Advances in Understanding Polymer Retention in Reservoir Rocks: A Comprehensive Review

Abstract

Understanding polymer retention is a critical aspect in the field of chemical-enhanced oil recovery (cEOR). This article presents a comprehensive review of polymer retention in reservoir rocks, focusing on the underlying mechanisms, measurement techniques, and the factors influencing this phenomenon. Three main (proposed) mechanisms that contribute to polymer retention are discussed in detail. Polymer adsorption, hydrodynamic retention, and mechanical entrapment are identified as key factors affecting the overall retention of polymers during flow through porous media. Also, herein, we explore the details of these mechanisms, explaining how polymer characteristics and rock surface properties influence the degree of retention. Furthermore, we analyze the influencing factors that affect polymer retention. The rock surface properties, such as surface charge and wettability, play a vital role in determining the interaction between polymers and rocks. The interplay of these factors provides valuable insights into understanding and controlling polymer retention in cEOR applications. This review paper put in a nutshell a comprehensive understanding of the mechanisms, measurement techniques, and influencing factors involved.

Keywords:

• Polymer retention
• chemical enhanced oil recovery
• polymer flooding
• oil recovery optimization

1. Introduction

Regardless of the conventional oil recovery, i.e. primary and secondary ones, far-reached amounts of oil remain uncovered. The tertiary stage of oil recovery, namely enhanced oil recovery (EOR), targets the trapped oil in a reservoir to maximize oil recovery. The oil recovery can be classified into three parts such as primary, secondary, and tertiary oil recovery (Figure 1). Primary oil recovery relies on the natural pressure of the reservoir, while secondary recovery involves water injection to further recover oil and maintain reservoir pressure. Tertiary oil recovery is also known as enhanced oil recovery (EOR). A successful EOR requires a comprehensive understanding of reservoir properties, fluid interactions, injection technology, reservoir pressure management, and continuous evaluation and monitoring of the reservoir. When fluids are introduced, the interactions between the injected fluids and the reservoir rock/fluids occur, critically affecting the flow of fluid in porous media and associated oil recovery efficiency.^[1]

Figure 1. (a) Oil production classification, adapted from Ref.^[7] (b) EOR projects, globally, as mentioned in Ref.^[8]

EOR technologies can generally be classified mainly into thermal methods, gas injection, and chemical flooding technologies (Figure 1). Even though the thermal and gas injection technologies possess the largest share of EOR projects globally, chemical-enhanced oil recovery (cEOR) is a unique technique that is employed in certain oil fields to tackle specific reservoir issues. Studies have shown that cEOR projects are growing rapidly worldwide due to a better understanding of rock–fluid interaction.^[2] The cEOR methods mainly rely on polymer flooding (∼77%) and the rest cEOR techniques depend on the use of surfactants, surfactant-polymer (SP), and alkaline–surfactant–polymer (ASP) flooding. Extensive research has been conducted in the field of cEOR over the past six decades.^[3] The consumption and cost of chemicals play an important role in the cEOR method.^[4] The application of cEOR agents such as surfactants, polymers, alkalis, or their combinations has demonstrated successful outcomes in improving oil recovery by enhancing both microscopic (displacement) and macroscopic (volumetric sweep) efficiency.^[5,6]

Polymers, in particular, possess elastic and viscous properties and exhibit unique behaviors under shear stress in porous materials.^[9] Polymer flooding can enhance the oil recovery process through several mechanisms such as: influencing fractional flow, decreasing the mobility ratio between water and oil, and redirecting injected water from previously swept areas.^[10,11]

However, the loss of polymers due to retention during the polymer flooding process remains a hurdle in polymer-based cEOR methods, hence impacting the economics of such projects.^[4] Retention values are quantified as micrograms of polymer adsorbed per gram of rock. The variation in retention degrees, ranging from 9 to 700 μg/g, has been documented across different types of polymers and rock formations 12. Significant losses through retention can cause considerable delays in oil production.^[12] Three mechanisms play a role in the retention of polymers when flowing into porous media including polymer adsorption, hydrodynamic retention, and mechanical entrapment.^[13]

Understanding the interplay between the surface of the rock and the structure of the polymer is crucial when choosing a suitable polymer for the flooding process. Valuable insights into these different dynamics can be addressed through polymer retention studies. Thus, the subsequent sections provide essential details regarding various retention mechanisms, measurement techniques, and factors that influence polymer retention. This knowledge contributes to a better understanding of polymer retention and facilitates the development of strategies to mitigate the loss of precious material. However, ahead of it, below we are refreshing the reader’s background about both reservoir types as well as polymer flooding types.

1.1. Reservoir lithology

One of the crucial criteria for selecting the suitable polymer in EOR technology is defined by the rock surface charge of the target reservoir. Hereafter, one could define a technique that identifies whether a rock surface is negative or positive. Based on the pH of the surrounding or flowing liquid, one could identify the surface as either positively or negatively charged. At the surface of the rock, the pH at which the surrounding liquid exhibits zero net charge is called the isoelectric point (IEP). If the flowing liquid has a pH value above IEP, the rock is defined as a negatively charged surface. Likewise, below that value, the rock surface is said to be positively charged.^[14] Typically, oil reservoirs are classified into two main types: sandstone or carbonate formations. Sandstone formations usually have a negative charge, with an isoelectric point falling between 1.7 and 3.5. In scenarios where the pH of the surrounding fluids is above 3.5, which is usually the case, the sandstone maintains its negative charge. On the other hand, carbonate rocks, known for their intricate nature including layering, microporosity, and natural fractures, tend to exhibit a positive surface charge when the pH is low, as their isoelectric point is typically above 8. However, carbonate rocks become negatively charged at higher pH levels, which is influenced by the solution’s equilibrium pH 15–19.

