Minimum Miscibility Enrichment Research Articles

Microfluidic Studies on Minimum Miscibility Pressure for n-Decane and CO2

Oil production is a complex process that can be made more efficient by applying gas enhanced oil recovery (EOR) methods. Thus, it is essential to know the minimum miscibility pressure (MMP) and minimum miscibility enrichment (MME) of gas in oil. Conventional slim-tube experiments for the measurement of MMP require hundreds of millilitres of real or recombined oil and last over 30 days. Advances in microfluidic technology allow the reduction of the amount of fluid and the time required in determining MMP (or MME), hence making the process rapid. In this study, we developed a microfluidic model with a stochastically distributed pore network, porosity of 74.6% and volume of 83.26 nanolitres. Although the volume was six orders of magnitude smaller than the slim tube, it retained the same proportions, guaranteeing a proper comparison between the tests. This microfluidic chip allowed the study of the MMP of n-decane with carbon dioxide at two different temperature conditions. The experimental results coincided with the results received both from conventional and microfluidic experiments. Furthermore, a numerical simulation of a section of the microfluidic model under the experimental conditions presented results within acceptable margins of the experimental ones. The results of the presented methodology indicate the potential to replace conventional technology for the measurement of MMP with microfluidic technology. Its promise lies in accelerating laboratory tests and increasing the reliability of experimental results and, subsequently, the quality of field gas EOR operations.

Development of minimum tie line length method for determination of minimum miscible pressure in gas injection process

Gas injection process is a very important technology in enhanced oil recovery. Minimum miscible pressure is one of the key parameters in gas injection processes. Various experimental methods such as slim tube are used to measure MMP. These methods are costly and time consuming. Recently computational methods are used in order to achieve a cost-effective and reliable technique to evaluate MMP. In this work, a new methodology has been proposed for determination of MMP using the minimum tie line length method. A real mixing cell model was developed to estimate the MMP, MME and key tie lines. This method is simple, robust, and faster than conventional one-dimensional simulation of slim tube. The new mixing cells method can accurately determine the whole key tie lines to a shift, regardless of the number of injection gas and reservoir fluid components. Unlike other methods of mixing cells, this method automatically corrects dispersion by additional contacts to achieve the low variation domain of tie line slope. Also, the determination and implementation of the minimum miscibility enrichment are investigated.

Reservoir Screening for EOR Potential for the Western North Slope, Alaska

The Western North Slope of Alaska is an oil-rich zone located in the Colville river unit close to the Eastern boundary of National Petroleum Reserve Alaska. With an objective to find better enhanced oil recovery solutions and improve recoveries, four reservoirs from the Western North Slope were screened for different enhanced oil recovery methods to find the most suitable option. Based on the initial screening, gas injection was found to be the preferred method. This was followed by the determination of optimum injection gas compositions for Western North Slope reservoirs and their rank, thereby developing a new ranking methodology for gas flooding projects. The work was accomplished via a combination of two custom developed Excel spreadsheets for the determination of minimum miscibility pressure and enrichment respectively and several numerical experiments carried out using a compositional reservoir simulator, the results of which were applied for parametric ranking of the four Western North Slope reservoirs.

Effect of initial gas saturation on miscible gasflood recovery

Multi-contact miscible (MCM) displacements are designed to achieve piston-like flow and optimal recovery of in-situ hydrocarbons. The primary goal of this paper is to explore the ramifications of leading condensate or gas banks in MCM floods with two-phase initial conditions, a problem which has not been considered in detail in theoretical or experimental research. The consequences of two or more in situ phases may be significant for displacements in capillary transition zones, vertically-graded compositional reservoirs or gas condensate reservoirs. We develop method of characteristics (MOC) solutions for 1-D displacement of two-phase initial compositions by gases that are enriched below and above the minimum miscibility enrichment (MME). We consider ternary and quaternary systems to examine both condensing and condensing/vaporizing (C/V) mechanisms. In the MCM displacements considered, recoveries are dependent on relative permeability functions and can be adversely affected by two-phase initial reservoir fluids for injection times less than 1.0 pore volumes injected (PVI). The delay in heavy component recovery could significantly impact the economics of gas injection projects. Because flow is MCM, however, recovery increases rapidly to 100% at 1.0 PVI in all cases.

