scholarly journals Scaleup of Laboratory Data for Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

SPE Journal ◽  
2020 ◽  
Vol 25 (04) ◽  
pp. 1857-1870
Author(s):  
Rodrigo O. Salazar-Castillo ◽  
William R. Rossen
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Water Saturation ◽  
Gas Injection ◽  
Laboratory Data ◽  
Mobility Control ◽  
Model Parameters ◽  
Fractional Flow ◽  
Foam Model ◽  
Irreducible Water Saturation

Summary Foam increases sweep efficiency during gas injection in enhanced oil recovery processes. Surfactant alternating gas (SAG) is the preferred method to inject foam for both operational and injectivity reasons. Dynamic SAG corefloods are unreliable for direct scaleup to the field because of core-scale artifacts. In this study, we report fit and scaleup local-equilibrium (LE) data at very-low injected-liquid fractions in a Bentheimer core for different surfactant concentrations and total superficial velocities. We fit LE data to an implicit-texture foam model for scaleup to a dynamic foam process on the field scale using fractional-flow theory. We apply different parameter-fitting methods (least-squares fit to entire foam-quality scan and the method of Rossen and Boeije 2015) and compare their fits to data and predictions for scaleup. We also test the implications of complete foam collapse at irreducible water saturation for injectivity. Each set of data predicts a shock front with sufficient mobility control at the leading edge of the foam bank. Mobility control improves with increasing surfactant concentration. In every case, scaleup injectivity is much better than with coinjection of gas and liquid. The results also illustrate how the foam model without the constraint of foam collapse at irreducible water saturation (Namdar Zanganeh et al. 2014) can greatly underestimate injectivity for strong foams. For the first time, we examine how the method of fitting the parameters to coreflood data affects the resulting scaleup to field behavior. The method of Rossen and Boeije (2015) does not give a unique parameter fit, but the predicted mobility at the foam front is roughly the same in all cases. However, predicted injectivity does vary somewhat among the parameter fits. Gas injection in a SAG process depends especially on behavior at low injected-water fraction and whether foam collapses at the irreducible water saturation, which may not be apparent from a conventional scan of foam mobility as a function of gas fraction in the injected foam. In two of the five cases examined, this method of fitting the whole scan gives a poor fit for the shock in gas injection in SAG. We also test the sensitivity of the scaleup to the relative permeability krw(Sw) function assumed in the fit to data. There are many issues involved in scaleup of laboratory data to field performance: reservoir heterogeneity, gravity, interactions between foam and oil, and so on. This study addresses the best way to fit model parameters without oil for a given permeability, an essential first step in scaleup before considering these additional complications.

Foam Diversion in Heterogeneous Reservoirs: Effect of Permeability and Injection Method

SPE Journal ◽  
2017 ◽  
Vol 22 (05) ◽  
pp. 1402-1415 ◽  
Author(s):  
A. H. Al Ayesh ◽  
R.. Salazar ◽  
R.. Farajzadeh ◽  
S.. Vincent-Bonnieu ◽  
W. R. Rossen
Keyword(s):  
Oil Recovery ◽  
Water Saturation ◽  
Gas Injection ◽  
Surfactant Solution ◽  
Model Parameters ◽  
High Permeability ◽  
Fractional Flow ◽  
Injection Method ◽  
Heterogeneous Reservoirs ◽  
Irreducible Water Saturation

