Enhanced Oil Recovery Processes Research Articles

Experimental investigation and machine learning modeling of diethylenetriaminepentaacetic acid agents in sandstone rock wettability alteration: Implications for enhanced oil recovery processes

Chelating agents have garnered increasing attention due to their unique capabilities in addressing challenges associated with chemical enhanced oil recovery (CEOR) materials. This research investigates the transformative potential of diethylenetriaminepentaacetic acid (DTPA) chelating agent in altering sandstone rock wettability. Wettability and zeta potential measurements were used to assess the impact of crucial factors including DTPA concentration, salinity, and potential determining ions (PDIs) on contact angle and rock surface charges. The findings revealed that there is an optimal level for DTPA concentration and salinity that can shift rock wettability from an oil-wet to strongly water-wet state. Moreover, while PDIs in their natural concentrations had no significant impact on DTPA performance, a threefold increase in their concentration was found to adversely affect DTPA efficacy. After conducting rock wettability tests, two advanced machine learning (ML) techniques, namely Random Forest (RF) and Boosted Regression Tree (BRT), were employed to assess rock/oil contact angle based on the aforementioned factors. Data were collected from 240 experimental datasets of contact angles. The findings indicated that both models performed well, but BRT exhibited exceptional performance. Sensitivity analysis, conducted using the Jackknife method, revealed the order of importance for parameters affecting wettability as follows: PDIs > salinity > time > DTPA concentration.

Developing statistical and machine learning models for predicting CO2 solubility in live crude oils

CO2 solubility in crude oil primarily affects the viscosity and swelling capacity of oil and determines the displacement efficiency of CO2 flooding during the enhanced oil recovery process. Dissolution of CO2 into crude oil also ensures safe and permanent storage of CO2 in depleted formations via solubility trapping. This study employed statistical and machine learning algorithms to develop precise and stable predictive models for estimating CO2 solubility in crude oils with dissolved gas. Recognizing the limitations of existing experimental data on CO2 solubility for live oils (crude oils with dissolved gas), we introduced a novel approach employing statistical and machine learning techniques for developing accurate and robust predictive models. Our methodology combined regularization, k-fold cross-validation, and statistical significance tests to ensure the robustness of the models, practices not considered in the previous studies. A linear regression model with L2 regularization is developed as the base model and compared with a 2nd order polynomial model and an ensemble feed-forward neural network (FNN) model integrated with gradient boosting (GB). The incorporation of GB into the neural network capitalizes on the additive sequence of FNN models, thereby enhancing the accuracy and reliability of predictions. Moreover, an improved user-accessible and easily implementable correlation is proposed to estimate CO2 solubility in live crude oils at diverse operating conditions as a function of reservoir temperature, saturation pressure, bubble-point pressure, oil molecular weight, and specific gravity. The performances of the developed model and the correlation are compared against the literature models and correlations. The FNN model with an overall R2 score of 0.9978, average absolute relative deviation (AARD) of 1.54 %, and root mean squared error (RMSE) of 0.0083 outperformed the previously published models and correlations. The new correlation, while being relatively simpler than previously published correlations, showed similar predictive performance with an overall R2 score of 0.9817, AARD of 4.98 %, and RMSE of 0.0225. The model and the correlation can be used to estimate CO2 solubility in live crude oils with 0.67 to 0.97 specific gravity for reservoir temperatures and pressures in the range of 28 to 124 °C and 3.23 to 32.76 MPa, respectively.