Improved Fluid Characterization for Miscible Gas Floods

Summary Equations of state (EOSs) are typically tuned to black-oil pressure/volume/temperature (PVT) data such as constant volume-depletion, constant-composition-expansion, differential-liberation, and separator tests. Other PVT data more appropriate for gas injection could include multicontact and swelling tests and slimtube tests. The standard method of tuning, however, does not typically incorporate important displacement parameters, such as the minimum miscibility pressure (MMP), minimum miscibility enrichment (MME), or the likely compositions that result in a reservoir from condensing-vaporizing (CV) displacements. This paper demonstrates an improved reservoir-fluid-characterization procedure for miscible gas floods that can represent the interaction of flow and phase behavior more accurately. We demonstrate the approach for two displacements, an 11-component CO2 flood and a 12-component enriched-gas flood. The method-of-characteristic (MOC) theory is used to determine the MME (or MMP) of both lumped and unlumped models. The results show that by tuning to the calculated MME/MMP, fewer pseudocomponents are required to characterize the fluid than with conventional tuning methods. For the cases studied, fluids lumped to as few as four or five pseudocomponents can provide a good match to the composition profiles and oil recoveries of the unlumped models.

Parametric Investigation of WAG Floods Above the MME

SummaryWater-alternating-gas floods (WAG) are commonly used to improve sweep efficiency in heterogeneous reservoirs. There has been little reported in the literature, however, on the effectiveness of WAG processes where the gas is enriched above the minimum miscibility enrichment composition (MME). This paper examines how to optimize WAG processes for enriched gasfloods above the MME, particularly as a primary recovery method. Compositional simulations of x-z cross-sections are used to quantify the effects of WAG parameters, numerical dispersion, level of enrichment, and heterogeneity on local displacement efficiency and sweep efficiency.The main conclusions of this research show that the richer the gas above the MME, the fewer the number of WAG cycles required for maximum oil recovery at a given WAG ratio. Another significant observation is that overenrichment above the MME improves recovery the most when the largest permeability layers are at the bottom of the reservoir. Continuous slug injection performs better than WAG when the largest permeability layers are at the bottom of the aquifer, richer gases are used, and the vertical to horizontal permeability ratio is small.

Rapid Flash Calculations for Compositional Simulation

Summary The computational time for conventional flash calculations increases significantly with the number of components, making it impractical for use in many fine-grid compositional simulations and other applications. Previous research to increase flash-calculation speed has been limited to those with zero binary interaction parameters (BIPs) or approximate methods based on an eigenvalue analysis of the binary interaction matrix. Practical flash calculations, however, nearly always have some nonzero BIPs. Further, the accuracy and speed of the eigenvalue methods varies depending on the choice and number of the dominant eigenvalues. This paper presents a new and simple method for significantly increasing the speed of flash calculations for any number of nonzero BIPs. The approach requires the solution of up to six reduced parameters regardless of fluid complexity or the number of components and is based on decomposing the BIPs into two parameters using a simple quadratic expression. The new approach is exact in that the equilibrium-phase compositions for the same BIPs are identical to those with the conventional flash calculation; no eigenvalue analysis is required. Further, the new approach eliminates the Rachford-Rice procedure (1952) and is more robust than the conventional flash-calculation procedure. We demonstrate the new approach for several example fluids and show that speedup by a factor of approximately 3 to 20 is obtained over conventional flash calculations, depending on the number of components. Introduction Gas injection into oil reservoirs results in complex interactions of flow with phase behavior that often are not modeled accurately by black-oil simulation. This is especially true for miscible or nearly miscible floods in which significant mass transfer occurs between the hydrocarbon phases. Such floods are best modeled by compositional simulation. A significant disadvantage of compositional simulation, however, is that it is much more computationally intensive than black-oil simulation. The primary reason for the increased computational time is the result of solving repeated flash calculations with cubic equations of state (EOS). Research has shown that EOS flash calculations can occupy 50 to 70% of total computational time in compositional simulations (Stenby and Wang 1993; Chang 1990). This is also true for other applications, such as multiphase flow in pipelines. The use of fewer pseudocomponents can reduce the flash computation time, but fewer components results in less accuracy (Hong 1982; Liu 2001; Egwuenu et al. 2005). This is especially true in multicontact miscible displacements, in which miscibility is developed by a combined condensing/vaporizing drive process (Zick 1986; Johns et al. 1993; Egwuenu et al. 2005). Fluid characterization by pseudocomponent models can be improved by tuning to the analytical minimum miscibility enrichment or minimum miscibility pressure (Johns et al. 1994), but those models still require significant computational time, even for fewer pseudocomponents. Another way to reduce computation time is to reduce the number of gridblocks. With coarse grids, however, numerical dispersion is large, which may cloud the results (Solano et al. 2001). Ideally, fine grids should be used that better match the level of dispersion found at the field scale. More recently, methods have been examined to find reduced parameters for flash calculations. Michelsen (1982a, 1982b, 1986) significantly increased flash-calculation speed by finding three reduced parameters, regardless of the number of components. His method, however, assumes zero BIPs, which is too restrictive for real fluid characterization. Michelsen also gave a practical method for stability calculations using the tangent plane distance (TPD) (Michelsen 1982b).