Summary Foam can divert flow from higher- to lower-permeability layers and thereby improve the injection profile in gas-injection enhanced oil recovery (EOR). This paper compares two methods of foam injection, surfactant-alternating-gas (SAG) and coinjection of gas and surfactant solution, in their abilities to improve injection profiles in heterogeneous reservoirs. We examine the effects of these two injection methods on diversion by use of fractional-flow modeling. The foam-model parameters for four sandstone formations ranging in permeability from 6 to 1,900 md presented by Kapetas et al. (2015) are used to represent a hypothetical reservoir containing four noncommunicating layers. Permeability affects both the mobility reduction of wet foam in the low-quality-foam regime and the limiting capillary pressure at which foam collapses. The effectiveness of diversion varies greatly with the injection method. In a SAG process, diversion of the first slug of gas depends on foam behavior at very-high foam quality. Mobility in the foam bank during gas injection depends on the nature of a shock front that bypasses most foam qualities usually studied in the laboratory. The foam with the lowest mobility at fixed foam quality does not necessarily give the lowest mobility in a SAG process. In particular, diversion in SAG depends on how and whether foam collapses at low water saturation; this property varies greatly among the foams reported by Kapetas et al. (2015). Moreover, diversion depends on the size of the surfactant slug received by each layer before gas injection. This favors diversion away from high-permeability layers that receive a large surfactant slug. However, there is an optimum surfactant-slug size: Too little surfactant and diversion from high-permeability layers is not effective, whereas with too much, mobility is reduced in low-permeability layers. For a SAG process, injectivity and diversion depend critically on whether foam collapses completely at irreducible water saturation. In addition, we show the diversion expected in a foam-injection process as a function of foam quality. The faster propagation of surfactant and foam in the higher-permeability layers aids in diversion, as expected. This depends on foam quality and non-Newtonian foam mobility and varies with injection time. Injectivity is extremely poor with foam injection for these extremely strong foams, but for some SAG foam processes with effective diversion it is better than injectivity in a waterflood.

Fitting Foam-Simulation-Model Parameters to Data: II. Surfactant-Alternating-Gas Foam Applications

2014 ◽  
Vol 18 (02) ◽  
pp. 273-283 ◽  
Author(s):  
W. R. Rossen ◽  
C. S. Boeije
Keyword(s):  
Steady State ◽  
Capillary Pressure ◽  
Oil Recovery ◽  
Water Saturation ◽  
Field Application ◽  
Model Parameters ◽  
Fractional Flow ◽  
Sweep Efficiency ◽  
Water Fraction ◽  
Foam Model

Summary Foam improves sweep in miscible and immiscible gas-injection enhanced-oil-recovery processes. Surfactant-alternating-gas (SAG) foam processes offer many advantages over coinjection of foam for both operational and sweep-efficiency reasons. The success of a foam SAG process depends on foam behavior at very low injected-water fraction (high foam quality). This means that fitting data to a typical scan of foam behavior as a function of foam quality can miss conditions essential to the success of an SAG process. The result can be inaccurate scaleup of results to field application. We illustrate how to fit foam-model parameters to steady-state foam data for application to injection of a gas slug in an SAG foam process. Dynamic SAG corefloods can be unreliable for several reasons. These include failure to reach local steady state (because of slow foam generation), the increased effect of dispersion at the core scale, and the capillary end effect. For current foam models, the behavior of foam in SAG depends on three parameters: the mobility of full-strength foam, the capillary pressure or water saturation at which foam collapses, and the parameter governing the abruptness of this collapse. We illustrate the fitting of these model parameters to coreflood data, and the challenges that can arise in the fitting process, with the published foam data of Persoff et al. (1991) and Ma et al. (2013). For illustration, we use the foam model in the widely used STARS (Cheng et al. 2000) simulator. Accurate water-saturation data are essential to making a reliable fit to the data. Model fits to a given experiment may result in inaccurate extrapolation to mobility at the wellbore and, therefore, inaccurate predicted injectivity: for instance, a model fit in which foam does not collapse even at extremely large capillary pressure at the wellbore. We show how the insights of fractional-flow theory can guide the model-fitting process and give quick estimates of foam-propagation rate, mobility, and injectivity at the field scale.

scholarly journals Fractional-Flow Theory for Non-Newtonian Surfactant-Alternating-Gas Foam Processes

