Coupling Equation-of-State Compositional and Surfactant Models in a Fully Implicit Parallel Reservoir Simulator Using the Equivalent-Alkane-Carbon-Number Concept

Han, Choongyong; Delshad, Mojdeh; Pope, Gary A.; Sepehrnoori, Kamy

doi:10.2118/103194-pa

Cited by 19 publications

(10 citation statements)

References 12 publications

(16 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[1][2][3][4][5][6] Specifically, for surfactant-based enhanced oil recovery (EOR), significant release of the entrapped oil exhibits when there is a microemulsion generated between the surfactant injected and the trapped oil, concomitant with an ultra-low IFT value. [7][8][9][10] With proper design and advances in new surfactant chemistry in the last decade, new generation surfactant chemical flooding has provided much more cost attractive and provided strong economic incentive for site owners to explore it as a viable EOR alternative in recent years. [11][12][13][14] During laboratory screening phase, investigating solution phase behaviors of brine/oil/surfactant mixture is one of the key steps that could reveal the potential outcome of the recovery and the size of chemical slug required.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Crude Oil Equivalent Alkane Carbon Number (EACN) for Surfactant Flooding Design

Wan

Zhao

Harwell

et al. 2014

Journal of Dispersion Science and Technology

View full text Add to dashboard Cite

EACN of crude oil reflects the hydrophobicity of the crude oils, thus it would be helpful to estimate the EACN of crude oil before fine tuning the surfactant selection for enhanced oil recovery (EOR) field application. In this study, we used the titration methodology to quantify the EACN values for several crude oil samples retrieved from the targeted mature oil fields. The results showed the method of using extended surfactant was simpler but reliable to determine the EACN of crude oils. The resulting EACN for these crude oils was found to be in the range of 6.0-11.3.

show abstract

Section: Introductionmentioning

confidence: 99%

Characterization of Crude Oil Equivalent Alkane Carbon Number (EACN) for Surfactant Flooding Design

Wan

Zhao

Harwell

et al. 2014

Journal of Dispersion Science and Technology

View full text Add to dashboard Cite

show abstract

“…Surfactant flooding, whose key principle is to improve pore-level sweep efficiency by reducing the interfacial tension between injected Water and reservoir Oil 1 (Lake, 1989), recently received renewed attention due to the perspective of long-lasting high oil prices. Meaningful simulation of surfactant flooding is challenging, in particular because when the surfactant concentration in the Water phase goes above a Critical Micelle Concentration (CMC), Water and Oil become mutually soluble in a proportion mainly determined by water salinity C S .…”

Section: Introductionmentioning

confidence: 99%

“…Meaningful simulation of surfactant flooding is challenging, in particular because when the surfactant concentration in the Water phase goes above a Critical Micelle Concentration (CMC), Water and Oil become mutually soluble in a proportion mainly determined by water salinity C S . Three different phase environments should be considered Lake, 1989). Near the so-called optimal salinity C SOP the surfactant is similarly hydrophilic and lipophilic, and a middle phase called Microemulsion forms, containing the surfactant in excess of the CMC as well as dispersed oil and water (Winsor III environment).…”

Section: Introductionmentioning

confidence: 99%

“…Typical chemical recovery strategies consist in injecting a slug of surfactant-polymer solution at some appropriate salinity, followed by a chase polymer slug to improve macroscopic-level sweep efficiency by mobility control; this Enhanced Oil Recovery (EOR) method is usually referred to as Surfactant-Polymer (SP) flood (Lake, 1989). A more advanced recovery mechanism consists in co-injecting Alkali, whose properties are to generate in-situ surfactant by reaction with the acidic components of the Oil in place, as well as to limit surfactant adsorption on the pore walls (ASP flood).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Four-Fluid-Phase, Fully Implicit Simulation of Surfactant Flooding