Using polymer-alternating-water to maximize polymer flooding performance

AbstractPolymer flooding has proved an effective technique to improve development efficiency in heterogeneous reservoirs. Previously, operators usually employed continuous injection of large polymer slugs. However, problems existed including premature injection profile reversal during development, ineffective circulation of polymer solution in low-permeability zones, and excessive polymer consumption in the late development stage. The paper proposed a combination method, named as polymer-alternating-water (PAW), to solve the issues of traditional polymer flooding. The characteristic of this method is injecting water slugs between polymer slugs during the polymer flooding process. At present, research on the PAW technique is limited, with the operational parameters, oil recovery mechanisms, and applicability under various reservoir conditions remaining unclear. In this work, a numerical polymer flooding model is developed using the commercial CMG-STARS reservoir simulation module to investigate the oil displacement performance of PAW. Numerical simulations are performed to determine the optimal parameters for maximizing oil recovery factor. The results indicated compared with continuous polymer flooding, PAW shows multiple peaks in daily oil production rate, with a significantly decreased decline rate, resulting in a 1.47% increase in recovery factor. Under different reservoir conditions including mean permeability, heterogeneity, and crude oil viscosity, PAW can achieve further improvements on the basis of continuous polymer flooding. Polymer adsorption and injection concentration significantly impact the recovery factor, requiring further optimization for field applications. In this study, better polymer flooding performance was achieved when the number of alternating cycles of PAW was 2, and the injected alternating water slug volume was 50%. This study contributes to a deeper understanding of the key mechanisms and parameters in PAW enhanced oil recovery process, thereby providing guidance for the further optimization and field application of this technique.

A comprehensive review direct methods to overcome the limitations of gas injection during the EOR process

Among the Enhanced Oil Recovery (EOR) methods, gas-based EOR methods are very popular all over the world. The gas injection has a high ability to increase microscopic sweep efficiency and can increase production efficiency well. However, it should be noted that in addition to all the advantages of these methods, they have disadvantages such as damage due to asphaltene deposition, unfavorable mobility ratio, and reduced efficiency of macroscopic displacement. In this paper, the gas injection process and its challenges were investigated. Then the overcoming methods of these challenges were investigated. To inhibit asphaltene deposition during gas injection, the use of nanoparticles was proposed, which were examined in two categories: liquid-soluble and gas-soluble, and the limitations of each were examined. Various methods were used to overcome the problem of unfavorable mobility ratio and their advantages and disadvantages were discussed. Gas-phase modification has the potential to reduce the challenges and limitations of direct gas injection and significantly increase recovery efficiency. In the first part, the introduction of gas injection and the enhanced oil recovery mechanisms during gas injection were mentioned. In the next part, the challenges of gas injection, which included unfavorable mobility ratio and asphaltene deposition, were investigated. In the third step, gas-phase mobility control methods investigate, emphasizing thickeners, thickening mechanisms, and field applications of mobility control methods. In the last part, to investigate the effect of nanoparticles on asphaltene deposition and reducing the minimum miscible pressure in two main subsets: 1- use of nanoparticles indirectly to prevent asphaltene deposition and reduce surface tension and 2- use of nanoparticles as a direct asphaltene inhibitor and Reduce MMP of the gas phase in crude oil was investigated.

New models for estimating minimum miscibility pressure of pure and impure carbon dioxide using artificial intelligence techniques

CO2 miscible flooding stands out as one of the most-commonly employed and promising processes in enhanced oil recovery. The key factor for ensuring success in designing and executing CO2 injection projects lies in the precise determination of the Minimum Miscibility Pressure (MMP). Despite significant research endeavors in measuring and predicting the MMP through the use of empirical, analytical, numerical, and experimental approaches, the need for a comprehensive, accurate, efficient, and easy-to-use model remains. In response to this gap, our study developed various predictive models with 205 datasets, including well-established ones such as Artificial Neural Network (ANN), Random Forest (RF), and K-Nearest Neighbors (KNN) along with employing the Gradient Boosting Algorithm (GBA) with the Grid Search (GS) as a novel approach to predict the MMP of both pure and impure CO2. The performance of these models was validated by comparing them with previously published models, using relevant performance metrics such as R2 (coefficient of determination) and MAPE (mean absolute percentage error). Our results demonstrated that the GBA model with GS optimization exhibited remarkable superiority in terms of performance and accuracy in both scenarios, outperforming previously published models as well as the developed ANN, RF, and KNN models. For pure CO2, it achieved an impressive R2 value of 0.999 on the training set and a relatively high value of 0.910 on the validation set. Additionally, the model showed remarkably low MAPE values of 0.0705 % on the training set and 9.238 % on the validation set. Similarly, for impure CO2, the GBA model with GS optimization achieved an R2 value of 0.999 on the training set and a relatively high value of 0.865 on the validation set. The model also exhibited low MAPE values of 1.66 % on the training set and 6.798 % on the validation set. These findings highlight the potential of the GBA model with GS optimization as a valuable approach for accurately estimating the MMP, offering a cost-effective and efficient approach for designing and optimizing CO2 flooding operations in enhanced oil recovery processes.

