Combining Thermal Effect and Mobility Control Mechanism to Reduce Water Cut in a Sandstone Reservoir in Kazakhstan.

The application of polymer flooding is currently under investigation to control water cut and recover residual oil from a giant sandstone reservoir in Kazakhstan, where the water cut in most producers exceeds 90%, leaving substantial untouched oil in the porous media. The primary objective of this research is to explore the feasibility of a novel approach that combines the mechanisms of mobility control by polymer injection and the thermal effects, such as oil viscosity reduction, by utilizing hot water to prepare the polymer solution. This innovative hybrid method's impact on parameters like oil recovery, resistance factor, and mobility was measured and analyzed. The research involved an oil displacement study conducted by injecting a hot polymer at a temperature of 85 °C, which is higher than the reservoir temperature. Incremental recovery achieved through hot polymer injection was then compared to the recovery by conventional polymer flooding and the conventional surfactant-polymer-enhanced oil recovery techniques. The governing mechanisms behind recovery, including reductions in oil viscosity, alterations in polymer rheology, and effective mobility control, were systematically studied to comprehend the influence of this proposed approach on sweep efficiency. Given the substantial volume of residual oil within the studied reservoir, the primary objective is to improve the sweep efficiency as much as possible. Conventional polymer flooding demonstrated a moderate incremental oil recovery rate of approximately 48%. However, with the implementation of the new hybrid method, the recovery rate increased to more than 52%, reflecting a 4% improvement. Despite the polymer's lower viscosity during hot polymer flooding, which was observed by the lower pressure drop in contrast to the conventional polymer flooding scenario, the recovery factor was higher. This discrepancy indicates that while polymer viscosity decreases, the activation of other oil displacement mechanisms contributes to higher oil production. Applying hybrid enhanced oil recovery mechanisms presents an opportunity to reduce project costs. For instance, achieving comparable results with lower chemical concentrations is of practical significance. The potential impact of this work on enhancing the profitability of chemically enhanced oil recovery within the sandstone reservoir under study is critical.

Experimental and data-driven analysis for predicting nanofluid performance in improving foam stability and reducing mobility at critical micelle concentration.

Application of surfactant-based foam flooding is an effective approach to reduce mobility and control early breakthrough. Despite the proper performance of surfactant-based foams in decreasing the channeling of the flooded gas and water, high pressure, high temperature, and high salinity of the reservoirs put some limitations on the foam flooding efficiency. Nanoparticles are used to improve the quality of the foams, enhance stability, and transcend the limitations. Although there are many benefits of using nanoparticles in foam flooding, their performance at surfactant critical micelle concentration (CMC) is not fully investigated and the optimum nanoparticle concentration is not specified. In this study, an experimental investigation using nanosilica with surfactants at CMC to improve the stability (half-life) and mobility reduction factor (MRF) has been conducted. Furthermore, data from the literature were collected and analyzed to evaluate the change in MRF and stability for a nanofluid-based foam at CMC. Both experimental results and literature data showed that application of nanofluid-based foam is a successful approach to develop a more stable foam with lower mobility. Nanoparticle (NP) concentration is the dominant parameter at different salinities and temperatures that affects foam flow through porous media. The range of 0.2-0.4 wt% is the optimum nanoparticle concentration to develop a strong foam with acceptable performance in controlling mobility.

Maximizing oil recovery: Innovative chemical EOR solutions for residual oil mobilization in Kazakhstan's waterflooded sandstone oilfield.

