Multiple-Mixing-Cell Method for MMP Calculations

SPE Journal ◽  
2011 ◽  
Vol 16 (04) ◽  
pp. 733-742 ◽  
Author(s):  
Kaveh Ahmadi ◽  
Russell T. Johns
Keyword(s):  
Analytical Methods ◽  
Oil And Gas ◽  
Equilibrium Phase ◽  
Variable Number ◽  
Simulation Methods ◽  
Displacement Efficiency ◽  
Fractional Flow ◽  
Cell Method ◽  
Multiple Mixing ◽  
Tie Lines

Summary The minimum miscibility pressure (MMP) is a key parameter governing the displacement efficiency of gasfloods. There are several methods to determine the MMP, but the most accurate methods are slim-tube experiments, analytical methods, and numerical-simulation/cell-to-cell methods. Slim-tube experiments are important to perform because they use actual crude oil, but they are costly and time consuming. Analytical methods that use the method of characteristics (MOC) are very fast and help to understand the structure of gasfloods. MOC, however, relies on finding the unique and correct set of key tie lines in the displacements, which can be difficult. Slim-tube simulation methods and their simplified cell-to-cell derivatives require tedious fluid and rock inputs, and their MMP estimates can be clouded by dispersion. This paper presents a simple and accurate multiple-mixing-cell method for MMP calculations that corrects for dispersion, and is faster and less cumbersome than 1D simulation methods. Unlike previous mixing-cell methods, our cell-to-cell mixing model uses a variable number of cells, and is independent of gas/oil ratio, volume of the cells, excess oil volumes, and the amount of gas injected. The new method only relies on robust P/T flash calculations using any cubic equation-of-state (EOS). The calculations begin with only two cells and perform additional cell-to-cell contacts between resulting equilibrium-phase compositions based on equilibrium gas moving ahead of the equilibrium liquid phase. We show for a variety of oil and gas compositions that all key tie lines can be found to the desired accuracy, and that they are nearly identical to those found using analytical MOC methods. Our approach, however, is more accurate and robust than those from MOC because we do not make approximations regarding shocks along nontie-line paths, and the unique set of key tie lines converges automatically. The MMP using our mixing-cell method can be calculated in minutes using an Excel spreadsheet and is estimated from a novel bisection method of the minimum tie-line lengths observed in the cells at four or five pressures. Our multiple-mixing-cell method can calculate either the MMP or the minimum miscibility for enrichment (MME) independent of the number of components in the gas or oil. Our approach further supports the notion that the MMP is independent of fractional flow because we obtain the same key tie lines independent of how much fluid is moved from one cell to another.

Multiple-Mixing-Cell Method for Three-Hydrocarbon-Phase Displacements

SPE Journal ◽  
2015 ◽  
Vol 20 (06) ◽  
pp. 1339-1349 ◽  
Author(s):  
Liwei Li ◽  
Saeid Khorsandi ◽  
Russell T. Johns ◽  
Kaveh Ahmadi
Keyword(s):  
Relative Permeability ◽  
Cell Model ◽  
Phase Identification ◽  
Displacement Efficiency ◽  
Compositional Simulation ◽  
Fractional Flow ◽  
Two Phase ◽  
Cell Method ◽  
Multiple Mixing ◽  
Three Phase