Based on the statistical study of global EOR projects, the sandstone reservoir has the largest share (78%) of these projects (Figure 2). Moreover, the major share of EOR projects goes to thermal methods in the sandstone reservoir. On the other hand, the major share of EOR projects goes to gas methods in the carbonate reservoir perhaps due to the complexity of the carbonate rocks such as low porosity, fractured, and heterogeneity.^[15]

Figure 2. EOR projects as per Reservoir type, adopted from ref.^[20]

1.2. Polymer flooding

Polymer flooding comprises the injection of polymer-augmented water into the reservoir (Figure 3) to improve the viscosity of displacing water and decrease the oil/water mobility ratio.^[16] The use of polymers in EOR has shown promising outcomes in extracting medium, heavy, and extra-heavy crude oil. Consequently, numerous studies have documented the application of polymer-based chemical EOR methods in experimental, pilot, and field-scale settings. However, the implementation of polymer flooding in actual oil fields has mainly been restricted to sandstone formations. This limitation arises due to the complexities associated with carbonate reservoirs. One should note that Figure 3 does not capture the possible fingering problem between the polymer slug and the chase water due to the adverse mobility ratio. One possible solution is the use of polymer tapering by reducing the polymer concentration in the injected polymer slug before switching to chase water.

Figure 3. Polymer flooding mechanism. adopted from ref.^[20]

The success of polymer flooding in EOR projects relies on a range of reservoir rock/fluid characteristics. These characteristics encompass rock type, geographical positioning (onshore or offshore), well depth, pore structure, fluid flow capacity, reservoir heterogeneity, oil thickness, reservoir temperature, brine salinity, water hardness, oil distribution, oil flowability, polymer type, and the properties of the injected polymer solution.^[17]

To assist in the screening and selection of suitable polymer flooding projects, several studies have developed screening criteria.^[18,19] These criteria serve as guidelines for evaluating the feasibility and potential success of polymer flooding in specific reservoirs. Considering the intricate interplay between reservoir characteristics and polymer flooding performance, the assessment of these screening criteria is essential for optimizing the application of polymer flooding in EOR projects.

In the Enhanced Oil Recovery (EOR) field, the selection of polymer flooding methods involves the consideration of various screening criteria presented in different research papers.^[21] Herein a comprehensive explanation and comparison of the screening criteria from four selected papers is provided in Table 1. Taber et al. recommend a reservoir depth of less than 9000 feet, a permeability greater than 10 mD, an oil viscosity range of 10 to 100 cP, an oil gravity higher than 15 API, a minimum oil saturation of over 50%, and a reservoir temperature below 200 °F.^[22] Aladasani et al. suggests a suitable reservoir depth ranging from 700 to 9460 feet, a permeability range of 1.8 to 5500 mD, an oil viscosity varying from 0.4 to 4000 cP, an oil gravity between 13 and 42.5 API, and an oil saturation between 34 and 82%.^[23] J. J. Sheng et al. focus on a recommended reservoir permeability of 50 mD, an oil viscosity below 150 cP, a reservoir temperature below 200 °F, and a salinity below 50,000 ppm.^[23] Saboorian et al. propose a reservoir depth of fewer than 5250 feet, a minimum porosity of 21%, a permeability greater than 1000 mD, an oil viscosity less than 5400 cP, an oil gravity higher than 11 API, a minimum oil saturation of over 50%, a reservoir temperature below 149 °F, and a salinity below 46,000 ppm.^[24] The variations in these screening criteria reflect the diversity in reservoir conditions, including depth, permeability, viscosity, gravity, saturation, temperature, and salinity. Thus, it is crucial to consider the specific characteristics of the reservoir when selecting polymer flooding methods and refer to the appropriate screening criteria provided in the literature.^[21]

Table 1. Screening criteria for polymer flooding reported in the literature.^[26]

Criteria	Taber et al.^[^27^]	Aladasani et al.^[^28^]	J. J. Sheng et al.^[^25^]	Saboorian et al.^[^29^]
Reservoir depth (feet)	<9000	700–9460	–	<5250
Permeability (mD)	>10	1.8–5500	50	>1000
Oil viscosity (cP)	10–100	0.4–4000	<150	<5400
Oil gravity (API)	>15	13–42.5	–	>11
Oil saturation (%)	>50	34–82	–	>50
Reservoir temperature (°F)	<200	<237	<200	<149
Salinity (ppm)	–	–	<50,000	<46,000
Porosity (%)	–	–	–	$\ge$21

The mobility ratio refers to the ratio of the fluid mobility (typically water) to the oil mobility (Figure 4). In a regular waterflood situation, the mobility ratio (M) can be stated as follows: (1) $$\mathrm{M}=\frac{{\lambda }_w}{{\lambda }_o}=\frac{k_{\mathit{\text{rw}}}/{\mu }_w}{k_{r0}/{\mu }_o}=\frac{k_{\mathit{\text{rw}}}{\mu }_o}{k_{r0}{\mu }_w}$$(1) where λ_w represents the water mobility, λ_o represents the oil mobility, K_rw represents water relative permeability, K_ro denotes oil relative permeability, μ_w represents water viscosity, and μ_o represents the oil viscosity.^[21] Adding water-soluble polymers to injected water increases the viscosity of the flooding fluid. As a result, the mobility of the injectant is reduced, leading to a decrease in the fractional flow of water and enhancing the volumetric sweep efficiency^[26],[32].

