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Cite This: Energy Fuels XXXX, XXX, XXX-XXX

Laboratory Investigation and Simulation Modeling of Polymer Flooding in High-Temperature, High-Salinity Carbonate Reservoirs Muhammad R. Hashmet,*,† Ali M. AlSumaiti,†,‡ Yemna Qaiser,† and Waleed S. AlAmeri† †

ADNOC Research and Innovation Center, The Petroleum Institute, Khalifa University of Science and Technology, P.O. Box 2533, Abu Dhabi, United Arab Emirates ‡ Abu Dhabi National Oil Company, Abu Dhabi, United Arab Emirates ABSTRACT: Polymer flooding is one of the most commonly employed improved oil-recovery techniques. However, its successful application is related to favorable reservoir conditions and geology. In addition, its application in high-temperature, high-salinity (HTHS) carbonate reservoirs is still a challenging task. A series of laboratory core-flood experiments have been performed at reservoir conditions (temperature of 120 °C and salinity of 167 g/L) on carbonate outcrop core samples to evaluate the flow behavior of polymer injection. A baseline with continuous polymer injection is established initially, and the experimental data are then historymatched to generate the relative permeability curves for the process using commercial software. Various parameters including reservoir permeability, polymer-slug size, polymer initiation time, and flow rate are varied to determine the optimum flooding conditions. All of the simulation results are then revalidated with the experimental results. Encouraging results are obtained at the optimum conditions despite the mechanical degradation of the polymer, which shows up to 85% recovery of the original oil in place with manageable polymer adsorption on the rock surface. It is also observed that the potential polymer can work effectively on the core samples having moderate (30 mD) to high-permeability samples; however, the polymer loses its efficiency in lower-permeability rock samples. The results also indicate that early polymer injection helps to reduce the polymer-slug size required to reach residual oil saturation. The optimum conditions for polymer-slug size and polymer initiation time is 0.1 pore volume after 0.3 pore volume of water injection, respectively. The smaller polymer-slug size also helped to manage the resistance factor and the residual resistance values in the desirable range, i.e., 1.9 and 1.1, respectively. Identifying a polymer that can withstand high-temperature and high-salinity conditions in carbonate reservoirs will be a major step toward broadening the scope of successful polymer-flooding applications.

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polymer is stable and effective under their reservoir conditions.8 Polymer’s viscosity is interestingly insensitive to temperature until 135 °C and brine salinity less than 186 g/L TDS. Additionally, the shear resistance test of this polymer showed that under 35 000 1/s shear rate for 5 min, the viscosity decreased less than 10%.8,9 The efficiency of polymer flooding is mainly influenced by formation type, salinity, reservoir temperature, permeability, and oil viscosity.7,10 The majority of polymer injection projects are executed in sandstone reservoirs due to more-favorable flooding conditions. However, the applications of polymer flooding in carbonate reservoirs are much less because of harsh reservoir conditions. Anionic polymers such as HPAM have high adsorption in carbonates and also typical Middle East carbonate reservoirs have high-temperature and high-salinity conditions.7 Moreover carbonates are usually heterogeneous with a low-permeability matrix, which makes it difficult for large-molecular-size polymers to enter formation.7 These conditions make polymer flooding significantly challenging. While in the reservoir, the injected polymer should remain intact for a long time to achieve a technically and economically successful polymer flood project, but the traditional polymers, such as HPAM and xanthan, degrade or precipitate at high-temperature and high-salinity conditions.11 Previous studies have indicated

INTRODUCTION Polymer flooding is an improved oil recovery (IOR) method in which polymer is dissolved in injected water to increase its viscosity thus decreasing the viscosity contrast between oil and water.1 The increase in viscosity of displacing fluid improves the mobility ratio resulting in better sweep efficiency.2 The mobility ratio affects the fractional flow of water and the total amount of injected water consumption.3 Hence, reducing the mobility ratio increases both macroscopic and microscopic oil displacement efficiency, which will reduce the displacing volume required to reach residual oil saturation. Moreover, the reduced water-injection requirement in polymer flooding compared to water flooding may also have an economic impact, especially in Middle East carbonate reservoirs.4,5 Partially hydrolyzed polyacrylamide (HPAM) and its derivatives are commonly used for polymer flooding projects.6 However, HPAM losses its viscosity under harsh reservoir conditions, high temperature and high salinity (HT-HS). Biopolymers are another type of polymer used in chemical EOR projects. Considerable research has been done on biopolymers in the 1970s and 1980s. However, there are limited industrial applications of biopolymers so far. Xanthan is one of the most widely used biopolymer for harsh reservoir conditions.7 However, the application of xanthan is not as popular as HPAM because of its poor injectivity and biodegradation. Schizophyllan is another biopolymer that appears to be compatible with high temperature, salinity, and shear rate. It has been used on the Bockstedt oil field in the North Sea. Field data showed that the schizophyllan © XXXX American Chemical Society

