Constructing an accurate geological model of the reservoir is a preliminary to make any reliable prediction of a reservoir’s performance. Afterward, one needs to simulate the flow to predict the reservoir’s dynamic behaviour. This process usually is associated with high computational costs. Therefore, alternative methods such as the percolation approach for rapid estimation of reservoir efficiency are quite desirable. This study tries to address the Well Testing (WT) interpretation of heterogeneous reservoirs, constructed from two extreme permeabilities, 0 andK. In particular, we simulated a drawdown test on typical site percolation mediums, occupied to fraction “p” at a constant rateQ/h, to compute the well-known pressure derivative (dP/dlnt). This derivative provides us with “apparent” permeability values, a significant property to move forward with flow prediction. It is good to mention that the hypothetical wellbore locates in the middle of the reservoir with assumed conditions. Commercial software utilized to perform flow simulations and well test analysis. Next, the pressure recorded against time at different realizations and values ofp. With that information provided, the permeability of the medium is obtained. Finally, the permeability change of this reservoir is compared to the permeability alteration of a homogeneous one and following that, its dependency on the model parameters has been analysed. The result shows a power-law relation between average permeability (considering all realizations) and the occupancy probability “p”. This conclusion helps to improve the analysis of well testing for heterogeneous reservoirs with percolation structures.

Capillarity refers to the phenomenon of fluids imbibing into fine pores or porous rocks and materials due to surface energy, through the action of capillary pressure. The capillary pressure causes the deformable interfaces formed between two phase fluids in contact with each other, such as a liquid and a vapor.

Studying bitumen has always posed a challenge to researchers owing to its extreme complexity and unique properties. To classify it commercially and to determine bitumen grade, two standard empirical tests have been adopted within the European standardized bitumen binders system [EN 12591:2009 (2009) Bitumen and bituminous binders – Specifications for paving grade bitumens]: Softening Point (SP) and Penetration (PEN). The relationship between these two tests and the physical or chemical properties of bitumen is not well understood. For the first time, this study represents an attempt to build more understanding of such a relationship through a comprehensive study of the correlation between the two standard tests and many physical and chemical properties of bitumen. A second goal is to propose some predictive models for these two tests and compare their predictive accuracy. Therefore, 13 Straight Run Vacuum Residues (SRVR) samples from different geographical origins were analyzed to measure the following parameters: Dynamic Viscosity (VisDy), Conradson Carbon Residue (CCR), C5 Asphaltenes Content (AspC5), C7 Asphaltenes Content (AspC7), Elemental Analysis (including C, H, O, N, S, Ni, and V content), Simulated Distillation (SD), Fourier-Transform Infrared Spectroscopy (FT-IR), and proton nuclear magnetic resonance spectroscopy (H-NMR). Results of studying correlations using correlation matrix and Principal Component Analysis (PCA) have emphasized the prominent effect of asphaltenes content on the other properties and the results of SP and PEN. It has also shown the potential importance of the aliphaticity/aromaticity of bitumen. Then, four models were proposed for the prediction of SP and PEN: viscosity, FT-IR, H-NMR, and multi-parameter models. Partial least squares (PLS) regression was used for building all models, except viscosity ones. All SP models, except H-NMR model, exhibited very good accuracy compared to the standard method. On the other hand, PEN was more difficult to predict than SP and only the multi-parameter model of PEN showed relatively good accuracy of prediction.

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Numerical simulation faces several challenges today. The different topics it relies on (scientific modelling, applied mathematics, High Performance Computing (HPC) and computer science) are continuously evolving, and not necessarily in compatible ways. The novelties emerging in the different fields involved in scientific computing, for instance graphics accelerators or manycore processors, programming languages, Domain Specific Languages (DSL; high level languages dedicated to an application domain), HPC libraries, mesh refinement, error estimates, high order numerical methods, ever finer models, . . . are often not so easy to combine.