Figure 4. Various mobility ratio (M) scenarios in polymer flooding.^[31]

2. Polymers retention mechanisms

Polymers utilized in enhanced oil recovery (EOR) are large molecular structures that interact with the rock matrix during their passage through oil-bearing formations. As a consequence, a certain fraction of these molecules can be lost due to retention. The term “retention” encompasses three distinct mechanisms, namely adsorption, mechanical entrapment, and hydrodynamic retention.^[13] Physical adsorption causes the polymer to adhere irreversibly to the rock surface, while in the porous medium, the polymer may block pores by straining the largest single molecules or result in concentration blocking if an excessive number of molecules enter a single pore.^[26–29] Consequently, the flow of polymer leads to pore blocking and a reduction in pore volume, known as the inaccessible pore volume (IPV).^[30]

High polymer retention causes a delay in the breakthrough of the polymer during the injection process, consequently delaying oil recovery.^[1] Moreover, polymer flooding performance is influenced by polymer retention.^[31,32] A higher polymer retention requires a larger quantity of polymer to achieve the desired viscosity, exceeding the planned amount and affecting the efficiency and economics of the project. Therefore, it is crucial to measure and account for polymer retention on a laboratory scale and perform careful upscaling through simulation runs before implementing it in the field.^[13,33,34]

Figure 5 illustrates the retention mechanism in reservoirs, which involves several key processes. Firstly, polymers can be adsorbed onto the reservoir rock surface, where chemical bonds or physical interactions bind them to the surface. Additionally, polymers can be hydrodynamically trapped in stagnant zones, where limited fluid flow causes the polymers to be trapped in those areas. Lastly, polymers can be mechanically entrapped within nanopores of the rock, where the small pore size prevents the polymers from escaping.

Figure 5. Retention mechanisms in porous media.^[35]

2.1. Polymers adsorption

The process of polymer molecules interacting with the rock surface in an aqueous environment is referred to as adsorption, which is a well-studied but complex phenomenon that is not yet fully understood.^[36] This interaction leads to the binding and attachment of polymer molecules to the surface of rock grains primarily through physical adsorption, driven by hydrogen bonding and van der Waal’s forces, rather than chemisorption. The extent of adsorption, which can account for up to 60% of the total polymer retention, depends on the interactive properties between the polymer and rock.^[37] However, there are situations where the contribution of adsorption may be significantly lower (below 20%) compared to other retention mechanisms.^[38]

The adsorption phenomenon occurs on the rock surface due to a favorable decrease in overall free energy. This decrease in free energy is primarily influenced by entropic factors, such as the release of water molecules from the polymer solution or rock surface during the process, leading to an increase in entropy. The decrease in the concentration of polymer fluid also contributes to the increase in entropy. However, there is a counteracting entropy loss due to the reduction in configurational freedom of the polymer when it becomes adsorbed on the surface. Enthalpy also plays a role in the favorable free energy of polymer adsorption, especially for ionic polymers. This contribution is a result of the electrostatic attraction or repulsion between the polymer and the surface, which depends on the net ionic charge of the surface.^[39,40]

Referring to Figure 6, the adsorption mechanism of anionic polymers on reservoir rock surfaces involves multiple interactions, including hydrogen and ion bonding, lipophilic interaction, Van der Waals, and electrostatic interaction. Hydrogen bonding occurs between the anionic polymer and the surface of rock, while hydrophobic interaction takes place between nonpolar regions of the polymer and hydrophobic areas of the rock. Ion binding occurs when the polymer interacts with charged ions present on the rock surface, and electrostatic interaction involves the attraction between the anionic polymer and oppositely charged species on the rock. Van der Waals forces represent weak attractive forces between the polymer and the rock surface. These various interactions collectively contribute to the adsorption of anionic polymers on reservoir rock surfaces.

Figure 6. The adsorption mechanism of anionic polymers on reservoir rock surface.^[41]

2.2. Mechanical entrapment

Mechanical entrapment also referred to as deep-bed filtration occurs when the movement of polymer fluid is obstructed by narrow pore throats.^[13,42–44]

The extent of mechanical entrapment is influenced by the polymer’s molecular weight and concentration, and it decreases in rocks with high permeability. Experimental studies have shown that a higher level of mechanical entrapment is observed when the effective hydrodynamic radius of the polymer molecule is similar to the net average pore radius suggesting that polymers exhibiting a very high level of mechanical entrapment behavior could lead to pore plugging in the near-wellbore region, potentially resulting in complete well plugging and formation damage. Therefore, it is crucial to assess the extent of mechanical entrapment in laboratory-scale experiments before implementing polymer injection in the field, particularly in low-permeability reservoirs.^[34,45,46] Sugar et al. reveal that the complete blockage of flow channels by polymer molecules is the result of polymer aggregation and the combined effects of adsorption and mechanical plugging, affecting the porosity and conductivity of the medium and creating inaccessible pore volumes 54.

2.3. Hydrodynamic entrapment

Hydrodynamic entrapment pertains to the confinement of polymers in stagnant zones, regions with no flow, or secondary flow zones at the pore scale, resulting from the osmotic force and hydrodynamic drag exerted by the pore throats, acting as a filter for the polymers. The quantification of this mechanism involves considering parameters such as flow rate and tortuosity.^[13,47] However, it is believed that this mechanism has minimal impact at the field scale.^[48,49]