Received: September 11, 2017 Revised: October 30, 2017 Published: October 31, 2017 A

DOI: 10.1021/acs.energyfuels.7b02704 Energy Fuels XXXX, XXX, XXX−XXX

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Figure 1. Viscosity vs shear rate for an aging period of up to 232 days at 120 °C.

that the unavailability of a suitable polymer is primary reason to favor the alternative enhanced oil recovery (EOR) methods over polymer flooding for reservoirs that are most-suited for polymer EOR.12,13 In our previous papers,9,14 we have conducted a series of rheological tests on a biopolymer to investigate effects of polymer concentration, temperature, brine salinity, and shear rate. The results of the static rheology experiments have identified that the selected biopolymer, schizophyllan, is a thermally stable, salt-tolerant polymer with reasonable thickening efficiency and acceptable adsorption on reservoir formation in HTHS carbonate oil reservoirs. It has been observed that under anaerobic conditions, schizophyllan shows good thermal stability and retains its viscosity at 120 °C, as shown in Figures 1 and 2.

Figure 2. Viscosity vs aging time with varying shear rates at 120 °C.

Figure 3. Scanned image of carbonate outcrop core showing heterogeneity along the core and vugs. The color variation represents CT number. The lower the CT number, the smaller the density.

In this study, we conducted a series of a polymer core-flood experiments using schizophyllan to determine the flow behavior of injected polymer in carbonate core samples at high temperature (120 °C) and high salinity (167 g/L). The carbonate core samples are assumed to be homogeneous and characterized by a single value of porosity and permeability; however, the CT scan image as shown in Figure 3 depicts that there is considerable variation in pore sizes and pore distribution along the core. The heterogeneous nature of carbonates along with vugs has been taken into account in the core-flood experiments; however, fractures are not considered as they are beyond the scope of our study and are not significant in our targeted reservoir. At first, a baseline with continuous polymer injection is established. A simulation model is then developed and calibrated to

match the core-flood experiment results. The tuned model is then used to assess the sensitivity of oil recovery to reservoir permeability, polymer-slug size, polymer initiation time and flow rate and determine the optimum scenario of polymer injection. A series of core-flood experiments are then performed for some of the simulated cases to revalidate the results. The baseline experiment was conducted at 25 °C, but the subsequent core-flood experiments were performed at 120 °C. Figure 4 presents the sequence of work followed. The notion behind this work is to study the behavior of injected polymer in carbonate-core samples at high temperature and high salinity and, furthermore, to evaluate different parameters prior to core-flood experiments and therefore reduce the experiment B


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Wintershall. Polymer solution is prepared by mixing synthetic formation brine of 167 g/L and polymer concentrate. Synthetic brine is stirred using a laboratory driven magnetic stirrer for 15 min, with the vortex extending about three-quarters into the solution. Biopolymer is then added onto the shoulder of the vortex to avoid agglomeration of biopolymer, and the beaker is covered with an aluminum foil to avoid evaporation. The solution is stirred at a low speed for minimum 2−3 h to obtain homogeneous polymer solution as per the API Recommended Practice 63.9,14 Once polymer solutions are prepared, filtration test is performed to ensure that the polymer solution is homogeneous and free of any aggregates for all solutions.15 All polymer solutions are filtered using 0.45 μm filter paper, and filtration ratios calculated to be 1.2 or less are the only ones used. Standard carbonate outcrop core samples are used for the experiments. Core samples of 1.5 in. in diameter and 12 in. in length are cut and trimmed into desired dimensions and prepared for the experiments. Table 2 presents the petrophysical properties of core samples used in the experiments. The core preparation includes core cleaning, drying, and measuring their petro physical properties (dry-weight, porosity, permeability, and saturated weight). The cores are cleaned in a Soxhlet distillation− extraction unit to extract the impurity and salt content before measuring the petro physical properties. Porosity is measured using a digital gas porosimeter. The cores are saturated using a pressurized saturator until the cores are saturated to 100%.