Assessment of Biopolymers Rheological Properties and Flooding Results Under Reservoir Conditions for Enhanced Oil Recovery Processes

Assessment of Biopolymers Rheological Properties and Flooding Results Under Reservoir Conditions for Enhanced Oil Recovery Processes

Chevron Applies Some Unconventional Thinking To Try To Make Shale EOR a Standard Treatment

In the shale business, the closest thing now to enhanced oil recovery (EOR) is improved techniques. During an earnings call last November an analyst asked EOG Resources executives about their enhanced completion technique which EOG reported was adding 20% to first-year well production in the Permian. Improved completions have allowed operators to significantly increase early production year after year, but after that, steep declines are a given. Back in 2016, EOG was talking about how it was increasing oil production significantly by injecting millions of cubic feet of gas a day into wells in the Eagle Ford. It triggered an EOR field-testing boom by competitors hoping to match reported reserve increases of “30 to 70%.” In a 2017 JPT story, Deepak Devegowda, a petroleum engineering professor at the University of Oklahoma, said, “This is the name of the game. Everybody is talking about EOR and pumping money into trials of EOR.” Now the only mention of the acronym EOR on EOG’s website is an item in its corporate history timeline for 2016: “We commercialized the first enhanced oil recovery process, or EOR, in shale.” In recent years, reported shale EOR work has been mostly in the form of occasional papers describing production uplift by companies selling ways to increase production by injecting gas or chemicals. EOR effectiveness isn’t the issue, according to Todd Hoffman, a petroleum engineering professor at Montana Tech University who wrote two papers evaluating EOG’s methods cited in two Chevron papers. “The EOG field work showed us that these projects can produce significant additional oil and be economically positive,” he said. The problem is that drilling and fracturing wells delivers “higher economic returns than the EOG-style EOR projects with the huge compressors, high gas rates, and high injection pressures.” Last year in the middle of this EOR drought, Chevron did something different. It delivered two papers revealing a major company-scale effort to find ways to use chemical and gas injections to economically produce more oil. The papers presented at the 2023 Unconventional Resources Technology Conference (URTeC) reported on field tests of surfactants and natural gas injection on Permian Basin wells which delivered sufficiently encouraging results to justify an expanded testing program. (URTeC 3870505 and URTeC 3871386). Chevron described a systematic effort by its corporate technical unit and its Mid-Continent business unit to rethink shale EOR methods based on the unconventional nature of flow through fractured reservoirs and the economic realities in a business where new EOR technology is competing with the profitable status quo. Its methods challenge accepted notions about the role of EOR. In SPE’s disciplines, EOR normally falls under the production topic, “marginal aging fields.” What Chevron tested is better described by the topic, “well interventions.” Rather than looking at these techniques as a way to eke out the last barrels from old wells, the papers describe methods that can be deployed earlier in the life of these short-lived wells.

Molecular Dynamics Simulations of Supramolecular Polymers within Nanoconfinements for Enhanced Oil Recovery.

