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Because of the increasing global oil demand, efforts have been made to further extract oil using chemical enhanced oil recovery (CEOR) methods. However, unlike water flooding, understanding the physicochemical properties of crude oil and its sandstone reservoir makeup is the first step before embarking to CEOR projects. These properties play major roles in the area of EOR technologies and are important for the development of reliable chemical flooding agents; also, they are key parameters used to evaluate the economic and technical feasibilities of production and refining processes in the oil industries. Consequently, this paper aims to investigate various important physicochemical properties of crude oil (specific gravity; American Petroleum Institute [API]; viscosity; pour point; basic sediment and water; wax; and saturate, aromatic, resins and asphaltenes components) and sandstone reservoir makeup (porosity, permeability, bulk volume and density, grain volume and density, morphology and mineral composition and distributions) obtained from Malaysian oil field (MOF) for oil recovery prediction and design of promising chemical flooding agents.

Three reservoir sandstones from different depths (CORE 1; 5601, CORE 2; 6173 and CORE 3; 6182 ft) as well as its crude oil were obtained from the MOF, and various characterization instruments, such as high temperature gas chromatography and column chromatography for crude’s fractions identification; GC-simulated distillation for boiling point distribution; POROPERM for porosity and permeability; CT-Scan and scanning electron microscopy-energy dispersive X-ray for morphology and mineral distribution; wax instrument (wax content); pour point analyser (pour point); and visco-rheometre (viscosity), were used for the characterizations.

Experimental data gathered from this study show that the field contains low viscous (0.0018-0.014 Pa.s) sweet and light-typed crude because of low sulfur content (0.03 per cent), API gravity (43.1o), high proportion of volatile components (51.78 per cent) and insignificant traces of heavy components (0.02 per cent). Similarly, the rock permeability trend with depth was found in the order of CORE 1 < CORE 2 < CORE 3, and other parameters such as pore volume (Vp), bulk volume (Vb) and grain volume (Vg) also decrease in general. For grain density, the variation is small and insignificant, but for bulk density, CORE 2 records lower than CORE 3 by more than 1 per cent. In the mineral composition analysis, the CORE 2 contains the highest identified mineral content, with the exception of quarts where it was higher in the CORE 3. Thus, a good flow crude characteristic, permeability trend and the net mineral concentrations identified in this reservoir would not affect the economic viability of the CEOR method and predicts the validation of the MOF as a potential field that could respond to CEOR method successfully.

This paper is the first of its kind to combine the two important oil field properties to scientifically predict the evaluation of an oil field (MOF) as a step forward toward development of novel chemical flooding agents for application in EOR. Hence, information obtained from this paper would help in the development of reliable chemical flooding agents and designing of EOR methods.

Application of foam in enhanced oil recovery requires a production of foam that is strong and stable enough to withstand a long period. There are numerous factors that may affect the performance of foam, among which is temperature. Therefore, this study aims to observe the foam performance at different temperature by evaluating the foamability and the stability of the foam.

In this study, bulk foam test using FoamScan was conducted to examine the effect of temperature on foam in the presence of crude oil. Nitrogen gas was sparged through the mixture of crude oil, an in-house developed surfactant, and sodium chloride solution as the brine at different temperatures to produce foam at a certain height. The crude oil was extracted from an oilfield in East Malaysia and the in-house developed surfactant was a mixture of amphoteric and anionic surfactants. A camera continuously recorded the height of foam during the generation and the collapse of the foam. The foamability and foam stability properties of each sample were taken as the indicators for foam performance. Furthermore, the entering, spreading and bridging analysis was run to observe the effect of the presence of crude oil on foam performance.

In general, the higher the temperature, the less stable the foam is. As the stability of foam is associated with the rate of liquid drainage, it was observed that as temperature increases, the rate of liquid drainage also increases. On the other hand, the entering, spreading and bridging analysis shows that there is entering of oil droplet happening on the interface of foam film that may promote the rupture of the foam film even more.

It was found that the temperature has a small impact on foamability, whereas the foam stability was significantly affected by the temperature. Therefore, it can be concluded that foamability is not necessarily interrelated to foam stability, contradicting to the findings of few authors.

The analysis of enhanced oil recovery using surfactants is presented here. Surfactants lower the surface tension between oil and water and hence the capillary resistance to flow. The mathematical description of this problem requires modelling of multi‐phase flow in a porous medium. A pressure‐based formulation has been used in the present study. The governing partial differential equations have been solved by a finite difference method. Both Newtonian and non‐Newtonian (shear thinning) behaviour of oil are considered. Results clearly show an improvement in oil recovery in the presence of surfactants. A study of the ideal case where surface tension is reduced to zero shows that oil recovery can be very high.

Non‐Newtonian fluids are used in current oil recovery processes. These fluids do not satisfy the linear Darcy law for flow through porous media. To model the recovery processes, a generalization of Darcy's law is used. A numerical method, developed originally for salt and fresh groundwater flow, has been adapted to incorporate the generalized Darcy law. We use it to model the two‐phase, two‐dimensional flow of immiscible fluids in a porous medium. In particular it will be applied to investigate the stability of the fluid/fluid interface. The results verify the theoretically predicted critical velocity above which the displacement of oil by polymer flooding becomes unstable, leading to low recovery.