Summary Low-temperature oil displacements by carbon dioxide involve complex phase behavior, in which three hydrocarbon phases can coexist. Reliable design of miscible gasflooding requires knowledge of the minimum miscibility pressure (MMP), which is the pressure required for 100% recovery in the absence of dispersion or as defined by slimtube experiments as the “knee” in the recovery curve with pressure in which displacement efficiency is greater than 90%. There are currently no analytical methods to estimate the MMP for multicomponent mixtures exhibiting three hydrocarbon phases. Also, the use of compositional simulators to estimate MMP is not always reliable. These challenges include robustness issues of three-phase equilibrium calculations, inaccurate three-phase relative permeability models, and phase identification and labeling problems that can cause significant discontinuities and failures in the simulation results. How miscibility is developed, or not developed, for a three-phase displacement is not well-known. We developed a new three-phase multiple-mixing-cell method that gives a relatively easy and robust way to determine the pressure for miscibility or, more importantly, the pressure for high-displacement efficiency. The procedure that moves fluid from cell to cell is robust because it is independent of phase labeling (i.e., vapor or liquid), has a robust way to provide good initial guesses for three-phase flash calculations, and is also not dependent on three-phase relative permeability (fractional flow). These three aspects give the mixing-cell approach significant advantages over the use of compositional simulation to estimate MMP or to understand miscibility development. One can integrate the approach with previously developed two-phase multiple-mixing-cell models because it uses the tie-line lengths from the boundaries of tie triangles to recognize when the MMP or pressure for high-displacement efficiency is obtained. Application of the mixing-cell algorithm shows that, unlike most two-phase displacements, the dispersion-free MMP may not exist for three-phase displacements, but rather a pressure is reached in which the dispersion-free displacement efficiency is maximized. The authors believe that this is the first paper to examine a multiple-mixing-cell model in which two- and three-hydrocarbon phases occur and to calculate the MMP and/or pressure required for high displacement efficiency for such systems.

Application of Multiple-Mixing-Cell Method To Improve Speed and Robustness of Compositional Simulation

SPE Journal ◽  
2015 ◽  
Vol 20 (03) ◽  
pp. 565-578 ◽  
Author(s):  
Mohsen Rezaveisi ◽  
Russell T. Johns ◽  
Kamy Sepehrnoori
Keyword(s):  
Phase Equilibrium ◽  
Gas Injection ◽  
Computational Time ◽  
Simulation Methods ◽  
K Value ◽  
Acceptable Accuracy ◽  
Multiple Mixing ◽  
Tie Lines ◽  
Tie Line ◽  
Equilibrium Calculations

Summary Standard equation-of-state-based phase equilibrium modeling in reservoir simulators involves computationally intensive and time-consuming iterative calculations for stability analysis and flash calculations. Therefore, speeding up stability analysis and flash calculations and improving robustness of the calculations are of utmost importance in compositional reservoir simulation. Prior knowledge of the tie-lines traversed by the solution of a gas-injection problem translates into valuable information with significant implications for speed and robustness of reservoir simulators. The solution of actual-gas-injection processes follows a very complex route because of dispersion, pressure variations, and multidimensional flow. The multiple-mixing-cell (MMC) method, originally developed to calculate minimum miscibility pressure of a gas-injection process, accounts for various levels of mixing of the injected gas and initial oil. This observation suggests that the MMC tie-lines developed upon repeated contacts may represent a significant fraction of the actual simulation tie-lines encountered. We investigate this idea and use three tie-line-based K-value-simulation methods for application of MMC tie-lines in reservoir simulation. In two of the tie-line-based K-value-simulation methods, we examine tabulation and interpolation of MMC tie-lines in a framework similar to the compositional-space adaptive-tabulation (CSAT) method. In the third method, we perform K-value simulations based on inverse-distance interpolation of K-values from MMC tie-lines. We demonstrate that for the displacements examined, the MMC tie-lines are sufficiently close to the actual simulation tie-lines and provide excellent coverage of the simulation compositional route. The MMC-based methods are then compared with the computational time by use of other methods of phase-equilibrium calculations, including a modified application of CSAT (an adaptive tie-line-based K-value simulation), a method using only heuristic techniques, and the standard method in an implicit-pressure/explicit-concentration-type reservoir simulator. The results show that tabulation and interpolation of MMC tie-lines significantly improve phase equilibrium and computational time compared with the standard approach, with acceptable accuracy. The results also show that computational performance of the MMC-based methods with only prior tie-line tables is very close to that of CSAT, which requires flash calculations during simulation. The K-value simulations by use of MMC-based tie-line-interpolation methods improve the total computational time up to 51% in the cases studied, with acceptable accuracy. The results suggest that MMC tie-lines represent a significant fraction of the actual tie-lines during simulation and can be used to significantly improve speed and robustness of phase-equilibrium calculations in reservoir simulators.