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CORE-FLOOD EXPERIMENTS A set of polymer core-flood experiments was designed to evaluate the performance of schizophyllan under high-temperature and high-salinity conditions. The first experiment was conducted at a temperature of 25 °C to establish a baseline, and the subsequent experiments for optimization were conducted at 120 °C. A schematic of core-flood apparatus is shown in Figure 5. The major components includes core holder, fluid accumulators for oil, brine and polymer solutions, a back-pressure regulator, a digitally control oven, and pumps for liquid injection, overburden pressure, and back-pressure application. Pressure transducers of varying ranges were connected to the core at inlet, outlet, and differential pressures. A computer was connected to control core-flooding process and record the pressure, temperature, and flow-rate data. A core-flood experiment mainly consists of five phases in the sequence of water flooding, oil flooding, water flooding pre-flush, polymer flooding, and water flooding post-flush. The sequence and objective of each stage is shown in Figure 6. Formation brine of TDS 167 g/L was injected into core samples at three different flow rates to determine the absolute brine permeability of core sample. For each rate, fluid was injected until steady-state conditions were achieved and differential pressure was stabilized across the core sample. Darcy’s law presented in eq 1 was used to calculate brine absolute permeability:16

Figure 4. Sequence of work.

run time to reach the optimized polymer flooding scenario applicable in the high-temperature, high-salinity carbonate reservoirs.

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MATERIALS AND PREPARATION

The raw materials used in this study include electrolytes, deionized water, crude oil, biopolymer, and core samples. Formation brine is prepared by dissolving required amount of electrolytes in deionized water. The electrolytes include NaCl, KCl, NaHCO3, CaCl2·2H2O, and MgCl2·6H2O salts. The prepared brine has TDS of 167 g/L with density and viscosity of 1.09 g/cm3 and 1.25 cP, respectively, at room temperature. Table 1 enlists the constitution of brine used in this

Table 1. Constituents of Brine constituent

mass (g/L)

NaCl KCl CaCl2 MgCl2 NaHCO3

134.675 1.427 25.640 5.570 1.524

kabs =

14 700q (μL) AΔP

(1)

where q indicates injection rate. After measurement of the absolute permeability, crude oil was injected to displace formation brine until initial water saturation was reached. The injection was continued until water production became negligible and steady-state conditions were accomplished. The core was then aged for two months to allow for any wettability alterations. After aging, oil was injected again, and water production was recorded to recalculate Swi. This imitates the drainage process that takes place in the reservoir. The relative permeability of oil at Swi was calculated using Darcy’s law,

study. The dead oil used in the experiment has a density and viscosity of 0.834 g/cm3 and 5.229 cP, respectively, at ambient conditions. Oil is filtered through 0.45 μm filter paper to remove impurities and asphaltene contents. A water-soluble homoglucan biopolymer, schizophyllan is used in this study and has an average molecular weight of 2 to 3 million Daltons (2000 kg/mol).8 The polymer samples are provided by C


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Energy & Fuels Table 2. Petro Physical Properties of Core Samples length (cm) diameter (cm) porosity (%) pore volume (mL) absolute permeability (mD)

base case

experiment 1

experiment 2

experiment 3

experiment 4

7.208 3.810 13.12 10.35 30.5

7.356 3.810 25.60 21.56 2.8

7.270 3.810 17.26 14.31 126

7.177 3.810 31.00 25.14 43.6

7.776 3.810 16.67 13.31 444

Figure 5. Schematic of the core-flood apparatus.