Supramolecular polymers offer promising potential for enhanced oil recovery (EOR) advancing techniques. Current instrumental analyses face limitations in capturing instantaneous intracomplex motions due to temporal and spatial constraints. The molecular mechanism of supramolecular polymer transport behavior within nanoconfinement is not yet fully understood. Therefore, the self-assembly mechanism of β-cyclodextrin (β-CD) and adamantane (ADA)-modified supramolecular polymers (p-AA-β-CD-ADA) was delved into in this work. Further exploration focuses on the translocation dynamics of p-AA-β-CD-ADA within nanoconfinement under external driving forces. Results suggest that β-CD and ADA in p-AA-β-CD-ADA were assembled into nodes in the form of a host and a guest, combining with a "node-rebar-cement" interaction model encapsulating the formation mechanism of these supramolecular polymers. The heightened density of the hydrate layers at the nanoscale pore throats acts as a constraining factor, resulting in restricted mobility and altered dynamics of the supramolecular polymers. During passage through nanopore throats, host-guest molecules within the supramolecular polymer experience noncovalent dissociation. Notably, these supramolecular polymers exhibit remarkable self-healing capabilities, reinstating their assembly state upon traversing pore throats. This work provides a molecular-level comprehension of the potential utility of supramolecular polymers in EOR processes, offering valuable information for the molecular design of polymers employed for EOR in low-permeability reservoirs.

New Trends in Biosurfactants: From Renewable Origin to Green Enhanced Oil Recovery Applications.

Enhanced oil recovery (EOR) processes are technologies used in the oil and gas industry to maximize the extraction of residual oil from reservoirs after primary and secondary recovery methods have been carried out. The injection into the reservoir of surface-active substances capable of reducing the surface tension between oil and the rock surface should favor its extraction with significant economic repercussions. However, the most commonly used surfactants in EOR are derived from petroleum, and their use can have negative environmental impacts, such as toxicity and persistence in the environment. Biosurfactants on the other hand, are derived from renewable resources and are biodegradable, making them potentially more sustainable and environmentally friendly. The present review intends to offer an updated overview of the most significant results available in scientific literature on the potential application of biosurfactants in the context of EOR processes. Aspects such as production strategies, techniques for characterizing the mechanisms of action and the pros and cons of the application of biosurfactants as a principal method for EOR will be illustrated and discussed in detail. Optimized concepts such as the HLD in biosurfactant choice and design for EOR are also discussed. The scientific findings that are illustrated and reviewed in this paper show why general emphasis needs to be placed on the development and adoption of biosurfactants in EOR as a substantial contribution to a more sustainable and environmentally friendly oil and gas industry.

In-situ emulsification in low-tension surfactant/polymer systems: Impacts on enhanced oil recovery

The flow of two immiscible liquids in porous media can lead to fluid mixing, resulting in emulsions—where one phase is dispersed as droplets in the other. In reservoir rocks, natural surfactants and polar molecules, like asphaltenes, can promote oil–water emulsion formation. During chemically enhanced oil recovery processes (CEOR) such as surfactant, alkali, or surfactant-alkali flooding, in-situ emulsification is often seen as key to enhancing frontal stability and facilitating the piston-like displacement of oil by water. However, this work reports a minimal effect of in-situ emulsification on oil production during surfactant-polymer (SP) flooding. Experimental studies show this by injecting prepared emulsions into a multi pressure-tap core holder and examining emulsion formation in one reservoir core before moving it into a second core for oil displacement. This helps us understand the specific role of emulsions in oil mobilization. Factors like surfactant concentration, interfacial tension, and the timing of introducing the surfactant-polymer solution do influence the intensity of in-situ emulsification. Yet, the incremental oil recoveries show no significant differences. Through similar experiments, it is observed that ultra-low interfacial tension (IFT) in our surfactant-polymer system is the primary mechanism for oil mobilization. The slight increase in pressures suggests that in-situ emulsification has a limited role in increasing flow resistance during the ultra-low IFT SP flood process, potentially not improving the swept volume. This research can guide the development of systematic approaches to analyze the effects of in-situ emulsification on oil mobilization and evaluate chemical flooding processes.