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

2002 ◽  
Vol 5 (01) ◽  
pp. 4-10 ◽  
Author(s):  
R.T. Johns ◽  
P. Sah ◽  
R. Solano
Keyword(s):  
Oil Recovery ◽  
Analytical Solutions ◽  
Oil And Gas ◽  
Displacement Efficiency ◽  
Local Displacement ◽  
Highly Efficient ◽  
Free Theory ◽  
Component Systems ◽  
Tie Lines ◽  
Compositional Simulator

Summary Recent 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. Introduction The objective of enriched-gas floods is to achieve a multicontact miscible (MCM) displacement by a sufficient enrichment of the gas with intermediate components. If a near-MCM process occurs, then a highly efficient local displacement can be achieved. Because the local displacement efficiency is one of the primary factors that govern ultimate recovery, it is very important to quantify how mixing the oil and gas in reservoirs can adversely impact the efficiency of the MCM process. One of the key variables in enriched-gas floods, therefore, is the optimum enrichment for a highly efficient displacement. Slimtube experiments are often used to help determine the optimum enrichment. Because these experiments typically show that the oil-recovery increase beyond the MME is minimal, the optimum enrichment is often taken to be the MME. Other factors, such as the availability of solvents in the field and surface facility considerations, also can impact the choice of enrichment. Recent results by Johns et al.1 show that the slimtube results may be misleading because of the scaleup of dispersion from the laboratory to the field scale. Mixing by dispersion and other mechanisms is likely much greater in the field than the level of dispersion found in laboratory cores. Oil and gas mixing in a reservoir can be caused by mechanisms such as molecular diffusion, mechanical dispersion, gravity crossflow, viscous crossflow, and capillary crossflow.2 Several authors have examined the effect of mixing and enrichment above the MME on oil recovery. Johns et al.1 considered the effect of dispersion on recovery in 1D displacements. They showed that the "knee" in the recovery curve from slimtube experiments depends on the level of dispersion. For small dispersivities typical of slimtubes, the knee occurs at the MME. For greater levels of mixing, they showed that the knee could occur at enrichments much greater than the MME. Chang3 matched coreflood displacements with reservoir simulations at different enrichments. He showed that recovery increased sharply for enrichments above the MME. Chang concluded that the increased recoveries were caused by higher displacement and sweep efficiencies as the enrichment level increased. The better sweep efficiency was attributed to increased gas density with enrichment. Jerauld4 also observed an increase in recovery above the MME. Giraud et al.5 observed that the highest recovery occurred at pressures above the minimum miscibility pressure (MMP). Stalkup2 showed that significant additional recovery might be obtained by injecting enriched gases above the MME. A significant increase in recovery occurred for longitudinal dispersivities as low as 0.3 ft, when the solvent and water were injected in slugs. He also concluded that mixing of the solvent and the oil by viscous crossflow during water alternating gas (WAG) might dominate other mixing mechanisms in the reservoir (i.e., dispersion). Numerous other papers also have examined the effect of viscous crossflow, capillary pressure, diffusion, gravity, heterogeneities, and numerical grids on recovery.6–19 The main focus of this paper is to extend the work for four-component systems to displacements of a 12-component oil by solvents enriched above the MME. The effects of realistic levels of dispersive mixing on the displacement efficiency of the floods are examined. The slope in the recovery curves is used to quantify the effect of dispersion on the displacement efficiency. We also show how dispersion and enrichment affect the CV displacement mechanisms. The displacement mechanisms of the miscible process are quantified exactly for the first time using dispersion-free theory. We use numerical dispersion in this research to mimic physical dispersion. Analytical and Numerical Models The numerical solutions for 1D flow are calculated with the U. of Texas at Austin Compositional Simulator (UTCOMP), a compositional simulator that includes volume change on mixing.20 Analytical solutions to dispersion-free flow in one dimension are solved using hyperbolic conservation equations with the assumptions stated by Helfferich.21 The analytical solutions are used to find the MME and the key tie lines in the displacement.22–26