2019 ◽  
Vol 131 (2) ◽  
pp. 399-426
Author(s):  
Rodrigo O. Salazar Castillo ◽  
Sterre F. Ter Haar ◽  
Christopher G. Ponners ◽  
Martijn Bos ◽  
William Rossen
Keyword(s):  
Shock Front ◽  
Gas Injection ◽  
Laboratory Data ◽  
Flow Theory ◽  
Shear Thinning ◽  
Grid Resolution ◽  
Mobility Control ◽  
Fractional Flow ◽  
Fractional Flow Theory ◽  
Newtonian Behavior

Abstract Foam can improve sweep efficiency in gas-injection-enhanced oil recovery. Surfactant-alternating-gas (SAG) is a favored method of foam injection. Laboratory data indicate that foam can be non-Newtonian at low water fractional flow fw, and therefore during gas injection in a SAG process. We investigate the implications of this finding for mobility control and injectivity, by extending fractional-flow theory to gas injection in a non-Newtonian SAG process in radial flow. We make most of the standard assumptions of fractional-flow theory (incompressible phases, one-dimensional displacement through a homogeneous reservoir, instantaneous attainment of local equilibrium), excluding Newtonian mobilities. For this initial study, we ignore the effect of changing or non-uniform oil saturation on foam. Non-Newtonian behavior at low fw implies that the limiting water saturation for foam stability varies as superficial velocity decreases with radial distance from the well. We discretize the domain radially and perform Buckley–Leverett analysis on each narrow increment in radius. Solution characteristics move outward with fixed fw. We base the foam model parameters and non-Newtonian behavior on laboratory data in the absence of oil. We compare results to mobility and injectivity determined by conventional simulation, where grid resolution is usually limited. For shear-thinning foam, mobility control improves as the foam front propagates from the well, but injectivity declines somewhat with time. This change in mobility ratio is not that at steady state at fixed water fractional flow in the laboratory, however, because the shock front in a non-Newtonian SAG process does not propagate at fixed fractional flow (though individual characteristics do). Moreover, the shock front is not governed by the conventional condition of tangency to the fractional-flow curve, though it continually approaches this condition. Injectivity benefits from the increased mobility of shear-thinning foam near the well. The foam front, which maintains a constant dimensionless velocity for Newtonian foam, decelerates somewhat with time for shear-thinning foam. For shear-thickening foam, mobility control deteriorates as the foam front advances, though injectivity improves somewhat with time. Overall, however, injectivity suffers from reduced foam mobility at high superficial velocity near the well. The foam front accelerates somewhat with time. Conventional simulators cannot adequately represent these effects, or estimate injectivity accurately, in the absence of extraordinarily fine grid resolution near the injection well.

Anomalous Foam-Fractional-Flow Solutions at High-Injection Foam Quality

2013 ◽  
Vol 16 (01) ◽  
pp. 40-50 ◽  
Author(s):  
A.. Roostapour ◽  
S.I.. I. Kam
Keyword(s):  
Oil Recovery ◽  
Water Saturation ◽  
Mobility Control ◽  
Injection Velocity ◽  
Fractional Flow ◽  
Improved Oil Recovery ◽  
High Injection ◽  
Constant State ◽  
Dry Conditions ◽  
First Time

Summary A thorough understanding of foam fundamentals is crucial to the optimal design of foams for improved oil recovery (IOR) or enhanced oil recovery (EOR). This study, for the first time, presents anomalous foam-fractional-flow solutions that deviate significantly from the conventional solutions at high-injection foam qualities by comparing method-of-characteristics and mechanistic bubble-population-balance simulations. The results from modeling and simulations derived from coreflood experiments revealed the following: The fraction of grinding energy contributed by the flowing gas (fg)There are three regions—Region A with relatively wet (or high fw) injection conditions in which the solutions are consistent with the conventional fractional-flow theory; Region C with very dry (or low fw) injection conditions in which the solutions deviate significantly; and Region B in between, which has a negative dfw/dSw slope showing physically unstable solutions.For dry-injection conditions in Region C, the solutions require a constant state (IJ) between initial (I) and injection (J) conditions, forcing a shock from I to IJ by intersecting fractional-flow curves, followed by spreading waves or another shock to reach from IJ to J.The location of IJ in fw vs. Sw domain moves to the left (or toward lower Sw) as the total injection velocity increases for both weak and strong foams until it reaches limiting water saturation. Even though foams at high-injection quality are popular for mobility control associating a minimum amount of surfactant solutions, foam behaviors at dry conditions have not been thoroughly investigated and understood. The outcome of this study is believed to be helpful to the successful planning of foam IOR/EOR field applications.