Advanced polymer‐based surfactant for improved heat and salinity stability in enhanced oil recovery processes

AbstractEnhancing oil recovery through surfactants has proven to be a successful strategy in recent times. However, traditional surfactants have their limitations, particularly in terms of stability under high temperatures and salinity levels. This study delved into a groundbreaking macromolecular polymeric surfactant, S‐AV, which holds the unique ability to transform rock surface characteristics, effectively stripping away residual oil while maintaining resilience against elevated temperatures and salinity. S‐AV was synthesized through a free‐radical copolymerization process, incorporating benzyl, perfluoroalkyl, alkyl‐, benzyl‐, ethylene glycol, and amide‐alkyl‐sulfonate groups, ultimately yielding a comb‐like molecular structure. S‐AV demonstrated exceptional prowess, swiftly reducing the underwater oil contact angle to 53.4° in just 48 h. This synthesized surfactant also retained its phase stability up to salinity levels of 36,000 ppm, with temperature having no disruptive impact on its phase stability performance. Furthermore, S‐AV showcased remarkable viscosity reduction in conditions of high temperature and salinity. The core flooding experiments underscored the potential of S‐AV, as its injection led to a significant oil recovery rate of up to 83%. These findings position S‐AV as a promising candidate for practical enhanced oil recovery applications.

Technology Focus: EOR Modeling (January 2024)

The oil and gas industry is at a critical juncture in addressing the pressing need to balance operational efficiency with environmental stewardship. With the world’s growing emphasis on climate change and sustainability, the industry is tasked with the dual objectives of refining operational efficiency and simultaneously diminishing its carbon footprint. This balancing act has become a strategic imperative crucial for the long-term viability of the industry. In light of the recent COP28 agreement, which emphasizes a “swift, just, and equitable energy transition,” the role of low-emission enhanced oil recovery (EOR) and operational optimization becomes increasingly significant. This period of transition, which may span several decades, demands a pragmatic approach where the existing hydrocarbon resources are used as efficiently and responsibly as possible. In the quest to optimize operations and reduce carbon footprint, three innovative technical papers present a cohesive story of advancement through modeling and machine learning. These papers underscore the industry’s shift toward more efficient practices, each contributing a crucial piece to the larger puzzle of EOR.The first paper introduces an advanced modeling approach for fractured reservoirs, a significant development in tight rock simulations that simplifies fracture heterogeneity characterization and enhances computational efficiency, crucial for optimizing asset development decisions in shale and tight oil resources. Building on the theme of efficiency, the second paper pivots to the realm of surfactants, exploring their role in wettability alteration within unconventional liquid-rich reservoirs. This research provides a systematic approach for screening thermally stable surfactants under reservoir conditions, crucial for improving hydrocarbon recovery without unnecessary field trials. The final piece of this narrative is a study using machine learning to predict gas-injection parameters in EOR processes. This approach addresses the lack of extensive gas-injection laboratory data, demonstrating the power of data-driven predictions in enhancing operational efficiency and decision-making. These papers weave a compelling narrative of technological innovation, highlighting the role of advanced modeling and machine learning. As the oil and gas industry progresses in its vital mission to supply the world’s energy needs, the pivotal role of technology innovation becomes increasingly evident. Advanced technologies focused on operational optimization and reducing carbon emissions are essential in reinforcing the industry’s adaptability and resilience in the context of this rapidly evolving energy landscape. Recommended additional reading at OnePetro: www.onepetro.org. SPE 215083 An Analytical Tool to Predict Fracture Extension and Elastic Desaturation for Polymer Field Projects by M.B. Abdullah, The University of Texas at Austin, et al. SPE 216822 First Pilot Design of Low-Tension-Gas (LTG) Flooding in Carbonate Field in North Oman by Mohammed Al-Abri, Petroleum Development Oman, et al. SPE 213037 Field-Scale Multistage and Multiobjective Optimization of Rate and Concentration for Polymer Flooding by Ruxin Zhang, Texas A&M University, et al.