The purpose of this paper is to present detailed algorithms for simulation of individual and group control of production wells in hydrocarbon reservoirs which are implemented in a finite volume-based reservoir simulator.

The algorithm for individual control is described for the multi-lateral multi-connection ones based on the multi-segment model considering cross-flow. Moreover, a general group control algorithm is proposed which can be coupled with any well model that can handle a constraint and returns the flow rates. The performance of oil production process based on the group control criteria is investigated and compared for various cases.

The proposed algorithm for group control of production wells is a non-optimization iterative scheme converging within a few number of iterations. The numerical results of many computer runs indicate that the nominal power of the production wells, in general, is the best group control criterion for the proposed algorithm. The production well group control with a proper criterion can generally improve the oil recovery process at negligible computational costs when compared with individual control of production wells.

Although the group control algorithm is implemented for both production and injection wells in the developed simulator, the numerical algorithm is here described only for production wells to provide more details.

The proposed algorithm can be coupled with any well model providing the fluid flow rates and can be efficiently used for group control of production wells. In addition, the calculated flow rates of the production wells based on the group control algorithm can be used as candidate solutions for the optimizer in the simulation-optimization models. It may reduce the total number of iterations and consequently the computational cost of the simulation-optimization models for the well control problem.

A complete and detailed description of ingredients of an efficient well group control algorithm for the hydrocarbon reservoir is presented. Five group control criteria are extracted from the physical, geometrical and operating conditions of the wells/reservoir. These are the target rate, weighted potential, ultimate rate and introduced nominal power of the production wells. The performance of the group control of production wells with different group control criteria is compared in three different oil production scenarios from a black-oil and highly heterogeneous reservoir.

The aim of this study is to numerically simulate the density-driven convection in heterogeneous porous media associated with anisotropic permeability field, which is important to the safe and stable long term CO₂ storage in laminar saline aquifers.

The study uses compact finite difference and the pseudospectral method to solve Darcy’s law.

The presence of heterogeneous anisotropy may result in non-monotonic trend of the breakthrough time and quantity of CO₂ dissolved in the porous medium, which are important to the CO₂ underground storage.

The manuscript numerically study the convective phenomena of mixture contained CO₂ and brine. The phenomena are important to the process of CO₂ enhanced oil recovery. Interesting qualitative patterns and quantitative trends are revealed in the manuscript.

This paper seeks to present a novel computational intelligence technique to generate concise neural network models for distributed dynamic systems.

The approach used in this paper is based on artificial neural network architectures that incorporate linear and nonlinear principal component analysis, combined with generalized dimensional analysis.

Neural network principal component analysis coupled with generalized dimensional analysis reduces input variable space by about 90 percent in the modeling of oil reservoirs. Once trained, the computation time is negligible and orders of magnitude faster than any traditional discretisation schemes such as fine‐mesh finite difference.

Finding the minimum number of input independent variables needed to characterize a system helps in extracting general rules about its behavior, and allows for quick setting of design guidelines, and particularly when evaluating changes in the physical properties of systems.

The methodology can be used to simulate dynamical systems characterized by differential equations, in an interactive CAD and optimization providing faster on‐line solutions and speeding up design guidelines.

This paper aims to perform a comparative study between capabilities of two numerical schemes from two main branches of numerical methods for solving hyperbolic conservation equations.

The accuracy and performance of a newly developed high‐resolution central scheme vs a higher‐order Godunov‐based method are evaluated in the context of black‐oil reservoir simulations. Both methods are modified enabling study of applications that are not strictly hyperbolic and exhibit local linear degeneracies in their wave structure.

The numerical computations show that while both schemes produce results with virtually the same accuracy, the Godunov method reproduces slightly more accurate results at the expense of calculation of eigen‐structures.

The paper investigates only one dimensional problems, but the idea can be easily extended to multi‐dimensional problems.

The paper shows the strengths and weaknesses of two practical numerical methods.

Such comparative study has not been published elsewhere and in particular, the performance of numerical methods on simulating hysteresis effect in hydrocarbon reservoirs has not been investigated in detail before.

J. A. ROBERTSON addresses the Institute of Mechanical Engineers Tribology Group on the many‐sided health and safety risks arising from developments in modern industrial lubrication techniques.

The purpose of this work is to present a procedure for determining the wind drift factor through two-dimensional computational fluid dynamics (CFD) simulations of the wind acting on a wavy sea surface, such that the subjectivity of its estimation is reduced.

The wind drift factor was determined by two-dimensional CFD analyses with open-channel condition. The characteristic wave was determined by the Sverdrup–Munk–Bretschneider (SMB) method. The uncertainty analysis is based on convergence studies using a single parameter refinement (grid and time step).

This procedure allows the estimation of the wind drift factor in a fetch-limited domain. The domain's value in the analyzed region is 0.0519 ± 4.92% which is consistent with the upper values of the wind drift factors reported in the literature.

The use of a three-dimensional domain was impractical with the available computational resources because of the fine mesh required for wave modeling. The uncertainty analysis consisted only of a verification procedure. Validation against real data was not possible because of the lack of measured data in the analyzed region.

The wind drift factor is usually estimated based on either experience or random sampling. The original contribution of this work is the presentation of a CFD procedure for estimating the wind drift factor, in which the domain inlet is subjected to a wave boundary condition and to a wind velocity.