Microemulsion Phase Behavior Observations, Thermodynamic Essentials, Mathematical Simulation

1981 ◽  
Vol 21 (06) ◽  
pp. 747-762 ◽  
Author(s):  
Karl E. Bennett ◽  
Craig H.K. Phelps ◽  
H. Ted Davis ◽  
L.E. Scriven
Keyword(s):  
Experimental Data ◽  
Phase Behavior ◽  
Experimental Studies ◽  
Mathematical Framework ◽  
Alkyl Aryl Sulfonate ◽  
Phase Volume ◽  
Displacement Efficiency ◽  
Alkyl Aryl ◽  
Theoretical Understanding ◽  
Tie Lines

Abstract The phase behavior of microemulsions of brine, hydrocarbon, alcohol, and a pure alkyl aryl sulfonate-sodium 4-(1-heptylnonyl) benzenesulfonate (SHBS or Texas 1) was investigated as a function of the concentration of salt (NaCl, MgCl2, or CaCl2), the hydrocarbon (n-alkanes, octane to hexadecane), the alcohol (butyl and amyl isomers), the concentration of surfactant, and temperature. The phase behavior mimics that of similar systems with the commercial surfactant Witco TRS 10–80. The phase volumes follow published trends, though with exceptions.A mathematical framework is presented for modeling phase behavior in a manner consistent with the thermodynamically required critical tie lines and plait point progressions from the critical endpoints. Hand's scheme for modeling binodals and Pope and Nelson's approach to modeling the evolution of the surfactant-rich third phase are extended to satisfy these requirements.An examination of model-generated progressions of ternary phase diagrams enhances understanding of the experimental data and reveals correlations of relative phase volumes (volume uptakes) with location of the mixing point (overall composition) relative to the height of the three-phase region and the locations of the critical tie lines (critical endpoints and conjugate phases). The correlations account, on thermodynamic grounds, for cases in which the surfactant is present in more than one phase or the phase volumes change discontinuously, both cases being observed in the experimental study. Introduction The phase behavior of a surfactant-based micellar formulation is one of the major factors governing the displacement efficiency of any chemical flooding process employing that formulation. Knowledge of phase behavior is, thus, important for the interpretation of laboratory core floods, the design of flooding processes, and the evaluation of field tests. Phase behavior is connected intimately with other determinants of the flooding process, such as interfacial tension and viscosity. Since the number of equilibrium phases and their volumes and appearances are easier to measure and observe than phase compositions, viscosities, and interfacial tensions, there is great interest in understanding the phase-volume/phase-property relationships. Commercial surfactants, such as Witco TRS 10-80, are sulfonates of crude or partially refined oil. While they seem to be the most economically practicable surfactants for micellar flooding, their behavior, particularly with crude oils and reservoir brines, can be difficult to interpret, the phases varying with time and from batch to batch. Phase behavior studies with a small number of components, in conjunction with a theoretical understanding of phase behavior progressions, can aid in understanding more complex behavior. In particular, one can begin to appreciate which seemingly abnormal experimental observations (e.g., surfactant present in more than one phase or a discontinuity in phase volume trends) are merely features of certain regions of any phase diagram and which are peculiar to the specific crude oil or commercial surfactant used in the study.We report here experimental studies of the phase behavior of microemulsions of a pure sulfonate surfactant (Texas 1), a single normal alkane hydrocarbon, a simple brine, and a small amount of a suitable alcohol as cosurfactant or cosolvent. The controlled variables are hydrocarbon chain length, alcohol, salinity, salt type (NaCl, MgCl2, or CaCl2), surfactant purity, surfactant concentration, and temperature. Many of these experimental data were presented earlier. SPEJ P. 747^

scholarly journals Naphthenic Acids: Formation, Role in Emulsion Stability, and Recent Advances in Mass Spectrometry-Based Analytical Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Roselaine Facanali ◽  
Nathália de A. Porto ◽  
Juliana Crucello ◽  
Rogerio M. Carvalho ◽  
Boniek G. Vaz ◽  
...  
Keyword(s):  
Analytical Methods ◽  
Oil And Gas ◽  
Oil Quality ◽  
Economic Value ◽  
Oil And Gas Industry ◽  
Naphthenic Acids ◽  
Gas Industry ◽  
Oil In Water ◽  
Oil Emulsions ◽  
Modern Analytical