The Method of Characteristics Applied to Oil Displacement by Foam

SPE Journal ◽  
2010 ◽  
Vol 16 (01) ◽  
pp. 8-23 ◽  
Author(s):  
M.. Namdar Zanganeh ◽  
S.I.. I. Kam ◽  
T.C.. C. LaForce ◽  
W.R.. R. Rossen
Keyword(s):  
Capillary Pressure ◽  
Oil Recovery ◽  
Method Of Characteristics ◽  
Water Saturation ◽  
Gas Injection ◽  
Mobility Control ◽  
Residual Water ◽  
Injection Point ◽  
Oil Saturation ◽  
The Method Of Characteristics

Summary Solutions obtained by the method of characteristics (MOC) provide key insights into complex foam enhanced-oil-recovery (EOR) displacements and the simulators that represent them. Most applications of the MOC to foam have excluded oil. We extend the MOC to foam flow with oil, where foam is weakened or destroyed by oil saturations above a critical oil saturation and/or weakened or destroyed at low water saturations, as seen in experiments and represented in foam simulators. Simulators account for the effects of oil and capillary pressure on foam using algorithms that bring foam strength to zero as a function of oil or water saturation, respectively. Different simulators use different algorithms to accomplish this. We examine SAG (surfactant-alternating-gas) and continuous foam-flood (coinjection of gas and surfactant solution) processes in one dimension, using both the MOC and numerical simulation. We find that the way simulators express the negative effect of oil or water saturation on foam can have a large effect on the calculated nature of the displacement. For instance, for gas injection in a SAG process, if foam collapses at the injection point because of infinite capillary pressure, foam has almost no effect on the displacement in the cases examined here. On the other hand, if foam maintains finite strength at the injection point in the gas-injection cycle of a SAG process, displacement leads to implied success in several cases. However, successful mobility control is always possible with continuous foam flood if the initial oil saturation in the reservoir is below the critical oil saturation above which foam collapses. The resulting displacements can be complex. One may observe, for instance, foam propagation predicted at residual water saturation, with zero flow of water. In other cases, the displacement jumps in a shock past the entire range of conditions in which foam forms. We examine the sensitivity of the displacement to initial oil and water saturations in the reservoir, the foam quality, the functional forms used to express foam sensitivity to oil and water saturations, and linear and nonlinear relative permeability models.

scholarly journals Experimental investigation of the displacement flow mechanism and oil recovery in primary polymer flood operations

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Ruissein Mahon ◽  
Gbenga Oluyemi ◽  
Babs Oyeneyin ◽  
Yakubu Balogun
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
Polymer Flooding ◽  
Mobility Control ◽  
List Type ◽  
Motor Oil ◽  
Flow Mechanism ◽  
Fractional Flow ◽  
Recovery Method ◽  
Polymer Flood