Simplified Method for Calculation of Minimum Miscibility Pressure or Enrichment

Summary Local displacement efficiency from gas injection is highly dependent on the minimum miscibility pressure (MMP) or minimum miscibility enrichment (MME). Analytical methods, which are inexpensive and quick to use, have been developed to estimate MMPs for complex fluid characterizations. Published methods,1–3 however, often require estimation of numerous parameters and little has been written with regard to method robustness. This paper presents a simplified and robust method for MMP or MME calculation. The approach relies on finding key crossover tie lines for a dispersion-free displacement using the method of characteristic theory (MOC). The new method, however, differs from published methods by significantly reducing the number of equations and unknown parameters, and by providing a fast and robust method that can avoid trivial and false solutions. We demonstrate the improvements by calculation of the MMP and MME for a variety of gas/oil systems and also give new analytical solutions for constant K-value systems that give insight into the nature of false solutions. The number of potential false solutions increases greatly with the number of components in the fluid characterization. Thus, any proposed method must ensure convergence to the physical MMP/MME.

Quantification of Displacement Mechanisms in Multicomponent Gasfloods

Summary Local displacement efficiency in gasfloods depends strongly on the minimum miscibility pressure (MMP) or minimum miscibility enrichment (MME). The values for these design parameters depend in turn on the displacement mechanisms: vaporizing, condensing, or a combination of the two known as a condensing/vaporizing (CV) drive. Characterization of the displacement mechanism, however, is currently limited to these broad categories, with little reference to the degree to which a CV displacement is condensing or vaporizing. This "discrete" classification approach can result in significant confusion in the interpretation and comparison of various miscible gasfloods. The focus of this paper, therefore, is to present a method to quantify in a continuous way the fraction of a multicomponent gasflood that is vaporizing or condensing as the pressure or gas enrichment is increased. The approach relies on finding key tie lines for a dispersionfree 1D displacement using method of characteristic theory (MOC). We quantify the displacement mechanism for any number of oil or gas components by calculating the displacement path lengths along ruled surfaces bounded by these key tie lines. We show how to determine the displacement mechanism along each of these ruled surfaces by the calculation and comparison of the key tie-line lengths. Several multicomponent fluid characterizations are considered, including a 12-component enriched-gasflood and a 13-component CO2 flood. The results show that as the pressure or enrichment is increased, condensation occurs at the expense of vaporization. We also show by numerical simulations that the sensitivity of the local displacement efficiency to dispersion depends on the condensing fraction of the displacement. We show that the trends in displacement efficiency sensitivity to dispersion oppose previously published results, which showed that vaporizing displacements are more sensitive to dispersion than condensing ones. The differing trends are likely the result of improper and discrete determination of the displacement mechanism.

Effect of Dispersion on Local Displacement Efficiency for Multicomponent Enriched-Gas Floods Above the Minimum Miscibility Enrichment

SummaryRecent research on four-component 1D displacements has shown that enriching the gas above the minimum miscibility enrichment (MME) can increase oil recovery substantially for certain systems. Research has shown further that the oil-recovery increase can be very sensitive to the level of dispersion at the enrichment chosen.The main focus of this paper is to extend the research on four-component systems to displacements of multicomponent oils and gases in which the recovery is affected by dispersion and enrichment. We consider here a 12-component oil displaced by solvents enriched above the MME. For this case, the increase in recovery (displacement efficiency) above the MME can be as large as 15% original oil in place (OOIP), depending on the level of mixing. The methodology outlined can be used as a screening tool to determine whether a significant benefit may exist and whether further 2D and 3D studies are warranted.A secondary focus of the paper is to examine in detail how dispersion affects recoveries and displacement mechanisms for the 4- and 12-component systems. We show that for the case of the four-component model, the displacement mechanism changes from a combined condensing/vaporizing (CV) displacement to a strictly condensing one as enrichment increases above the MME. We also show how to quantify the percentage of the CV displacement that is vaporizing or condensing by calculating the compositional distances between key tie lines identified from "dispersion-free" theory.