Naphthenic acids (NAs) are compounds naturally present in most petroleum sources comprised of complex mixtures with a highly variable composition depending on their origin. Their occurrence in crude oil can cause severe corrosion problems and catalysts deactivation, decreasing oil quality and consequently impacting its productivity and economic value. NAs structures also allow them to behave as surfactants, causing the formation and stabilization of emulsions. In face of the ongoing challenge of treatment of water-in-oil (W/O) or oil-in-water (O/W) emulsions in the oil and gas industry, it is important to understand how NAs act in emulsified systems and which acids are present in the interface. Considering that, this review describes the properties of NAs, their role in the formation and stability of oil emulsions, and the modern analytical methods used for the qualitative analysis of such acids.

scholarly journals Low-tension gas process in high-salinity and low-permeability reservoirs

2020 ◽  
Vol 17 (5) ◽  
pp. 1329-1344
Author(s):  
Alolika Das ◽  
Nhut Nguyen ◽  
Quoc P. Nguyen
Keyword(s):  
Oil Recovery ◽  
High Salinity ◽  
Oxidative Degradation ◽  
Qualitative Assessment ◽  
Low Permeability ◽  
Displacement Efficiency ◽  
Fractional Flow ◽  
Hydrocarbon Gases ◽  
Low Tension ◽  
Low Permeability Reservoirs

Abstract Polymer-based EOR methods in low-permeability reservoirs face injectivity issues and increased fracturing due to near wellbore plugging, as well as high-pressure gradients in these reservoirs. Polymer may cause pore blockage and undergo shear degradation and even oxidative degradation at high temperatures in the presence of very hard brine. Low-tension gas (LTG) flooding has the potential to be applied successfully for low-permeability carbonate reservoirs even in the presence of high formation brine salinity. In LTG flooding, the interfacial tension between oil and water is reduced to ultra-low values (10−3 dyne/cm) by injecting an optimized surfactant formulation to maximize mobilization of residual oil post-waterflood. Gas (nitrogen, hydrocarbon gases or CO2) is co-injected along with the surfactant slug to generate in situ foam which reduces the mobility ratio between the displaced (oil) and displacing phases, thus improving the displacement efficiency of the oil. In this work, the mechanism governing LTG flooding in low-permeability, high-salinity reservoirs was studied at a microscopic level using microemulsion properties and on a macroscopic scale by laboratory-scale coreflooding experiments. The main injection parameters studied were injected slug salinity and the interrelation between surfactant concentration and injected foam quality, and how they influence oil mobilization and displacement efficiency. Qualitative assessment of the results was performed by studying oil recovery, oil fractional flow, oil bank breakthrough and effluent salinity and pressure drop characteristics.

Analytical methods for mercury speciation, detection, and measurement in water, oil, and gas

2020 ◽  
Vol 132 ◽  
pp. 116016 ◽  
Author(s):  
Tawfik A. Saleh ◽  
Ganjar Fadillah ◽  
Endang Ciptawati ◽  
Mazen Khaled
Keyword(s):  
Analytical Methods ◽  
Oil And Gas ◽  
Mercury Speciation

Assessment of Non-Equilibrium Phase Behavior Model Parameters for Oil and Gas-Condensate Systems by Laboratory and Field Studies (Russian)

2020 ◽  
Author(s):  
Ilya Mikhailovich Indrupskiy ◽  
Mikhail Yurievich Danko ◽  
Timur Nikolaevich Tsagan-Mandzhiev ◽  
Ayguzel Ilshatovna Aglyamova
Keyword(s):  
Phase Behavior ◽  
Oil And Gas ◽  
Equilibrium Phase ◽  
Field Studies ◽  
Gas Condensate ◽  
Model Parameters ◽  
Behavior Model ◽  
Non Equilibrium