After the pre-flush described above, a polymer slug of 200 ppm prepared in brine salinity of 167 g/L was injected in the core at a rate of 0.2 cc/min at 25 °C and 3500 psi. The effluents were collected to measure the oil recovered during polymer flooding. The resistance factor and relative permeability of polymer were calculated at steady-state conditions. The resistance factor (RF) is defined as the ratio of differential pressures recorded during polymer flood and water flood.17 Mathematically, RF is expressed as:

RF =

ΔPp ΔPw

After the polymer injection described above, formation brine was reinjected to evaluate polymer adsorption and permeability reduction due to polymer flooding. The change in formation permeability can be quantified by residual resistance factor (RRF). RRF can be calculated as shown in eq 6:18

Figure 6. Polymer core-flood procedure.

and initial saturations were calculated as follows: V Soi = w × 100% PV and

Swi = 1 − Soi

RRF = (2)

Vp V

× 100%

kafter polymer flooding k before polymer flooding

=

ΔPafter polymer flooding ΔPbefore polymer flooding

(6)

The core-flood experiment for the base case showed encouraging results and additional oil recovery was achieved after polymer flooding. The initial water saturation (Swi) for base case experiment was 30.43%, and the relative permeability of oil at Swi is 0.447. The oil recovery of the water flooding preflush was found to be 63.88%. The end-point water relative permeability of water at Sor after pre-flush was 0.123. The water and oil saturations after the water flooding (pre-flush) were 74.88% and 25.12%, respectively. To improve the mobility ratio, the polymer slug was injected for 7 PV followed by 6 PV of post-flush brine. The movable oil recovery by polymer is 6.94%. The oil recovery curve and differential pressure data are presented in Figure 7.

(3)

After aging and Swi was reached, brine was injected into core samples with a flow rate of 0.2 cc/min at 25 °C and 3500 psi. In this study, formation brine was used as the injected brine, which had a salinity of 167 g/L. The relatively permeability of water was calculated at steady-state conditions. The oil recovery factor (RFw) from water flooding was calculated using eq 4, given by: RFw =

(5)

(4) D


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Figure 7. Base case experimental result: oil recovery factor and differential pressure.

The RF and RRF are calculated to be 7.14 and 3.90 using eqs 5 and 6, respectively. Mobility at each stage was calculated to evaluate the polymer effectiveness. The brine mobility during the water flooding pre-flush was 6.19 mD/cp. The mobility of polymer was 0.26 mD/cp, while the mobility of brine during post-flush was 0.47 mD/cp. Results indicated that the polymer was effective under high salinity and that the mobility of displacing fluid during polymer flooding was reduced. Table 3 summarizes the results of the experiment.

Table 4. Initial Input Parameters reservoir properties porosity (%) permeability (mD) initial water saturation (%) fluid properties water density (g/cm3) viscosity (cP)

Table 3. Base-Case Experiment Results parameters

value

polymer mobility at 0.2 cc/min (mD/cP) postpolymer brine mobility at 0.2 cc/min (mD/cP) resistance factor at 0.2 cc/min residual resistance factor at 0.2 cc/min water end-point relative permeability oil end-point relative permeability water flooding oil recovery (%) overall oil recovery (%)

0.26 0.47 7.14 3.90 0.123 0.447 63.9 70.8

13.12 30.5 30.43 oil

polymer

1.09 0.834 1.25 5.23 polymer properties

polymer resistance factor polymer half life (days) polymer adsorption (mg/100 g rock)

1.09 10.6 3.90 232 0.7

Table 5. Injection Scheme of Base-Case Experiment water flooding pre-flush polymer flooding water flooding post-flush

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injection fluid

slug size (PV)

water polymer water

3 7 6

whole relative permeability curves are generated. The relative permeability curves are presented in Figure 8:

SIMULATION MODEL AND PROCESS A Cartesian grid model was developed using the CMG STARS module.19 The model was 7.2 cm long and had been discretized into 20 × 1 × 1 grid blocks. The dimensions of grids were chosen to represent the size of core sample. Injector and producer wells were placed on each corner of the model. The initial input parameters including reservoir properties, fluid properties, and polymer properties used in the model are shown in Table 4. The polymer properties were obtained from our previous publications.9,14 To replicate the base experiment, the injection scheme was followed according to the experiment. Pre-flush water flooding was carried out until the water cut was 99% and oil production reached a plateau. Polymer flooding was then initiated and followed with water flooding post-flush. The injection rate for all three injection stages was fixed at 0.2 cc/min. The injection scheme is presented in Table 5.