Impact of Reservoir Mixing on Recovery in Enriched-Gas Drives Above the Minimum Miscibility Enrichment

Summary Gas enrichment is an important variable used to optimize oil recovery in enriched-gas drives. For slimtube experiments, oil recoveries do not increase significantly with enrichments greater than the minimum miscibility enrichment (MME). For field projects, however, the optimum enrichment required to maximize recovery on a pattern scale may be different from the MME. The optimum enrichment is likely the result of greater mixing in reservoirs than in slimtubes. In addition, 2D effects, such as channeling, gravity tonguing, and crossflow, can impact the enrichment selected. Numerical simulation is often used to model the effect of physical mixing on oil recovery in miscible gasfloods. Unfortunately, numerical dispersion can cloud the interpretation of the results by artificially increasing the level of mixing in the reservoir. This paper investigates the interplay among various mixing mechanisms, enrichment levels, and numerical dispersion. The mixing mechanisms examined are mechanical dispersion, gravity crossflow, and viscous crossflow. The U. of Texas Compositional Simulator (UTCOMP) is used to evaluate the effect of these mechanisms on recovery for different grid refinements, reservoir heterogeneities, injection boundary conditions, relative permeabilities, and numerical weighting methods, including higher-order methods. The reservoir fluid used for all simulations is a 12-component oil displaced by gases enriched above the MME. The results show that for 1D enriched gasfloods, the recovery difference between displacements above the MME and those at or near the MME increases significantly with dispersion. The trend, however, is not monotonic and shows a maximum at a dispersivity of approximately 4 ft. The trend is independent of relative permeabilities and gas trapping for dispersivities of less than approximately 4 ft. For 2D enriched gasfloods with slug injection, the difference in recovery generally increases as dispersion and crossflow increase. The magnitude of the recovery differences is less than that observed for the 1D displacements. Recovery differences for 2D models are highly dependent on relative permeabilities and gas trapping. For water alternating gas (WAG) injection, the differences in recovery increase slightly as dispersion decreases. That is, the recovery difference is significantly greater with WAG at low levels of dispersion than with slug injection. For the cases examined, the magnitude of recovery difference varies from approximately 1 to 8% of the original oil in place (OOIP).

Characterization of heavy oils. 3. Prediction of gas injection behavior: swelling test, multicontact test, multiple-contact minimum miscibility pressure, and multiple-contact minimum miscibility enrichment

Characterization of heavy oils. 3. Prediction of gas injection behavior: swelling test, multicontact test, multiple-contact minimum miscibility pressure, and multiple-contact minimum miscibility enrichment

Characterization of Heavy Oils. 3. Prediction of Gas Injection Behavior: Swelling Test, Multicontact Test, Multiple-Contact Minimum Miscibility Pressure, and Multiple-Contact Minimum Miscibility Enrichment

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTCharacterization of Heavy Oils. 3. Prediction of Gas Injection Behavior: Swelling Test, Multicontact Test, Multiple-Contact Minimum Miscibility Pressure, and Multiple-Contact Minimum Miscibility EnrichmentJean-Noel Jaubert, Evelyne Neau, Laurent Avaullee, and Georges ZaborowskiCite this: Ind. Eng. Chem. Res. 1995, 34, 11, 4016–4032Publication Date (Print):November 1, 1995Publication History Published online1 May 2002Published inissue 1 November 1995https://doi.org/10.1021/ie00038a043RIGHTS & PERMISSIONSArticle Views250Altmetric-Citations22LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-Alerts Get e-Alerts

Effect of Phase Behavior on Bypassing in Enriched Gasfloods

Summary Enriched gasfloods incorporate a complex interaction of heterogeneity, fingering, multiphase flow, and phase behavior. Experiments and simulations indicate that the optimum solvent enrichment in high-viscosity-ratio secondary gasfloods can be below minimum miscibility enrichment (MME). The compositional path and resulting mobility profile in multidimensional multiple-contact miscible (MCM) or immiscible floods are different from their ID counterparts for high-viscosity-ratio floods in heterogeneous media.