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The second paper by Chen and Heidari uses pore-scale simulation to study measurements of electrical resistivity and dielectric permittivity. On the basis of the new understanding, the authors propose a new method that combines interpretation of these two measurements to improve assessment of hydrocarbon saturation and enable assembly of spatial distribution of rock components (pore, kerogen, and pyrite networks) in conventional models. Then, in the next paper, Argüelles-Vivas and Badadagli study gravity-driven steam-displacement of heavy oil inside a glass-bead sandpack model to explain the formation of residual oil saturation.

In the fourth paper, Riewchotisakul and Akkutlu use nonequilibrium molecular-dynamics simulations to study steady-state methane flow in carbon nanotubes. It is shown that these tubes contain an adsorbed phase that may significantly influence gas transport. Using a bundle-of-capillaries approach, the authors estimate a permeability increase of at least 50% for the organic micropores of Marcellus shale.

The fifth paper by Yassin et al. proposes new relative-permeability models for dual-wettability systems in unconventional rocks. In these systems, the oleic phase will act as the wetting phase in the hydrophobic pore network in the organic part of the system and the aqueous phase will act as a wetting phase in the hydrophilic pore network in the inorganic part.

In the last paper, Wang et al. investigate the effect of pore-size distribution on phase transitions during depressurization of a light oil and a retrograde gas confined inside nanoporous media.

The focus of the second paper is on generating geostatistical realizations of continuous variables such as porosity and permeability, water and oil saturation, and shale volumes within each geological facies. Here, Barnett et al. propose the use of a projection-pursuit multivariate transform method to improve the reproduction of multivariate properties existing between the continuous variables inside each facies.

The next two papers focus on various aspects of Monte Carlo methods for uncertainty quantification. The multilevel Monte Carlo method was recently introduced to reduce the computational costs associated with Monte Carlo simulations. Here, the idea is to perform simulations on a hierarchy of grids, so that parts of the sampling can be performed on coarser grids, where the solution of the forward flow problem is less costly. This gives rise to two errors, a sampling error and a discretization error. Müller et al. address how to balance these two errors and present a parallelization strategy. Then, the fourth paper, by Yu et al., discusses how to combine a Markov-chain Monte Carlo method with a fractional decline-curve model to improve uncertainty quantification in well-performance forecasts for shale-gas reservoirs.

The next two papers discuss multiscale simulation of in-situ conversion, a process in which tightly spaced electrical heaters are inserted into oil-shale resources to heat solid kerogen and turn it into recoverable hydrocarbons. To make simulations more computationally tractable, Li et al. introduce a dual-grid model in which thermal-reactive, compositional flow equations are solved on a coarse grid, using kinetic parameters and a heater-well model derived from fine-scale computations. Then, Alpak and Vink present an alternative adaptive, two-scale method in which a global coarse-scale model and multiple local fine-scale near-heater models are sequentially time stepped. The global model gives boundary conditions to the fine-scale models, which subsequently are upscaled to provide effective properties for the global equation. If necessary, this process is repeated iteratively.

The last two papers by Yoon et al. and Yang et al. discuss model-reduction methods. Here, the key idea is that although the dynamics of a multiphase simulation takes place in a high-dimensional vector space, it is possible to reproduce the essential features of the simulation by use of a reduced set of variables lying in a lower-dimensional vector space. The overall approach consists of an offline stage that computes representative solutions (snapshots), which are then reduced to a small-dimensional space, and an online stage, in which the reduced offline space is used to approximate the multiphase flow behavior for particular parameter combinations. Both papers use proper orthogonal decomposition (POD) to generate the offline space, but differ in the way they reduce the nonlinear part of the online system. Yoon et al. use a hyper-reduction procedure, whereas Yang et al. use discrete empirical interpolation (DEIM) combined with a generalized multiscale finite-element method for inexpensive computation of POD snapshots. By including velocity as an auxiliary variable, Yang et al. ensure that the POD-DEIM method is mass conservative.

The third paper by Le et al. proposes two automatic procedures for choosing the inflation factors to avoid ensemble collapse in the ensemble-smoother with multiple data assimilation (ES-MDA) method. The fourth paper by Lu and Chen explains how to use the exact analytical solution for pseudo-steady flow of a vertically fractured well to optimize the performance of the well by means of optimal fracture design.

The last paper by Sun et al. compares and contrasts various approaches to generate unstructured grids for modeling complex fracture networks arising around multiple horizontal wells. The authors present a new gridding and discretization workflow to handle nonorthogonal and low-angle intersections of clustered fractures with nonuniform apertures, and also discuss how to reduce the number of grid cells to give improved computational performance.

In the third paper, Johansen et al. extend the classical 1D Buckley-Leverett solution for constant flow rate to a system governed by constant inlet and outlet pressures. The fourth paper by Schmid et al. derives the analytic solution of capillary-controlled displacement in 1D using fractional-flow theory (i.e., thereby developing the capillary analogue of the classical Buckley-Leverett solution for viscous-dominated flow). The last paper by Yuan et al. applies the method of characteristics to develop semi-analytical solutions describing particulate flows in porous media. The authors then use these solutions to evaluate to what extent nanoparticles can be used to mitigate fines migration in porous media.

Recently, Amy Kan and Peter Valko retired from the editorial board. I hereby thank them for the service they have provided to SPE and the readers of the journal. Likewise, let me welcome our new Associate Editors: Cheng Chen (Virginia Tech), Kun Ma (Total), and Joachim Moortgat (Ohio State University). Last, but not least, I wish to thank all those who have contributed to write and review the 30 papers in this issue.

Knut-Andreas Lie, Executive Editor

SINTEF ICT / NTNU