[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 …

Inference of unexploded ordnance (UXO) by probabilistic inversion of magnetic data

MD Wigh, TM Hansen, A Døssing - Geophysical Journal …, 2020 - academic.oup.com
Magnetic modelling of unexploded ordnance (UXO) is a well-documented method used to
interpret magnetic anomalies occurring in UXO excavation surveys. By treating UXO as a …

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] Information content in 4D seismic data: Effect of correlated noise

DS Oliver - Journal of Petroleum Science and Engineering, 2022 - Elsevier
Several types of data used in history matching for subsurface reservoir characterization have
errors that are spatially or temporally correlated. Although it is often assumed that correlated …

Single-step probabilistic inversion of 3D seismic data of a carbonate reservoir in Southwest Iran

H Heidari, TM Hansen, H Amini, ME Niri, RB Madsen… - Geophysics, 2022 - library.seg.org
We use a sampling-based Markov chain Monte Carlo method to invert seismic data directly
for porosity and to quantify its uncertainty distribution in a hard-rock carbonate reservoir in …

Novel approaches to uncertainty estimation in seismic subsurface characterization

M Walker, A Crosby, A Lomas, E Kazlauskas… - The Leading …, 2024 - library.seg.org
Uncertainty estimation in subsurface characterization workflows is an important input to
decision-making in earth science-related problems. We present three methods to …

Estimation of a non‐stationary prior covariance from seismic data

RB Madsen, TM Hansen, H Omre - Geophysical Prospecting, 2020 - Wiley Online Library
Non‐stationarity in statistical properties of the subsurface is often ignored. In a classical
linear Bayesian inversion setting of seismic data, the prior distribution of physical …

Exploring noise models in approximate Bayesian inversion for facies

AF Jakobsen, HJ Hansen - 81st EAGE conference and exhibition 2019, 2019 - earthdoc.org
An inversion for geological parameters such as spatial distribution of facies with uncertainty
is one of the fundamental goals of seismic inversion/interpretation, since facies mapping is …

Assessment of the impact of noise magnitude and bandwidth variations on a probabilistic inversion of reflection seismic data

H Heidari, RB Madsen, H Amini, TM Hansen… - Geophysical …, 2023 - earthdoc.org
Accounting for an accurate noise model is essential when dealing with real data, which are
noisy due to the effect of environmental noise, failures and limitations in data acquisition and …

Assessment of the impact of noise magnitude and bandwidth variations on a probabilistic inversion of seismic data

H Heidari, RB Madsen, H Amini, TM Hansen… - Authorea …, 2022 - authorea.com
Accounting for an accurate noise model is essential when dealing with real data which are
noisy due to the effect of environmental noise, failures and limitations in data acquisition and …