The observation of hydrodynamic retention came from experiments where changes in flow rates led to variations in polymer retention levels after reaching a steady state.^[44,47,50] In a partially hydrolyzed polyacrylamide (HPAM) core flooding experiment conducted by Chauveteau and Kohler, increasing the rate of flow from 3 cubic meters/day to 10.3 cubic meters/day resulted in higher polymer loss within the porous media, as evidenced by a decrease in the effluent polymer concentration. When the rate of flow was reduced back to 3 cubic meters/day, the concentration of polymer effluent exceeded the initial input value of 400 ppm, indicating a decrease in the level of retention. Resuming injection led to a sharp peak in the polymer effluent concentration, caused by the mobilized polymer molecules, illustrating the reversibility of this retention mechanism.^[13] As this effect is temporary and minor, retention due to this mechanism is typically disregarded.^[51]

In the literature, two main methods are commonly used for measuring and quantifying polymer retention in reservoir rock samples which are dynamic retention/adsorption and static retention. Dynamic adsorption involves core flooding and is considered time-consuming, while static adsorption entails mixing polymer solution with crushed rock powder and requires less time. However, the static adsorption method yields higher adsorption values compared to the dynamic adsorption method. This discrepancy is primarily attributed to the significant difference in surface area between the crushed rock samples used in static adsorption tests and the consolidated rock samples used in dynamic adsorption tests. Additionally, the static adsorption method does not account for mechanical entrapment.^[51] Hydrodynamic forces cause temporary entrapment of polymer molecules in microfluidic channels, with the extent of retention influenced by channel width and flow dynamics, impacting the transport and behavior of polymers in porous media 54.

Typically, polymer retention is measured in a single-phase system, without the presence of oil, mainly for the sake of simplicity in experimental setups. However, in field projects, the injected polymer often encounters oil. Even if the polymer is injected below the oil-water contact, it will propagate toward the oil producers and encounter porous media containing oil.^[52]

2.4. Static adsorption

Static methods have been employed to measure the adsorption or retention of polymers.^[53] This method involves measuring the concentration of the polymer solution before and after it comes into contact with sand. The adsorption of the polymer is determined by dividing the mass lost from the solution by the weight of the sand it was exposed to. However, there are some criticisms of this method. Firstly, it heavily relies on only two measurements of polymer concentration, which means that any errors in those measurements can significantly impact the calculated adsorption value. Secondly, the process of pulverizing the rock to create the sand may expose surface areas and minerals that may not be accessible during dynamic experiments where polymer solutions flow through porous media. Additionally, this method does not take into account any polymer that may be mechanically trapped.^[54–56]

Another approach, as described by Hughes, Osterloh & Law, involves the injection of a polymer solution, along with a tracer, into a core or sand pack.^[26,27] The effluent concentrations of both the polymer and tracer are monitored until they reach the injected concentrations. At this point, a significant volume of brine (around 100 pore volumes) is injected to displace all the mobile polymer and tracer. Following this, a second bank of polymer solution is injected, again with the tracer. By analyzing the initial portions of the effluent curves during the two injection stages, the retention of the polymer and the inaccessible pore volume can be determined. This method eliminates the uncertainties and challenges associated with issues like viscous fingering and prolonged production of low-concentration fluids. To calculate polymer adsorption at each concentration, Equation (2)(2) $$R_{\mathit{\text{pret}}}=\left(C_o-C_{\mathit{\text{eq}}}\right)x\mathrm{ }{V}_p/W_{\mathit{\text{sg}}}$$(2) can be used based on mass balance.^[26,55] (2) $$R_{\mathit{\text{pret}}}=\left(C_o-C_{\mathit{\text{eq}}}\right)x\mathrm{ }{V}_p/W_{\mathit{\text{sg}}}$$(2)

The parameter $R_{\mathit{\text{pret}}}$ represents the amount of polymer adsorbed in milligrams per gram of sand, while $C_o$ and $C_{\mathit{\text{eq}}}$ indicate the initial and equilibrium polymer concentrations, respectively, measured in parts per million (ppm). $V_p$ refers to the volume of polymer in cubic centimeters (cm³), and $W_{\mathit{\text{sg}}}$ denotes the weight of the sand in grams (g). The density of both the polymer and brine is assumed to be 1 g/cm³.

2.5. Dynamic adsorption

Dynamic adsorption tests, as opposed to static tests, entail significant costs and time investments. However, they offer a more accurate depiction of chemical retention during flooding operations. Previous research has aimed to establish a correlation between dynamic and static adsorption data, seeking to leverage static data to predict dynamic adsorption.^[57,58] One such method, proposed by Al-Hajri et al., employs a static polymer adsorption test. This method revolves around the separate measurement of adsorption per unit surface area and the inaccessible pore volume. By integrating these outcomes, practical values can be derived, which closely mirror those obtained in dynamic tests. Notably, this approach is both swifter and more cost-effective. The quantity of dynamic retention can be computed using Equation 3(3) $$Q=\frac{C_o{V}_o-{\sum }_{i=1}^n{C}_i{V}_i}{W}$$(3) ^[57,58] (3) $$Q=\frac{C_o{V}_o-{\sum }_{i=1}^n{C}_i{V}_i}{W}$$(3) where Q refers to the density of polymer retention (µg/g), Co represents the initial concentration (mg/L), Vo refers to the volume of polymer solution (mL), Ci is the concentration (mg.L⁻¹) and Vi is the volume (mL), W is the core weight (g).

3. Measurements techniques

The estimation of static polymer adsorption can be conducted using several methods, including comparing the measured polymer concentrations before and after the treatment. Some of these methods include:

3.1. Total Organic carbon (TOC)

The amount of organic carbon (Figure 7) present in a chemical mixture can be measured using Total Organic Carbon (TOC) analysis.^[59] In this study, a Total Organic Carbon Analyzer (TOC-L) in combination with an air generator was employed. The TOC-L instrument utilizes a combustion catalytic oxidation process at a temperature of 680 °C, which enables the oxidation of low molecular weight organic compounds like polymer. The TOC analyzer determines the concentrations of both total carbon (TC) and inorganic carbon (IC). The TOC value is obtained by subtracting the IC concentration from the TC concentration. It is important to note that higher polymer concentrations will result in greater TOC values, as observed by Wang et al. (2015).