Abstract Polymer flooding is a mature chemical enhanced oil recovery method employed in oilfields at pilot testing and field scales. Although results from these applications empirically demonstrate the higher displacement efficiency of polymer flooding over waterflooding operations, the fact remains that not all the oil will be recovered. Thus, continued research attention is needed to further understand the displacement flow mechanism of the immiscible process and the rock–fluid interaction propagated by the multiphase flow during polymer flooding operations. In this study, displacement sequence experiments were conducted to investigate the viscosifying effect of polymer solutions on oil recovery in sandpack systems. The history matching technique was employed to estimate relative permeability, fractional flow and saturation profile through the implementation of a Corey-type function. Experimental results showed that in the case of the motor oil being the displaced fluid, the XG 2500 ppm polymer achieved a 47.0% increase in oil recovery compared with the waterflood case, while the XG 1000 ppm polymer achieved a 38.6% increase in oil recovery compared with the waterflood case. Testing with the motor oil being the displaced fluid, the viscosity ratio was 136 for the waterflood case, 18 for the polymer flood case with XG 1000 ppm polymer and 9 for the polymer flood case with XG 2500 ppm polymer. Findings also revealed that for the waterflood cases, the porous media exhibited oil-wet characteristics, while the polymer flood cases demonstrated water-wet characteristics. This paper provides theoretical support for the application of polymer to improve oil recovery by providing insights into the mechanism behind oil displacement. Graphic abstract Highlights The difference in shape of relative permeability curves are indicative of the effect of mobility control of each polymer concentration. The water-oil systems exhibited oil-wet characteristics, while the polymer-oil systems demonstrated water-wet characteristics. A large contrast in displacing and displaced fluid viscosities led to viscous fingering and early water breakthrough.

Applicability of Enhanced Oil Recovery techniques on mature fields - Interest of gas injection

2005 ◽  
Author(s):  
Frederic Maubeuge ◽  
Danielle Christine Morel ◽  
Jean-Pierre Charles Fossey ◽  
Said Hunedi ◽  
Jacques Albert Danquigny
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Gas Injection ◽  
Recovery Techniques

Numerical Optimization of WAG Injection in a Sandstone Field using a Coupled Surface and Subsurface Model

2021 ◽  
Author(s):  
Thaer I. Ismail ◽  
Emad W. Al-Shalabi ◽  
Mahmoud Bedewi ◽  
Waleed AlAmeri
Keyword(s):  
Oil Recovery ◽  
Gas Injection ◽  
Coupled Model ◽  
Sensitivity Study ◽  
Mobility Control ◽  
Base Case ◽  
The North ◽  
Injection Process ◽  
Interaction Terms ◽  
Wag Injection

Abstract Gas injection is one of the most commonly used enhanced oil recovery (EOR) methods. However, there are multiple problems associated with gas injection including gravity override, viscous fingering, and channeling. These problems are due to an adverse mobility ratio and cause early breakthrough of the gas resulting, in poor recovery efficiency. A Water Alternating Gas (WAG) injection process is recommended to resolve these problems through better mobility control of gas, leading to better project economics. However, poor WAG design and lack of understanding of the different factors that control its performance might result in unfavorable oil recovery. Therefore, this study provides more insight into improving WAG oil recovery by optimizing different surface and subsurface WAG parameters using a coupled surface and subsurface simulator. Moreover, the work investigates the effects of hysteresis on WAG performance. This case study investigates a field named Volve, which is a decommissioned sandstone field in the North Sea. Experimental design of factors influencing WAG performance on this base case was studied. Sensitivity analysis was performed on different surface and subsurface WAG parameters including WAG ratio, time to start WAG, total gas slug size, cycle slug size, and tubing diameter. A full two-level factorial design was used for the sensitivity study. The significant parameters of interest were further optimized numerically to maximize oil recovery. The results showed that the total slug size is the most important parameter, followed by time to start WAG, and then cycle slug size. WAG ratio appeared in some of the interaction terms while tubing diameter effect was found to be negligible. The study also showed that phase hysteresis has little to no effect on oil recovery. Based on the optimization, it is recommended to perform waterflooding followed by tertiary WAG injection for maximizing oil recovery from the Volve field. Furthermore, miscible WAG injection resulted in an incremental oil recovery between 5 to 11% OOIP compared to conventional waterflooding. WAG optimization is case-dependent and hence, the findings of this study hold only for the studied case, but the workflow should be applicable to any reservoir. Unlike most previous work, this study investigates WAG optimization considering both surface and subsurface parameters using a coupled model.

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