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k rw = k rwiro × ((Sw − Swcrit)/(1 − Swcrit − Soirw ))Nw

(7)

k ro = k rocw × ((So − Sorw)/(1 − Swcon − Sorw ))Now

(8)

MODEL CALIBRATION AND HISTORY MATCHING A number of simulation runs were performed to calibrate the initial chemical flooding model. The model was tuned to history-match production data measured during core-flood experiments. The match was obtained by adopting different sets of history matching parameters, including relative permeability exponents and polymer reaction rate. A reasonable match was obtained by using the parameters listed in Table 6. The polymer degradation was incorporated into the model by defining a reaction. It described the mechanical degradation of polymer inside the core sample rather than chemical reaction, and it is an adjustable parameter for history matching. The degraded polymer was assumed to be water to describe the degradation process. The reactant stoichiometry A and product stoichiometry B were balanced according to material balance and are shown in the following correlation. The coefficients A and B

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RELATIVE PERMEABILITY MODEL The saturation end points and corresponding relative permeabilities were obtained from the experiment. Using the end points and Corey correlations presented in eqs 7 and 8, the E


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PERMEABILITY The effect of permeability on oil recovery from both water and polymer is significant. The oil recovery increases with increase in permeability. In low-permeability core samples, the pore throat size is smaller, giving higher resistance to trapped oil and making it difficult for the trapped oil to produce.20 Moreover, the effect of capillary pressure is higher in low-permeability core samples. This lead to a lower water flooding oil recovery in lowpermeability circumstance.21 The small pore throat size also affects the polymer behavior because a smaller pore throat size will have a higher shear rate. The shear rate is inversely proportional to permeability:22 ⎤ ⎡ 3n + 1 ⎤n /(n − 1)⎡ uw ⎢ ⎥ γeff = C ⎢ ⎥ ⎣ 4n ⎦ ⎢⎣ kk rwSwϕ ⎥⎦

Figure 8. Relative permeability curves of water and polymer flooding.

Thus, the viscosity of the polymer will be lower in lowpermeability cores due to shear-thinning behavior and the mechanical degradation of polymer and the effect of mobility control is reduced. Experiment no. 1 was designed to evaluate the performance of biopolymer on low-permeability outcrop carbonate core sample. The experiment was conducted at 120 °C. Results were first simulated using the tuned model and later verified with the experiment run on a core sample of absolute permeability 2.8 mD. Water flooding pre-flush was done for 11 PV, and the oil recovery was calculated to be 46.66%. Polymer flooding was then initiated and was continued for 9.8 PV, but the polymer failed to increase oil recovery. The biopolymer degraded because of mechanical degradation in low permeability. Figure 10 summarizes the experimental output. Rheology tests of the produced effluent showed that viscosity of produced polymer is the same as of formation brine (1.25 cP). The reduction in polymer solution viscosity indicates mechanical degradation of polymer inside core sample because of the high in situ shear rate caused by small pore throat size inside the low-permeability core sample. It has been believed that the biopolymer molecule was degraded into small fragments and were attached on the rock surface. The increase in differential pressure during polymer flood and post flush further strengthens this rationale, although there is no other evidence that the molecule was degraded into smaller bits. The low-permeability matrix makes it difficult for largemolecule-size polymer to enter pores.7 The minimum permeability

Table 6. Parameters for History Matching parameter

value

Nw Now reaction rate

2 1.8 0.00001

(9)

were calculated and found to be 5.18 and 575 000, respectively, with a material balance error of −0.048%: A polymer → Bwater 5.18 × 2000 → 575 000 × 0.018

Figure 9 shows the match between experimental results and model output. This calibrated simulation model was then used for optimization of polymer flooding, including the investigations on injection rate, polymer initiation time, and polymerslug size.

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OPTIMIZATION AND RESULTS To optimize recovery and evaluate the effects of injection rate, rock permeability, polymer initiation time, and polymer-slug size on the ultimate oil recovery, various cases were simulated on the history-matched model. For optimization, the temperature in the simulation model was increased to 120 °C. The effects of these parameters are discussed in the following sections.

Figure 9. Match of experimental and simulated results of the base case experiment. F


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Figure 10. Oil recovery factor and differential pressure of experiment no. 1.