Figure 7. Total organic carbon (TOC) analyzer.^[60]

3.2. Ultraviolet (UV) spectroscopy

In a UV spectrometer (Figure 8), molecules with electrons absorb ultraviolet or visible light energy, causing the electrons to move to higher energy levels.^[59] The extent of electron excitation determines the amount of light absorption at a specific wavelength. This phenomenon is utilized in UV-spectrometry to measure the absorbance of light by a sample. The spectrometer emits a light beam with a known wavelength onto the sample, and the resulting absorbance of the light is measured. This technique, as explained, allows for the characterization of molecules based on their light absorption properties.

Figure 8. Schematic diagram of UV–Vis spectrometer.^[61]

3.3. Radioactivation method

In radioactivation (Figure 9), the analysis is conducted to determine the concentration of an element capable of forming a radioactive isotope. For instance, the sample containing the element of interest is placed in an atomic reactor alongside a standardized sample with a known concentration of the element. Once both samples have been equally exposed to radiation, a comparative measurement of their resulting radioactivity is performed to determine the unknown concentration of the element in the first sample. This method allows for the quantification of trace amounts of elements by utilizing the radioactive properties and measuring the resulting radioactivity.^[62]

Figure 9. Schematic of a Nier-type isotope ratio mass spectrometer.^[63]

3.4. Chromatographic and ion exchange methods

The technique of chromatography has gained significant interest in recent years, although it is not a recent discovery. It has now become the most widely used method for separating different components. Certain materials, such as silica, alumina, carbon, and cellulose can attract and retain various substances on their surface without undergoing a chemical reaction. This type of attraction is purely physical and differs from a chemical reaction called chemisorption (Figure 10), which involves polymers with specific functional groups on their surface. For example, if the adsorbent material contains acidic groups, it can effectively exchange ions and is known as an ion exchange resin.^[62]

Figure 10. Schematic diagram of ion chromatography analysis.^[64]

In recent years, microfluidics has emerged as a powerful tool for investigating polymer retention at the microscale.^[65–67] The integration of microfluidics with single-molecule imaging techniques has enabled direct visualization and multi-scale characterization of polymer dynamics in representative porous media. For instance, Sugar et al. employed microfluidic techniques to assess polymer-induced clogging and transport mechanisms through porous media, highlighting the limitations of existing polymer screening workflows and emphasizing the need for careful core-flood experiments to evaluate polymer entrapment mechanisms.^[67] Similarly, in another study by Sugar et al., the dynamic behavior of polymer molecules in porous media was investigated using microfluidics and single-molecule imaging, shedding light on the contributions of polymer adsorption, entrapment, and hydrodynamic retention to overall retention.^[65] This research demonstrated the role of microfluidic platforms in providing a more representative and accurate model for polymer retention and permeability reduction, thus offering insights crucial for a wide range of applications in geoscience and materials science. Additionally, in a study by Sugar et al., fluorescent polymers and single-molecule imaging were utilized to assess the dynamic interaction and transport behavior of polymer molecules in a microfluidic device, providing direct observations of polymer pore-clogging and unclogging processes.^[66] Pore-scale simulations further complemented experimental observations, revealing a decline in flow conductivity over time due to polymer accumulation and retention. Together, these studies highlight the significant advancements made in understanding polymer retention mechanisms at the microscale through the use of microfluidics.

4. Polymer retention influencing factors

The quality of polymers available in the market can vary significantly. Poor-quality polymers, characterized by high insoluble content and broad molecular weight distributions, generally result in higher polymer retention values due to pore blockage caused by high molecular weight tail ends and insoluble particles.^[68] Reducing the insoluble content significantly improves polymer propagation.^[42,52]

Various parameters influence polymer retention, including the permeability of the porous media,^[34,68] brine composition,^[69–71] reservoir temperature,^[18,69] and the presence of oil.^[26,72,73] Retention values tend to be higher for porous media with lower permeability. Lower permeability restricts the flow of polymer chains, resulting in increased mechanical entrapment. Additionally, lower permeability rock typically has a higher pore surface area compared to highly permeable rock.

The clay content, specifically on the surface of porous media, significantly affects polymer retention. Porous media with high clay content exhibit high polymer retention, attributed to greater physical adsorption.^[70] Recent studies have demonstrated that brine composition is also a significant factor affecting polymer retention. Brines with low total dissolved solids (TDS) show much lower polymer retention. Moreover, adjusting the brine composition, such as the mass action ratio (MAR), to minimize electrolyte imbalance also impacts polymer retention.^[74]

4.1. Effect of permeability

Numerous studies have reported an increase in polymer retention with decreased permeability, particularly in rocks with permeability below 100 mD.^[73,75–80] Other researchers have suggested that retention is predominantly governed by mechanical entrapment in low-permeability rocks (>130 md), while adsorption primarily influences retention in moderate-to-high permeability sands and rocks.^[44,73,81] These suggestions align with the fact that the dimensions of high-molecular-weight EOR polymers (typically 0.1–0.5 μm radius, depending on molecular weight and salinity) can approach the size of pore throats in low-permeability rock.^[70,82]