Further improving the environmental performances of Internal Combustion Engines (ICE) increasingly requires moving beyond traditional multidimensional simulation tools based on a cycle averaged approach (Reynolds-Averaged Navier–Stokes, RANS), and to reliably predict and control individual engine cycles under realistic operating conditions. Large-Eddy Simulation (LES) offers this unique potential by predicting spatially filtered flow realizations, thus opening up new perspectives for extending the scope of application of Computational Fluid Dynamics (CFD) for ICE. Since its 1 edition in 2008, the LES4ICE conference provides a forum for exchange concerning research and development of LES and related experimental techniques for their application to ICE flows. It brings together researchers and engineers working in the field of piston engine combustion to debate the state of the art in LES applied to ICE and examine advanced experimental techniques capable of supporting and validating its development. The present special issue proposes an extract from the contributions to the 2014 edition of LES4ICE, following a selection by the conference’s Scientific Committee. The selected four articles provide a view on some recent advances in the domain of LES and related experimental techniques, and on their application to ICE flows. The study of Cyclic Combustion Variability (CCV) in Spark-Ignition Engines (SIE) has become a prominent topic for LES research in the past decade. It has been demonstrated how combining advanced optical diagnostics and state-of-the-art LES can allow identifying the causes of CCV, and that the acquired understanding could efficiently be capitalized in the form of reduced models for 1D CFD simulations of complete engine systems. This on-going research opened exciting perspectives for the application of LES to other yet poorly understood and mastered non-cyclic phenomena in SIE, as in particular the link between CCV and engine knock. A longstanding issue when studying the causes of CCV in SI engines is the relative importance of the variability of large-scale coherent structures, and of small scale turbulent fluctuations. A method aiming at addressing this question was proposed by S. Buhl, F. Hartmann and C. Hasse, in their contribution “Identification of Large-Scale Structure Fluctuations in IC Engines using POD-Based Conditional Averaging” [1]. They propose a method combining POD and conditional averaging, and discuss its application to the analysis of the origins of CCV for two different LES datasets. Oil & Gas Science and Technology – Rev. IFP Energies nouvelles (2016) 71, E1 C. Angelberger and C. Mounaim-Rousselle, published by IFP Energies nouvelles, 2016 DOI: 10.2516/ogst/2015048 IFP Energies nouvelles International Conference Rencontres Scientifiques d'IFP Energies nouvelles

\n\t\t\t\tIn this paper, a new method that predicts the pre-spud mud loss flow rate in formations with tectonic fractures of steeply folded structures is proposed. The new method is based on finite element analysis of the palaeo-tectonic and current tectonic stress field and fracture distribution. The steps of the method are as follows. First, palaeo-tectonic stress distribution is simulated through finite element analysis. The tectonic fracture distribution of the region is obtained by combining rock failure criteria with palaeo-tectonic stress distribution. Afterward, the tectonic fracture density, aperture, porosity and permeability are calculated by studying the rebuilding process of current stress to the fracture parameters. Finally, the mud loss flow rate is calculated according to fracture parameters and the basic data of a given well. The new method enables the prediction of the mud loss flow rate before drilling steeply folded structures.\n\t\t\t

L'automobile, autrefois considre comme un vecteur de croissance conomique et de progrs social, est depuis ces dernires dcennies galement juge du point de vue de ses impacts ngatifs, parmi lesquels : -la contribution la congestion des villes ; -la scurit, qui s'est nanmoins largement amliore, tant du point de vue de la scurit active que de la scurit passive ; -la consommation importante de ressources naturelles ; -l'mission de polluants, dornavant bien contrle ; -la production de gaz effet de serre, essentiellement sous forme de CO 2 , lie l'utilisation de produits ptroliers du fait de la large domination de l'essence. Les nombreuses activits de recherche et de dveloppement technologique apportent chaque jour des solutions et orientations pour faire face ces nombreux dfis. Ce numro spcial de OGST -Revue d'IFP Energies Nouvelles donne des exemples de ces travaux :