The Influence of Pineapple Skin Eco-Enzyme on The Formation of Middle Phase Emulsion in Enhanced Oil Recovery Implementation

Oil requirement is constantly experiencing escalation, although at the current situation, the supply still depended on fossil and non-renewable fuel sources. The volume of crude oil production, especially in older wells, is starting to decrease. That is why, Enhanced Oil Recovery (EOR) method in form of chemical injection with surfactant is currently developed. The study aims to provide understanding on the influence of pineapple peel eco enzyme concentration in the formation of middle phase emulsion in EOR process. The method used in this research is a laboratory study of pineapple skin eco-enzyme as surfactant solution on brine with 20,000 ppm and 40,000 ppm sanities. The concentration levels of pineapple skin eco-enzyme surfactant were at 20%, 30%, and 40%. Phase behavior test was conducted on pineapple skin eco-enzyme with varied levels of salinities and concentrations. The middle phase emulsion test was conducted at 60°C. Middle phase emulsion test results for 20,000 ppm salinity produced 2.5% middle phase in all concentration variations (20%, 30%, and 40%). Meanwhile for 40,000 ppm brine salinity, 1.25% of middle phase was found at 20% and 40% concentration, however at 40% concentration, the middle phase was at 6.25%. The phase behavior test results show that the highest level of middle phase emulsion formation was at 40,000 ppm salinity and 30% concentration (6.25%). Based on the finding, we can conclude that eco-enzyme can be utilized as surfactant due to its ability to form a stable middle phase emulsion on certain levels of concentration and salinity.

Modeling and semi-analytical solution for immiscible and miscible fingers formation during enhanced oil recovery

ABSTRACT The fingering phenomenon arises during the secondary and tertiary oil recovery processes when injected fluid (water, gases, nano/biomaterials, or polymer particles) shoots through a porous medium at a relative speed. Oil recovery is influenced by various factors including the fluid type, capillary pressure, permeability, and porous material structure. All these elements play crucial roles in determining the success and efficiency of the oil recovery process. Many scientists have debated the fingering phenomenon from different perspectives. Here, we developed mathematical models with and without considering mass flow rates of oil and water for an inclined oil layer flowing through a homogenous porous medium to generate immiscible fingers. Furthermore, a mathematical model of miscible viscous finger formation with carbonated water injection (flooding) during the enhanced oil recovery process (EOR) has been analyzed in this paper. To solve each of these mathematical models, we used the recently developed approach known as the Method of Directly Defining the inverse Mapping (MDDiM). We found approximate solutions to the nonlinear partial differential equations (PDEs), which describe each modeling of the fingering phenomenon in a homogeneous porous medium by incorporating gravitational effects for several types of flooding and discussed the effects of the saturation rate.

Stability Evaluation of Nanofluids Suitable for Enhanced Oil Recovery

The evaluation of metal oxides nanoparticles stability in the base fluids has become a major aspect in enhanced oil recovery process in recent years. Physical and chemical properties of ZnO nanofluids have caught attention of many researchers because they are easily dispersed in the base fluids, better convective coefficient of heat transfer, and wider bandgap which make them remarkable nanofluids candidate compared to other metal oxides. In this study, the stability of nanofluid of zinc oxide nanoparticles was evaluated using different stability tests and analysis. However, ZnO nanoparticles were synthesized using sol-gel method and nanofluids of different concentrations were prepared. The prepared nanoparticles were characterized using various characterization techniques such as XRD, FTIR, TEM, and Zeta sizer. The stability of prepared nanofluids was investigated using sedimentation test, UV-vis spectrophotometer, and zeta analyzer. Based on physical investigation and UV-vis spectra observations, ZnO nanoparticles in base fluids have shown a good colloidal stability in addition to their high zeta potential values of-43.7 (mV) after seven days which makes it a successful potential candidate for enhanced oil recovery applications.