However, it should be noted that Gosh and Mohanty have mentioned the feasibility of polymer flooding in less-permeable reservoirs.^[83] Nevertheless, the majority of recent polymer floods have been applied in sands or sandstones with an average permeability exceeding 500 md. X-ray computed microtomography analysis of 470-md sandstone has provided evidence of extensively interconnected pores. The findings indicate that 98% of the pores possess an effective diameter exceeding 26 μm, with a pore throat diameter exceeding 6.7 μm.^[78,84] Consequently, mechanical entrapment of polymer, including bridging adsorption and hydrodynamic retention, is not expected to be significant in most polymer floods with an average permeability above 500 mD.^[49,73] In our previous studies on Milne Point core material using an 18-million-g/mol HPAM (Flopaam 3630) in 2435-ppm TDS water, we observed no correlation between polymer retention and permeability within the range of 15 md to 10 darcies.^[85]

The reversibility of polymer retention in chemical enhanced oil recovery processes is a critical aspect that influences the efficiency and economics of reservoir operations. Field observations often suggest that polymer retention may not be entirely irreversible, indicating the need for a deeper understanding of reversible polymer retention dynamics and their implications for fluid flow and residual resistance factors (RRF). The study by Hoteit et al. sheds light on this issue by investigating the mechanisms behind polymer-induced resistance to flow in reservoirs undergoing a chemical flood.^[86] They challenged the assumption of irreversibility in existing simulation models, highlighting that permeability reduction during polymer flood may not necessarily translate to the same reduction during post-polymer chase water injection. Their findings indicate that post-polymer chase water injection may not be as efficient as previously assumed due to the reversible nature of polymer-induced permeability reduction. Lab observations consistently show that RRF continues to decrease with post-polymer flood water injection, suggesting a decoupling between permeability reduction during polymer flood and subsequent water flood. To address this discrepancy, they propose a new model that decouples these mechanisms and introduces an empirical parameter to denote the degree of reversibility of permeability reduction during chase water flood.

The proposed model offers a more accurate representation of the fluid flow behavior during post-polymer chase water injection, highlighting the importance of proper measurements to determine RRF behavior at reservoir operating conditions. Overestimating RRF may lead to premature switching from polymer flood to chase water flood, impacting project economics and efficiency.

4.2. Effect of polymer charge, salinity, divalent ion content, and alternative monomer units

Some researchers have suggested that polymer adsorption should decrease with increased anionicity (e.g. degree of hydrolysis for HPAM) and decreased salinity.^[87] The rationale behind this suggestion is that negatively charged rock surfaces should repel negatively charged polymers, and increased salinity should screen this repulsion, thereby increasing polymer adsorption. Supporting this view,^[88] presented evidence showing a decrease in HPAM adsorption as the degree of hydrolysis decreased from 15% to 2%. However, their work showed no significant effect on retention for degrees of hydrolysis between 25% and 75%. Similarly, literature^[89] observed no reduction in polymer retention in Berea sandstone as the degree of hydrolysis of HPAM increased from 0% to 15%. Similarly, literature^[90] reported comparable polymer retention on Berea sandstone for both 0% and 22% degrees of hydrolysis. Our findings in this article will also indicate that HPAM retention on illite is not greatly influenced by the degree of hydrolysis between 15% and 35%.

At low to moderate salinities, most previous researchers found that HPAM retention was not sensitive to the monovalent ion content of the water.^[91] observed similar HPAM retention on Berea sandstone between 0.1% and 2% NaCl.^[37] did not consistently notice a variation in HPAM adsorption when comparing distilled water and 2% NaCl. In a separate study,^[54] discovered that polymer adsorption on quartzite remained relatively unaffected by changes in salinity within the range of 0% to 13% KCl. Chiappa and Smith reported a modest dependence of HPAM retention on silica for NaCl concentrations below 3%, significantly higher retention was observed above 10% NaCl. Lee et al., also reported that the adsorption of HPAM on kaolinite increased fourfold when using 24% NaCl instead of 0.2% NaCl. It is worth considering whether the high retention observed at very high salinities might be related to HPAM solubility/cloud point rather than charge repulsion arguments. If charge repulsion were the dominant factor, one would expect the greatest variation in polymer retention to occur at the lowest salinities. However, in reality, the highest retention variations in clastic cores have been observed at the highest salinities.^[87] Interestingly, in Indiana limestone cores, Souayeh reported that the retention of an ATBS polymer was 2.5 times greater with a salinity of 0.196% TDS than with a salinity of 19.6% TDS (using the same ratio of monovalent to divalent cations).^[92]

4.3. Effect of oil saturation and wettability

Intuitively, one might expect that polymer retention would be lower, possibly significantly lower, in the presence of oil during retention measurements compared to when no oil is present, as oil can restrict polymer access to the rock surface.^[93] Additionally, it would be expected that water-wet rock would exhibit higher polymer adsorption than oil-wet rock. Nevertheless, the majority of researchers have observed only a slight impact of oil presence on the retention of polymers. In some cases, retention was modestly lower, up to half, compared to no oil conditions^{[39,54,81,94–99]} or even higher.^{[72,73,94,98,99]}

An intriguing anomaly was observed by Wever et al. (2018) in which the retention of sand sourced from an oil reservoir in Oman exhibited a tenfold increase in the absence of oil when compared to its presence.^[52] However, this case is complicated because the core without oil had substantially lower permeability than the one with oil. Souayeh reported a case where the retention of an ATBS polymer (SAV10) in approximately 250-md carbonate cores with residual oil was only 16% of that without residual oil.^[92] In our extensive study involving 30 core experiments with Milne Point core material, we did not find a clear relationship between HPAM retention and wettability or the presence/absence of oil.^[94] One possible explanation for the limited effect of oil on retention is that polymer adsorption increases the water-wet character of the rock.^{[57,80,92,100]}

