the subsurface is an inherent challenge in
the process of making realistic geological and hydrostratigraphic models. Often the available …

Markov chain Monte Carlo for seismic facies classification

D Grana, L de Figueiredo, K Mosegaard - Geophysics, 2023 - library.seg.org
Seismic facies classification aims to predict a facies model, or a set of facies models, from
measured seismic data. We focus on stochastic classification methods to estimate the …

Bayesian tomography with prior-knowledge-based parametrization and surrogate modelling

GA Meles, N Linde, S Marelli - Geophysical Journal International, 2022 - academic.oup.com
We present a Bayesian tomography framework operating with prior-knowledge-based
parametrization that is accelerated by surrogate models. Standard high-fidelity forward …

Reconstruction, with tunable sparsity levels, of shear wave velocity profiles from surface wave data

G Vignoli, J Guillemoteau, J Barreto… - Geophysical Journal …, 2021 - academic.oup.com
The analysis of surface wave dispersion curves is a way to infer the vertical distribution of
shear wave velocity. The range of applicability is extremely wide: going, for example, from …

Markov chain Monte Carlo algorithms for target‐oriented and interval‐oriented amplitude versus angle inversions with non‐parametric priors and non‐linear forward …

M Aleardi, A Salusti - Geophysical Prospecting, 2020 - earthdoc.org
In geophysical inverse problems, the posterior model can be analytically assessed only in
case of linear forward operators, Gaussian, Gaussian mixture, or generalized Gaussian prior …

[HTML][HTML] 3D multiple-point geostatistical simulation of joint subsurface redox and geological architectures

RB Madsen, H Kim, AJ Kallesøe… - Hydrology and Earth …, 2021 - hess.copernicus.org
Nitrate contamination of subsurface aquifers is an ongoing environmental challenge due to
nitrogen (N) leaching from intensive N fertilization and management on agricultural fields …

Hamiltonian Monte Carlo algorithms for target-and interval-oriented amplitude versus angle inversions

M Aleardi, A Salusti - Geophysics, 2020 - library.seg.org
ABSTRACT A reliable assessment of the posterior uncertainties is a crucial aspect of any
amplitude versus angle (AVA) inversion due to the severe ill-conditioning of this inverse …

Use of machine learning to estimate statistics of the posterior distribution in probabilistic inverse problems—An application to airborne EM data

TM Hansen, CC Finlay - Journal of Geophysical Research …, 2022 - Wiley Online Library
The solution to a probabilistic inverse problem is the posterior probability distribution for
which a full analytic expression is rarely possible. Sampling methods are therefore often …