Variations of Gas/Condensate Relative Permeability With Production Rate at Near-Wellbore Conditions: A General Correlation

2006 ◽  
Vol 9 (06) ◽  
pp. 688-697 ◽  
Author(s):  
Mahmoud Jamiolahmady ◽  
Ali Danesh ◽  
D.H. Tehrani ◽  
Mehran Sohrabi
Keyword(s):  
Relative Permeability ◽  
Oil And Gas ◽  
Coupling Effect ◽  
Flow Behavior ◽  
Accurate Determination ◽  
Gas Condensate ◽  
Gas Oil ◽  
Fractional Flow ◽  
General Correlation ◽  
Fluid Saturation

Summary It has been demonstrated, first by this laboratory and subsequently by other researchers, that the gas and condensate relative permeability can increase significantly by increasing rate, contrary to the common understanding. There are now a number of correlations in the literature and commercial reservoir simulators accounting for the positive effect of coupling and the negative effect of inertia at near-wellbore conditions. The available functional forms estimate the two effects separately and include a number of parameters, which should be determined with measurements at high-velocity conditions. Measurements of gas/condensate relative permeability at simulated near-wellbore conditions are very demanding and expensive. Recent experimental findings in this laboratory indicate that measured gas/condensate relative permeability values on cores with different characteristics become more similar if expressed in terms of fractional flow instead of the commonly used saturation. This would lower the number of rock curves required in reservoir studies. Hence, we have used a large data bank of gas/condensate relative permeability measurements to develop a general correlation accounting for the combined effect of coupling and inertia as a function of fractional flow. The parameters of the new correlation are either universal, applicable to all types of rocks, or can be determined from commonly measured petrophysical data. The developed correlation has been evaluated by comparing its prediction with the gas/condensate relative permeability values measured at near-wellbore conditions on reservoir rocks not used in its development. The results are quite satisfactory, confirming that the correlation can provide reliable information on variations of relative permeability at near-wellbore conditions with no requirement for expensive measurements. Introduction The process of condensation around the wellbore in a gas/condensate reservoir, when the pressure falls below the dewpoint, creates a region in which both gas and condensate phases flow. The flow behavior in this region is controlled by the viscous, capillary, and inertial forces. This, along with the presence of condensate in all the pores, dictates a flow mechanism that is different from that of gas/oil and gas/condensate in the bulk of the reservoir (Danesh et al. 1989). Accurate determination of gas/condensate relative permeability (kr) values, which is very important in well-deliverability estimates, is a major challenge and requires an approach different from that for conventional gas/oil systems. It has been widely accepted that relative permeability (kr) values at low values of interfacial tension (IFT) are strong functions of IFT as well as fluid saturation (Bardon and Longeron 1980; Asar and Handy 1988; Haniff and Ali 1990; Munkerud 1995). Danesh et al. (1994) were first to report the improvement of the relative permeability of condensing systems owing to an increase in velocity as well as that caused by a reduction in IFT. This flow behavior, referred to as the positive coupling effect, was subsequently confirmed experimentally by other investigators (Henderson et al. 1995, 1996; Ali et al. 1997; Blom et al. 1997). Jamiolahmady et al. (2000) were first to study the positive coupling effect mechanistically capturing the competition of viscous and capillary forces at the pore level, where there is simultaneous flow of the two phases with intermittent opening and closure of the gas passage by condensate. Jamiolahmady et al. (2003) developed a steady-dynamic network model capturing this flow behavior and predicted some kr values, which were quantitatively comparable with the experimentally measured values.

Multiple Mixing Cell Method for Three-Hydrocarbon-Phase Displacements

2014 ◽  
Author(s):  
Liwei Li ◽  
Saeid Khorsandi ◽  
Russell T. Johns ◽  
Kaveh Ahmadi
Keyword(s):  
Cell Method ◽  
Multiple Mixing
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