2012

View full text Add to dashboard Cite

The Microemulsion phase behavior model based on oleic-aqueous-surfactant pseudo-phase equilibrium, commonly used in chemical flooding simulators, is coupled to Gas-Oil-Water phase equilibrium in our new four-fluid-phase, fully implicit In-House Research Reservoir Simulator (IHRRS). The method consists in splitting the equilibrium in two stages, where all the components other than surfactant are equilibrated first (e.g. using a black-oil, K-value or equation of state model), and the resulting Gas, Oil and Water phases are then lumped into pseudo-phases to be equilibrated using the Microemulsion model. This subdivision in stages is conceptual, and at each converged time-step the four phases (Gas, Oil, Water and Microemulsion, when simultaneously present) will be in equilibrium with each other.The fluid properties (such as densities, viscosities and interfacial tensions) and rock-fluid properties (such as relative permeabilities), required in the transport equations, are evaluated with models from well-known industrial or academic simulators. Surfactant flooding being usually implemented as a tertiary recovery mechanism, on fields for which complete models that we do not wish to modify already exist, particular care is devoted to ensuring continuity of the physics at the onset of surfactant injection.Our code is validated against a reference academic chemical flooding simulator, on 1D corefloods where the original hydrocarbons in place form a dead-Oil phase, possibly with free dry-Gas. Some numerical aspects of our implementation such as numerical dispersion versus time-step size and nonlinear convergence performance are also discussed. As an application example of our code where it is necessary to account for four phases in equilibrium, we consider a scenario where the chemical flood is preceded by a vaporizing Gas drive.

show abstract

“…The UTCHEM simulator (Delshad et al 1996) used a simple rational function of the trapping number (Jin 1995;Pennell et al 1996) to compute the residual saturation. Han et al (2007Han et al ( , 2009) developed implicit parallel reservoir simulators with surfactant flooding features. No mathematical model of MEOR has reported details of residual oil saturation reductions during the EOR processes or discussed how biogeochemical parameters can affect residual oil saturation distributions in heterogeneous porous media.…”

Section: Introductionmentioning

confidence: 99%

Impact of Rock Heterogeneity on Interactions of Microbial-Enhanced Oil Recovery Processes

Liu

Trefry

et al. 2011

Transp Porous Med

View full text Add to dashboard Cite

Residual oil saturation reduction and microbial plugging are two crucial factors in microbial-enhanced oil recovery (MEOR) processes. In our previous study, the residual saturation was defined as a nonlinear function of the trapping number, and an explicit relation between the residual oil saturation and the trapping number was incorporated into a fully coupled biological (B) and hydrological (H) finite element model. In this study, the BH model is extended to consider the impact of rock heterogeneity on microbial-enhanced oil recovery phenomena. Numerical simulations of core flooding experiments are performed to demonstrate the influences of different parameters controlling the onset of oil mobilization. X-ray CT core scans are used to construct numerical porosity-permeability distributions for input to the simulations. Results show clear fine-scale fingering processing, and that trapping phenomena have significant effects on residual oil saturation and oil recovery in heterogeneous porous media. Water contents and bacterial distributions for heterogeneous porous media are compared with those for homogenous porous media. The evolution of the trapping number distribution is directly simulated and visualized. It is shown that the oil recovery efficiency of EOR/MEOR will be lower in heterogeneous media than in homogeneous media, largely 123 374 J. Li et al. due to the difficulty in supplying surfactant to unswept low-permeability zones. However, MEOR also provides efficient plugging along high-permeability zones which acts to increase sweep efficiency in heterogeneous media. Thus, MEOR may potentially be more suited for highly heterogeneous media than conventional EOR.

show abstract

Coupling Equation-of-State Compositional and Surfactant Models in a Fully Implicit Parallel Reservoir Simulator Using the Equivalent-Alkane-Carbon-Number Concept

Cited by 19 publications

References 12 publications

Characterization of Crude Oil Equivalent Alkane Carbon Number (EACN) for Surfactant Flooding Design

Characterization of Crude Oil Equivalent Alkane Carbon Number (EACN) for Surfactant Flooding Design

Four-Fluid-Phase, Fully Implicit Simulation of Surfactant Flooding

Impact of Rock Heterogeneity on Interactions of Microbial-Enhanced Oil Recovery Processes

Contact Info

Product

Resources

About