Impact of Injection Gas on Low-Tension Foam Process for EOR in Low-Permeability Oil-Wet Carbonates

Low-tension gas (LTG) flooding has been proven in lab-scale experiments to be a viable tertiary enhanced oil recovery (EOR) technique in low-permeability (~10 mD) oil-wet carbonates. Work carried out previously almost exclusively focused on water-wet cores. The application of LTG in oil-wet carbonates is investigated in this study along with the impact of a hydrocarbon (HC) mixture as the injection gas on oil–water microemulsion phase behavior. The optimum injection gas fraction (ratio of gas injection rate to total injection rate of gas and water) for the hydrocarbon gas mixture in oil-wet carbonates regarding the oil recovery rate was determined to be 60% as it resulted in around 50% residual oil in place (ROIP) recovery. It was shown that proper mobility control can be achieved under these conditions even in the absence of strong foam. The effect of HC gas dissolution in oil was clearly shown by replacing the injection HC gas with nitrogen under the same conditions. Furthermore, the importance of ultra-low interfacial tension (IFT) produced by the injection gas and surfactant slug is proven by comparing injection at sub-optimum salinity to injection at optimum salinity.

Synergistic effect of graphene oxide and partially hydrolyzed polyacrylamide for enhanced oil recovery: Merging coreflood experimental and CFD modeling approaches

The present study provides a comprehensive examination of GO-HPAM polymeric nanocomposite, contributing significantly to enhanced oil recovery (EOR). At the core of this investigation are a series of experimental tests and validations of simulations. The study examines the bonding effects, structural integrity, morphological interconnections, and stability of the GO-HPAM. The significance of reservoir and in-situ fluid conditions in the effort to improve EOR The GO-HPAM stabilization composite was developed, assessed, and examined for its extended core-flooding capabilities owing to its high energy characteristics. The simulation model was built on a Cartesian grid with fixed values for the bulk volume, injection rate, well completion, and rock-fluid properties using ANSYS Fluent. During the flooding experiment, the injections of 2 PV of brine, 0.50 PV of GO-HPAM, and 2 PV of chase water were precursors. The findings showed that 19.67% of the original oil could be recovered after injecting the nanocomposite fluid consisting of GO-HPAM. The GO-HPAM flooding gathered over 60% more oil than the traditional EOR polymer. Moreover, numerical modeling demonstrated a performance of the GO-HPAM combination comparable to the experimental results. The proposed synergetic fluid will assist researchers and industrialists in the design of an EOR process.

Molecular insights into the synergistic mechanisms of hybrid CO2-surfactant thermal systems at heavy oil-water interfaces

A hybrid thermal recovery process is a promising EOR (Enhanced Oil Recovery) method and has been widely applied to post-steamed heavy oil reservoirs. Due to the complexity of High Temperature and High Pressure (HTHP) reservoir environments, Molecules Dynamics (MD) simulations are conducted to investigate the interfacial behavior between multiphase multicomponent fluids and heavy oil over a wide temperature range. We select CO2 and a cost-effective anionic surfactant, SDS (Sodium Dodecyl Sulfate), to build hybrid thermal systems. The interfacial behavior in different systems is characterized by the local density distribution, cluster analysis, hydrogen bond characters, solvent accessible surface area, and interaction energy. Systematic MD simulations reveal a two-step interfacial tension (IFT) reduction process stimulated by thermal migration. Both CO2 and SDS can achieve an IFT decrement with different mechanisms. Moreover, a co-addition of CO2 and SDS can further efficiently reduce the IFT. Average Reduced Density Gradient (aRDG) results reveal that a unique asphaltenes-SDS-CO2 structure improves the interfacial activities and mobility of the heavy oil phase through a bidirectional mass exchange mechanism, which ultimately realizes the most significant IFT decrement. Furthermore, an optimal concentration (10C–20S) in a hybrid thermal system is recommended because of its balanced performance. This work sheds insight into the synergistic effects of multiphase multicomponent thermal fluids on hybrid thermal systems, which will guide future field applications of hybrid thermal EOR processes.