4.4. Effect of clay content, carbonates, iron

Several authors have reported retention values of PAM, HPAM, and xanthan on kaolinite, ranging from 339 to 16,900 μg/g.^[26,47,90] In an experiment conducted by Seright using 9% kaolinite in 200-μm glass beads, 845 μg of HPAM was retained per gram of kaolinite.^[94] For comparison, our previous work with illite in 200-μm bead packs (involving 16 separate experiments with illite fractions ranging from 4.5% to 36%) yielded average HPAM retention values on illite of around 1100 μg/g. It should be noted that experiments with pure clay were challenging to assess due to their low permeability (<1 md), which led to significant mechanical entrapment of the polymer and subsequently extremely high retention values during flooding experiments. These excessively high values would not be representative of polymer retention in cases where clay constitutes a modest fraction of the reservoir rock. This issue may have contributed to the extremely high retention values (>10,000 μg/g) reported by some authors with pure clays.^[26,54] This point is also relevant to the report of 15,600 μg/g retention in siderite (FeCO3) by Hughes et al.^[26] In a bead pack with 9% siderite, we found HPAM retention to be only 545 μg/g when expressed as polymer retention per gram of siderite present.

At low temperatures (e.g., 25 °C) in brines with low salinity, most reports on polymer retention in carbonates or carbonate (dolomite or calcium carbonate) cores or packs indicate modest HPAM retention values, typically 100 μg/g or less.^[81,90,94] At higher temperatures (60°–130 °C) in high-salinity, high-hardness brines, the retention of synthetic polymers, especially those containing ATBS or NVP, in carbonate cores varied widely, ranging from 84 to 911 μg/g, with values around 200–300 μg/g being the most common.^{[94,96,98,100–102]}

4.5. Inaccessible pore volume

The observation of polymer molecules propagating through sandstones at a faster rate than salt ions in the solvent was documented by Dawson and Lantz in 1972. The observed variation was attributed to a specific fraction of the pore space that is impermeable to larger polymer molecules but accessible to smaller solvents, salt molecules, and ions. In their study conducted on 470-md Berea sandstone, it was found that HPAM (Pusher 700) exhibited a 22% inaccessible pore volume (IAPV), while Xanthan gum, tested on 681-md Berea sandstone, showed a 35% IAPV. Similar trends were observed in 2,090-md Bartlesville sandstone, where HPAM demonstrated a 24% IAPV. Additionally, He et al. (1990) provided supporting evidence through an analysis of the molecular weight distributions of HPAM effluent from cores, revealing that larger polymer molecules traverse porous media at a faster rate compared to smaller polymer molecules.^[103]

4.6. Effect of polymer concentration and Mw

The Langmuir isotherm assumes that polymer retention increases linearly with increasing polymer concentration at low values and reaches a plateau at higher concentrations. While most polymer-flood simulators adopt this assumption^[40] and only Szabo et al. provided experimental data to support it.^[43] However, several other studies report a weak or insignificant dependence of retention on polymer concentration.^[104]

In a study by Zhang et al., experiments were conducted using HPAM concentrations within a range of 10 to 6000 ppm., revealing three distinct regimes of retention behavior. Firstly, they observed a relatively stable and low retention level at low polymer concentrations (approximately 20 μg/g within the range of 10 to 100 ppm).^[32] Secondly, they noticed an increasing trend in retention at intermediate HPAM concentrations (reaching around 200 μg/g between 100 and 1000 ppm). Lastly, they noted relatively high and fixed retention at high HPAM concentrations. Wang et al. reported that HPAM retention in Milne Point core material was insensitive to polymer concentration and molecular weight.^[105] Similarly, in studies conducted with 9% illite in bead packs, Seright found little dependence of HPAM retention on polymer concentration and Mw, except at very low values (i.e. 200 ppm polymer or less than 2.7 million g/mol Mw).^[94]

5. Polymer injectivity issues

Addressing field-scale observations of polymer injectivity issues is crucial for optimizing polymer flooding operations in enhanced oil recovery projects. Techniques aimed at enhancing polymer injectivity are essential for overcoming these challenges and improving the efficiency of polymer flood in real-world applications.

The research by Torrealba, A., et al. introduces an innovative polymer flood injection scheme based on compositionally-tuned slugs.^[106] This approach involves cyclical injection of slugs with varying polymer concentrations to achieve low viscosity near the wellbore and high viscosity away from it. By optimizing slug mixing mechanisms, including polymer rheology, inaccessible-pore-volume, and adsorption, this scheme enhances sweep efficiency without compromising fluid injectivity. The study demonstrates that injecting compositionally-tuned polymer slugs with low viscosity near the wellbore preserves higher polymer injectivity, leading to improved sweep efficiency and incremental oil recovery compared to traditional continuous injection methods.

Similarly, Santoso et al. investigated the effectiveness of a polymer flooding scheme employing compositionally tuned slugs.^[107] Through reservoir simulations and design-of-experiments, they analyzed the impact of various reservoir and design parameters on recovery factor and injectivity. The study reveals that the slug-based process outperforms traditional continuous injection schemes, especially when polymer weight is high, enhancing polymer acceleration. Moreover, the process allows for increased polymer solution viscosity in the reservoir without impairing polymer injectivity at the well, offering a promising alternative to conventional polymer methods.

Furthermore, the work by Torrealba et al. emphasizes the importance of refining coarse history-matched waterflooding models for improving chemical-enhanced-oil-recovery simulations.^[108] By introducing a geostatistical downscaling method conditioned to tracer data, they refine coarse grids and populate relevant properties in finer grid blocks, reproducing fine-scale heterogeneity while retaining fluid material balance. This method reduces uncertainties in geological properties by integrating dynamic data such as sweep efficiency from interwell tracers, enhancing the accuracy of chemical enhanced oil recovery simulations, and optimizing polymer flood operations.

