We present a discussion of the state-of-the-art on the use of discrete fracture networks
(DFNs) for modelling geometrical characteristics, geomechanical evolution and …

Aiming to find the most suitable development schemes of conventional and unconventional
reservoirs for maximum energy supply or economic benefits, reservoir production …

We analyze how artificial intelligence changes a significant part of the energy sector, the oil
and gas industry. We focus on the upstream segment as the most capital-intensive part of oil …

The spatially and temporally variable parameters and inputs to complex groundwater
models typically result in long runtimes which hinder comprehensive calibration, sensitivity …

In the last decade, ensemble-based methods have been widely investigated and applied for
data assimilation of flow problems associated with atmospheric physics and petroleum …

Numerical simulation of flow and transport in heterogeneous formations has long been
studied, especially for uncertainty quantification and risk assessment. The high …

Although researchers have applied many methods to history matching, such as Monte Carlo
methods, ensemble-based methods, and optimization algorithms, history matching fractured …

Over the last few decades, significant advances in using geophysical techniques to image
the structure of magma plumbing systems have enabled the identification of zones of melt …

Parameter identification is an essential step in constructing a groundwater model. The
process of recognizing model parameter values by conditioning on observed data of the …

Abstract The ensemble Kalman filter (EnKF) is a sequential data assimilation method that
has been demonstrated to be effective for history matching reservoir production data and …