Study Evaluates CO2 Storage Potential During CO2 Mobility-Control Optimization

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 212969, “Evaluation of CO2 Storage Potential During CO2 Mobility-Control Optimization for Enhanced Oil Recovery,” by Alvinda Sri Hanamertani, SPE, Ying Yu, SPE, and Omar El-Khatib, SPE, University of Wyoming, et al. The paper has not been peer reviewed. _ CO2 mobility control through foam technology has enabled better sweep efficiency and, consequently, better oil productivity during enhanced oil recovery (EOR) processes. Along with enhancing oil production, a sound potential exists for in-situ generated foam to enhance CO2 storage. However, the effect of the different in-situ foam generation strategies on the combined goal of maximum oil production and carbon storage is not well elucidated in the literature. In the complete paper, the authors methodically evaluate the simultaneous optimization of CO2 storage and oil recovery using multiple injection strategies. Introduction The current investigation is a continuation of two previous studies that provided a methodology for screening and using foaming agents for optimized CO2 storage in sandstone and carbonate formations. A base case of tertiary CO2 flooding was established for comparison with in-situ foam generation by two approaches: single-cycle surfactant-alternating-gas (SAG) flooding and coinjection of CO2 and surfactant. Additionally, the effect of surfactant concentration on foam efficiency, CO2 storage capacity, and oil recovery were evaluated in both approaches at reservoir conditions. Materials and Methods Fluids and Porous Medium. In this study, a synthetic brine with total dissolved solids of 20 wt% was used as blank brine and laden with a commercial zwitterionic surfactant that was used to prepare surfactant solutions with concentrations of 0.5 and 1 wt% active matter in the synthetic brine. Three core plugs were drilled from an Indiana limestone outcrop block. The cores were then cleaned and oven-dried at 95°C. Experimental Procedure. Vacuum saturation with brine was commenced for the three cores. The porosity of the cores was calculated using their dry and brine-saturated weights. Then, the 100% brine-saturated core was placed in a core holder and loaded into an oven set to 90°C. The pore pressure was fixed at 2,000 psi, and the confining pressure was controlled at 3,000 psi throughout the flooding experiment. The brine permeability of the core samples was evaluated by measuring the pressure drop across the core at different brine-injection flow rates. In the first experiment (IL1), oil drainage with a flow rate of 0.2 cm3/min was performed to establish irreducible water saturation of 46.9%. This total flow rate was kept the same throughout the three experiments. Then, a waterflooding stage was begun and the oil recovery was recorded. After reaching a plateau in oil recovery, supercritical CO2 (scCO2) was injected during the EOR process until the oil production plateaued.

Molecular insights of condensate trapping mechanism in shale oil reservoirs and its implications on lean gas enhanced oil recovery

The heterogeneous pore structure and the confinement effect of the narrow pore space lead to the differential release/retention phenomenon of hydrocarbons in unconventional reservoirs. So far, the mechanism of this phenomenon, in particular the dynamic process, requires further investigation since it affects the design of gas-based enhanced oil recovery (EOR) operations. In this work, we aim to numerically study the capillary condensate trapping mechanism that causes the differential release phenomenon by conducting molecular dynamics (MD) simulations.In our work, a two-bath MD model is set up, in which two baths are used to mimic the bulk pores and a nano-channel connecting the two baths is used to model the pore throat. Methane (C1) and decane (C10) molecules are used to represent the light and heavy component of the in-situ oil. The MD results show that at the early stage of the primary depletion, the light components release faster than the heavier components, leading to increasing gas oil ratio (GOR) above the system’s bubble point. As depletion continues, heavier hydrocarbons accumulate in the nano-channel due to the confinement effect, while light hydrocarbons tend to remain in the dead-end pores. During the gas EOR process, the injected gas ‘dissolves’ the liquid in the nano-channel and thus enhances the recovery of the ‘trapped’ hydrocarbons.This work systematically investigates the impact of pore throat on the differential release and trapping effect. We demonstrate that a significant amount of light hydrocarbons may be ‘trapped’ during the primary depletion of unconventional reservoirs, due to the capillary condensate trapping effect. The trapped hydrocarbons can be partly recovered through gas injection. Our study has implications for practical EOR operations.