Figure 11. Simulated cases of varying injection rate.

for polymer flooding should be 50 mD.23 However, in our case, we found that a polymer injection is feasible when the absolute permeability of rock is greater than 30 mD.

injection rate on oil recovery, four different cases were simulated with injection rates varying from 0.2 to 2 cc/min. The simulation results of the effect of varying flow rate on oil recovery are given in Figure 11, which shows that the effect of flow rate is insignificant. The minor increase in oil recovery during polymer injection is caused by the increase of polymerslug size. With increase in injection rate, the apparent viscosity of polymer solution in porous media will be low because of the shear-thinning behavior of polymer solution, which results in increased chemical requirement. Moreover in the field scale, high flow rate may result in many problems including surface facilities requirement to pump high-viscosity polymer solution at a high flow rate. The bottom-hole flowing pressure (BHP) will also be affected when injecting at high flow rate and the formation may be damaged by high flow rate or fractured due to the high pressure. Therefore, 0.2 cc/min flow rate was selected to be the recommended case.

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INJECTION RATE Injection rate affects capillary number, which, in turn, affects Sor. In addition, the rate at which oil is produced depends upon the injection rate. The flow velocity is related to capillary number by the following equation:24 νμ Nc = (10) σ Increasing the injection rate will increase the Nc value, and that will reduce Sor.25 However, significant change on Sor can only be found when Nc is amplified several times. During polymer flooding, Sor does not increase. However, oil can be recovered quickly by increasing the injection rate. To evaluate the effect of G


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Figure 12. Simulated results of varying polymer initiation time cases.

Figure 13. Oil recovery factor of experiment no. 2.

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The recovery from pre-flush is 55.86%, and final oil recovery was 69.37%. The experimental results are presented in Figure 13. Theoretically, the best case is to start polymer injection at the beginning of the production of the reservoir. However, the targeted carbonate reservoir is already under water flooding. The case that polymer was injected after 0.3 PV of water flooding takes 1 PV of displacing fluid to reach the production platform. In conclusion, for our case, polymer injection should start after 0.3 PV of water flooding pre-flush; in other words, polymer flooding should be initiated before water breakthrough. Due to the early injection of polymer, water breakthrough is delayed to 0.6 PV rather than after 0.3 PV in the base-case experiment.

POLYMER INITIATION TIME Early initiation time has better effect in any EOR process. It is believed that the polymer does not decrease Sor.26 However, polymer initiation time dictates the amount of displacing fluid needed to reach Sor. To estimate the significance of initiation time, various cases were simulated on the tuned model with different initiation times. Polymer flooding was designed to start at the beginning for case 1; after 0.3 PV of water flooding for case 2; and 0.5, 1, and 2 PV of water flooding for cases 3, 4, and 5, respectively. The simulation results of varying polymer initiation time are presented in Figure 12. It has been observed that volume of displacing fluid required to reach Sor decreases with a decrease in initiation time. In experiment no. 2, the effects of early initiation time of polymer were assessed on a high-permeability core sample at a high temperature (120 °C). Simulated results are tested on a core sample with permeability of 126 mD. A polymer slug of 0.5 PV was injected after 0.5 PV of water flooding.

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POLYMER-SLUG SIZE The polymer-slug size governs the economic feasibility of polymer flooding. In practice, polymer-slug size should always be less than 1 PV. The polymer solution is diluted, adsorbed, and H


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Figure 14. Simulated cases of polymer-slug size.

Figure 15. Recovery factor and differential pressure of experiment no. 3.

degraded inside the core sample, by which the viscosity of the polymer solution decreases. Therefore, the optimization work is focused on finding the limitation of polymer-slug size that could give optimum recovery. The simulation results of polymer initiation time suggested that the best case for polymer injection is just before the water breakthrough. Here, polymer flooding was designed to initiate just after 0.3 PV of water flooding pre-flush. Multiple cases were simulated in which polymer-slug size was varied from 0.02 to 1 PV. The simulation results are presented in Figure 14. The results suggest that a smaller polymer-slug size decreases the oil recovery. However, compared with the cases of 1 PV polymer slug and 0.5 PV polymer slugs, the oil recovery of the case of 0.1 PV did not drop on large extent. Experiment no. 3 was conducted to validate the effect of polymer-slug size at high temperature and high salinity.

Core-flood was performed on a medium-permeability core sample having an absolute permeability of 43.5 mD. Water flooding pre-flush was done for 0.5 PV followed by 0.7 PV of polymer slug. The oil recovery from pre-flush was 51.36%, and polymer flooding had given 7.7% additional recovery. The experimental results are shown in Figure 15. During the core-flood process, the RF and RRF were calculated and found to be 1.95 and 1.092, respectively. The RF and RRF are decreased because of the reduction in polymer-slug size, which diffuses inside the core sample, and its viscosity decreases, causing lower polymer concentration. For further optimization, experiment no. 4 was performed on a high-permeability core sample of absolute permeability of 444 mD at reservoir temperature (120 °C) and salinity (167 g/L) conditions, with polymer initiation time and slug size further reduced. After 0.3 PV of water injection, 0.1 PV of polymer slug I


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Figure 16. Recovery factor and differential pressure of experiment no. 4.

