A chemical EOR benchmark study of different reservoir simulators

Goudarzi, Ali; Delshad, Mojdeh; Sepehrnoori, Kamy

doi:10.1016/j.cageo.2016.06.013

Cited by 56 publications

(34 citation statements)

References 21 publications

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“…[7] for example). Further, current models used for EOR either ignore the details of the microemulsion phase or use Hand's model [8] to describe microemulsion phase behavior [9]. In some cases, the Hand's coefficients are adjusted as a function of salinity, temperature, pressure, or oil composition (see Roshanfekr and Johns [4] for example).…”

Section: Introductionmentioning

confidence: 99%

“…This affinity, however, is a function of many parameters other than surfactant selection, including temperature, pressure, water composition, and oil composition. Winsor [9] defined the R-ratio to account for the overall effect of molecular forces at the interface on surfactant affinity. The R-ratio, however, is difficult to measure and calculate [13].…”

Section: Introductionmentioning

confidence: 99%

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Robust Flash Calculation Algorithm for Microemulsion Phase Behavior

Khorsandi

Johns

2016

J Surfact & Detergents

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The HLD‐NAC model was recently modified to match and predict microemulsion phase behavior experimental data for Winsor type III regions. Until now, the HLD‐NAC model could not generate realistic phase behavior for type II− and type II+ two‐phase regions, leading to significant saturation and composition discontinuities when catastrophe theory is applied. These discontinuities lead to significant failures in modeling surfactant applications. We modify the HLD‐NAC equations to ensure consistency over the entire composition space including type II− and II+ regions. A robust and efficient algorithm is developed that always converges and provides continuous estimates with any formation variable of tie lines and triangles for all Winsor types. Discontinuities are eliminated and limiting tie lines near critical points are determined analytically. The tuning procedure is demonstrated using several sets of experimental data. Excellent predictability of tie lines and tie triangles, and solubilization ratios are shown.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Flash Calculation Algorithm for Microemulsion Phase Behavior

Khorsandi

Johns

2016

J Surfact & Detergents

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“…Capillary pressure due to the co-existence of multiple phases is usually calculated by experimental means, such as the mercury injection, porous diagram method, centrifugal method, and dynamic capillary method [80]. These techniques require significant time and resources, which are not available for every project.…”

Section: Future Of Pore Network Modelsmentioning

confidence: 99%

Elementary Pore Network Models Based on Complex Analysis Methods (CAM): Fundamental Insights for Shale Field Development

Weijermars

Khanal

2019

Energies

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This paper presents insights on flow in porous media from a model tool based on complex analysis methods (CAM) that is grid-less and therefore can visualize fluid flow through pores at high resolution. Elementary pore network models were constructed to visualize flow and the corresponding dynamic bottomhole pressure (BHP) profiles in a well at reservoir outflow points. The pore networks provide the flow paths in shale for transferring hydrocarbons to the wellbore. For the base case model, we constructed a single flow path made up of an array of pores and throats of variable diameter. A passive ganglion (tracer) of an incompressible fluid was introduced to demonstrate the deformation of such ganglions when moving through the pores. The simplified micro-flow channel model was then expanded by stacking flow elements vertically and horizontally to create complex flow paths representing a small section of a porous reservoir. With these model elements in place, the flow transition from the porous reservoir fluid to the wellbore was modeled for typical stages in a well life. The dynamic component of the bottomhole pressure (BHP) was modeled not only during production but also during the drilling of a formation (with either balanced, underbalanced or overbalanced wellbore pressure). In a final set of simulations, the movement of an active ganglion (with surface tension) through the pore space was simulated by introducing a dipole element (which resisted deformation during the movement through the pores). Such movement is of special interest in shale, because of the possible delay in the onset of bubble point pressure due to capillarity. Capillary forces may delay the reservoir to reach the bubble point pressure, which postpones the pressure-drop trigger that would lead to an increase of the gas–oil ratio. The calculation of the estimated ultimate recovery (EUR) with an erroneous assumption of an early increase in the gas–oil ratio will result in a lower volume than when the bubble point delay is considered.

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“…The current industry is involved in the application of realistic chemical flood simulators like STARS by Computer Modelling Group (CMG), UTCHEM by the University of Texas at Austin (UT Austin), REVEAL by Petroleum Experts (Petex), and ECLIPSE by Schlumberger (SLB). The physics associated with fluid properties' evaluation differ in each type of reservoir simulator 17‐19 . UTCHEM is a compositional simulator capable of simulating different types of EOR processes owing to the provision of four different phases (gas, aqueous, oil, microemulsion) and incorporation of advanced numerical concepts 20 .…”

Section: Introductionmentioning

confidence: 99%

“…REVEAL, a full field reservoir expert, is similar to UTCHEM with surfactant phase behavior and mobility control options, permeability reduction, and polymer degradation parameters 21 . However, this tool is not well known among professionals and engineers in production areas and the existence of a fourth phase, that is, microemulsion may cause problems in field studies 17,20,21 . As per UTCHEM and REVEAL, the presence of a microemulsion phase is a key parameter to model displacement efficiency, in spite of the fact that microemulsion properties are not generally measured in pilot tests and field operations 18‐21 .…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of enhanced oil recovery studies for aqueous gemini surfactant‐polymer‐nanoparticle systems

Pal

2020

AIChE Journal

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The article investigates the efficacy of gemini surfactant/polymer/nanoparticle flooding on chemical EOR. Initially, physicochemical behavior of aqueous chemical fluids were investigated via interfacial tension reduction, wettability alteration, adsorption, viscosity moderation and oil displacement experiments. During compositional analysis, Cartesian model with specified grid properties, injection flow-rate, well pattern, and rock-fluid characteristics was developed using CMG-STARS tool. Contour map analyses showed that oil saturation decreased from~80% (initial) to 31.96%, 30.68%, and 29.30% after {14-6-14 GS + chase water}, {14-6-14 GS + PHPA + chase water}, and {14-6-14 GS + PHPA + SiO 2 chase water} flooding respectively. Tertiary recoveries of 15-19% were achieved, depending on injected fluid composition. Experimental data were history matched via CMOST tool to achieve good matching of simulated results. The CMG flooding simulator provides a holistic approach to investigate oil displacement profiles, assess flooding recovery capabilities with near-accuracy and predict the feasibility of proposed chemical EOR projects.

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A chemical EOR benchmark study of different reservoir simulators

Cited by 56 publications

References 21 publications

Robust Flash Calculation Algorithm for Microemulsion Phase Behavior

Robust Flash Calculation Algorithm for Microemulsion Phase Behavior

Elementary Pore Network Models Based on Complex Analysis Methods (CAM): Fundamental Insights for Shale Field Development

Numerical simulation of enhanced oil recovery studies for aqueous gemini surfactant‐polymer‐nanoparticle systems

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