In summary, these studies highlight the significance of innovative techniques, such as compositionally tuned slugs and geostatistical downscaling, for enhancing polymer injectivity and optimizing polymer flood performance in enhanced oil recovery projects. By addressing field-scale observations and refining simulation models, these techniques offer practical solutions for overcoming injectivity limitations and improving the efficiency of polymer flood in real-world applications. Incorporating these advancements into field practices can lead to enhanced sweep efficiency, reduced chemical usage, and increased incremental oil recovery, ultimately maximizing the success of enhanced oil recovery projects.

6. Prospects and challenges

In addition to the aforementioned challenges regarding polymer retention, which poses a significant threat to the application of chemical-enhanced oil recovery (EOR) methods, there are other obstacles that need to be addressed. One major challenge is the cost associated with the chemicals used in oil recovery. The expenses involved in acquiring and utilizing these chemicals can be substantial.

Furthermore, the application of chemical EOR techniques can lead to formation damage in the subsurface. This refers to the negative impact caused by the retention or reaction of polymers within the reservoir rock system. The presence of formation damage poses a risk to the efficiency of oil recovery and can create technical and cost-related complications in oil field operations and facilities.^[109] Similarly, the accumulation of polymer molecules can occur due to hydrodynamic retention, mechanical entrapment, adsorption, and the presence of an inaccessible pore volume caused by polymer flocculation under high salinity conditions. This accumulation can eventually lead to the obstruction of rock grain surfaces, a phenomenon known as particle filtration which typically takes place in rock pores with smaller diameters.^[109]

Addressing these challenges and finding effective solutions will be crucial for the successful application of chemical EOR methods in oil recovery operations. It requires further research and development efforts to optimize the use of chemicals, mitigate formation damage, and overcome the drawbacks related to polymer flooding.

In addressing the challenge of excessive chemical adsorption onto rock pores during chemical-enhanced oil recovery (cEOR) methods, the utilization of adsorption inhibitors, also called sacrificial agents, has garnered significant attention and is suggested for practical implementation, especially in reservoirs with high temperatures and salinity levels.^[110] The effectiveness of sacrificial agents in chemical EOR can be attributed to various mechanisms. Firstly, these agents form complexes with different ions found in the high-salinity brine, reducing the availability of cations for interacting with the chemicals present in the reservoir fluids. Secondly, there is competition between the chemicals and sacrificial agents for the adsorption sites on the rock pores. The sacrificial agents, characterized by high surface coverage and low desorption, tend to be preferentially adsorbed onto the rock surface. Lastly, the sacrificial agents efficiently obstruct the access of injected chemicals to other adsorption sites due to their extensive surface coverage.^[21]

The detrimental impact of high-hardness brines in the reservoir on the performance of injected chemicals for enhanced oil recovery has been acknowledged by researchers. To address this issue, a reservoir conditioning process, involving the injection of a water slug known as a preflush, has been identified. The objective of the preflush is to specifically target and minimize the presence of hardness brines in the reservoir before the implementation of chemical EOR techniques. However, careful design of the preflush process is crucial to determine the optimal composition for effective preflushing. Several key factors are taken into consideration during the design phase, including the total dissolved solids content of the field, the composition of the field brine, chemical concentration, size of the chemical slug, preflush concentration, and size of the preflush slug.^[111,112]

To optimize the economic feasibility of enhanced oil recovery processes, it is crucial to prioritize research and development efforts toward the formulation of cost-effective and efficient EOR chemicals utilizing waste materials and by-products. For example, fly ash, a waste generated from coal-fired power plants, can be utilized to derive nanoparticles for nanofluid-based EOR applications.^[113] Furthermore, the synthesis of graphene and carbon nanotubes from palm kernel shell, a by-product of palm oil refining, is proposed as a promising avenue for future exploration in the field.^[21]

7. Conclusion

In conclusion, this comprehensive review emphasizes the significance of comprehending polymer retention in reservoir rocks within the realm of chemical-enhanced oil recovery (cEOR) techniques. The mechanisms of polymer adsorption, hydrodynamic retention, and mechanical entrapment play a pivotal role in determining the extent of polymer loss during the oil recovery process. Factors such as rock surface properties, polymer characteristics, and injection conditions profoundly influence the degree of polymer retention. Minimizing polymer retention is crucial for achieving higher oil production efficiency and economic viability in cEOR projects, as excessive retention can lead to significant production delays and formation damage. Therefore, careful polymer selection, optimization of injection parameters, and the development of appropriate reservoir engineering techniques are imperative for reducing polymer retention and enhancing oil recovery efficiency.

This review also discussed various measurement techniques employed to quantify polymer retention, including static and dynamic measurements. A profound understanding of the mechanisms of polymer retention and effective measurement techniques is a critical step toward devising more efficient oil recovery strategies. Further research and development are necessary to gain deeper insights into the factors influencing polymer retention to achieve optimal oil recovery rates. Advancements in understanding rock surface properties, polymer–rock interactions, and flow conditions can offer valuable insights for developing improved methods to mitigate polymer retention. Collaboration among researchers, engineers, and industry stakeholders is paramount to achieving these objectives. By optimizing polymer flooding strategies and mitigating polymer retention in reservoir rocks, the potential for increased oil production and economic viability in cEOR projects can be realized.

Additional information

Funding

This publication is based upon work supported by the KFUPM-KU Joint Research Program. The author(s) at KFUPM would like to acknowledge the support received under grant # KU201001. The author(s) at Khalifa University acknowledge the support received under award # KFUPM-KU-2020-14.