Figure 17. Match of experimental and simulated results of experiment no. 4.

In the simulation, only polymer degradation and adsorption were taken into consideration. The dilution of the polymer was the key mechanism when the polymer-slug size is expressively reduced, but this complicated process could not be simulated. Actually, the polymer solution must have a minimum concentration to maintain its viscosity. For instance, 0.02 PV of polymer will be significantly diluted inside the core sample, and its viscosity will be reduced on large extent. In the simulation result, the percentage of recovery reduction for 0.02 PV is only 3.35%. In practice, the viscosity of significantly diluted polymer slug will not be enough to reduce the mobility of displacing fluid, and such low-viscosity polymer flooding will have no difference from common water. As a result, the conclusion could be made that 0.1 PV of polymer-slug size is expected to be a promising case, and this is confirmed from core-flood experiment no. 4. A total of five other core flood experiments were also performed, which validates the documented results of five core-flood experiments.

was injected in a high-permeability core sample. Because of early polymer injection in a high-permeability core sample, water breakthrough was postponed to 0.6 PV, which was a delay of 0.3 PV compared to the base case. This indicates that even 0.1 PV of polymer slug can reach the desired mobility control objective, and as a result, the final oil recovery of this core-flood run is as high as 85%. The experimental results are shown in Figure 16, and a match with simulated output is shown in Figure 17. The differential pressure increment in polymer flooding was not obvious because the polymer-slug size was only 0.1 PV. The differential pressure fluctuated drastically after water breakthrough because of the capillary end effect and two-phase flow, i.e., water and oil. This effect is more significant in high-permeability core samples.27 Oil was produced during pressure fluctuation. With the decreasing of oil saturation, the capillary end effect became inconspicuous, and the differential pressure was stabilized. J


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CONCLUSIONS The results from a series of the core-flood experiments indicate that the biopolymer can withstand high temperature and high salinity. It can improve mobility ratio and can possibly give additional recovery. The results of core-flood experiments were used to perform an optimization study for evaluating the effects of various parameters on oil recovery. The following conclusions can be inferred from this study: • The biopolymer was stable and effective in medium to high-permeability core samples; however, it was degraded in low-permeability rock. • The polymer initiation time effects the amount of fluid needed to reach residual oil saturation, and injecting polymer just before water breakthrough was the mostoptimal scenario of polymer flooding. • The increase in polymer-slug size increased oil recovery; however, 0.1 PV of polymer slug injected after 0.3 PV of pre-flush gave the most-optimized recovery. • Injection rate showed an insignificant impact on oil recovery.

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Now = exponent for calculating krow γeff = effective shear rate (1/sec) n = power law index C = function of permeability and porosity uw = Darcy velocity (cm/sec) Nc = capillary number v = flow velocity (ft/day) TDS = total dissolved solids

REFERENCES

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Muhammad R. Hashmet: 0000-0001-9584-3307 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We acknowledge financial support from the ADNOC R&D Oil Sub-Committee and ADCO for providing reservoir characteristics and formation brine composition. We also thank Wintershall for providing polymer samples.

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ABBREVIATIONS Kabs = absolute permeability (mD) q = injection rate (cc/min) μ = viscosity of brine (cp) L = length of core (cm) A = cross-sectional area (cm2) ΔP = differential pressure (psi) Swi = initial water saturation Soi = initial oil saturation Sor = residual oil saturation Vw = produced water volume (cc) PV = pore volume of the core sample (cc) RFw = recovery factor (%) Vp = produced oil volume (cc) V = volume of original oil in core sample (cc) RF = resistance factor RRF = residual resistance factor ΔPp = differential pressure during polymer flooding (psi) ΔPw = differential pressure during water flooding (psi) krwiro = water-phase relative permeability at irreducible oil saturation Swcrit = critical water saturation Soirw = irreducible oil saturation Sorw = residual oil saturation Swcon = connate water saturation Nw = exponent for calculating krw K


Article

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