The results of an experimental study to design a chemical flood scheme for a massive Kazakhstani oilfield with high water cut are presented in this paper. A meticulously formulated chemical flooding procedure entails injecting a blend comprising interfacial tension (IFT) reducing agents, alkaline/nanoparticles to control chemical adsorption, and polymer to facilitate mobility control. Overall, this well-conceived approach leads to a significant enhancement in the mobilization and production of residual oil. Experiments were conducted in Kazakhstan's Field A, one of the country's oldest oilfields with over 90% water cut and substantial remaining oil, to assess the efficiency of various hydrolyzed polyacrylamide (HPAM) derived polymers and surfactant solutions. Additionally, the effectiveness of alkaline and nanoparticles in minimizing chemical adsorption for the screened surfactant and polymer was investigated. These assessments were conducted under reservoir conditions, with a temperature of 63 °C, and using 13,000 ppm Caspian seawater as makeup brine. The performance assessment of the selected chemicals was carried out through a set of oil displacement tests on reservoir cores. Critical parameters, including chemical adsorption, interfacial tension, resistance factor, and oil recovery factor, were compared to determine the most effective chemical flooding approach for Field A. Both the surfactant-polymer (SP) and alkali-surfactant-polymer (ASP) approaches were more successful in recovering residual oil by efficiently generating and delivering microemulsion, producing more than 90% of the remaining oil after waterflooding. Due to the low increase in recovery compared to SP and the complexity of applying ASP at the field scale, SP was recommended for the pilot test studies. This investigation underscores that the choice of chemicals is contingent upon the interplay between the specific characteristics of the oil, the geological formation, the injection water, and the reservoir rock. Consequently, assessing all potential configurations on reservoir cores is imperative to identify the most optimal chemical combination. The practical challenges at the field scale should also be considered for the final decision. The results of this study contribute to the successful design and implementation of tailored chemical flooding to challenging oilfields with excessive water cut and high residual oil.

Enhanced oil recovery by using modified ZnO nanocomposites in sandstone oil reservoirs.

Recently, nanocomposites were employed to improve the extraction of oil in different reservoirs. Due to the unique characteristics of nanoparticles such as small size, efficient altering main mechanisms such as IFT, CA, and viscosity reduction, have received wide attention among researchers. This study investigated the application of a newly designed ZnO-cerium N-composite for EOR at reservoir conditions, and the performance was compared to the standalone ZnO nanoparticles. After performing the morphology of the N-composite, the effect of the N-composites on the wettability alteration, interfacial tension, viscosity, Zeta potential, pH, and density was studied at different N-composites concentrations at reservoir conditions. Based on the results of rock/fluid interactions at the static phase, an optimum concentration was chosen for performing dynamic core flooding experiments. At 100 ppm, the highest stability and the highest reduction in capillary force were observed. The presence of Ce in the structure of the N-composite changes the pore volume of ZnO-Ce compared to ZnO nanoparticles, which affects the surface charge. IFT (mN/m), CA (°), and zeta potential (mV) were (22.51, 40.83, and - 44.36), and (30.50, 50.21, and - 31.05) for ZnO-Ce and ZnO, respectively at 100 ppm. By application of the optimized nanofluid in an oil displacement study, RF in the presence of ZnO-Ce, and ZnO were 37.11% and 71.40%, respectively.

Impact of the Naturally Driven Surfactant in EOR Application: Experimental, Microscopic, and Numerical Analyses.

While synthetic, conventional surfactants have a known negative environmental impact, their high cost poses a significant challenge. In contrast, naturally extracted surfactants are cheaper and are readily available. The applicability of natural surfactants depends on the saponin concentration, extraction, and synthesis methods. Certain parameters, such as their efficiency in obtaining the required interfacial tension (IFT) values, salinity tolerance, and stability under reservoir conditions, must be examined. Kazakhstan produces a substantial quantity of flaxseed, and flaxseed oil is a good source of fatty acids that can be converted to natural surfactants. Therefore, the work aims to identify the potential of the natural-flaxseed oil surfactant. The experimental study evaluated the synthesized surfactant, effective concentration, salinity's effect, interfacial tension, rheology, and oil recovery concerns in vugs limestone. A microscopic study was conducted to provide insight into the flow in the vugus matrix. At the same time, the numerical method was also employed to establish a potential recovery understanding. The Fourier spectrometer results proved the distinct presence of the triterpenoid. The critical micelle concentrations are 6 and 2.5 wt % for solution in 0 and seawater salinity, respectively. The IFT was reduced by 40-48% and is more effective in seawater solutions. The oil additional recovery was 39-50% after surfactants. The presence of a fractured vugus did not affect the success of the application. Despite the difficulty in modeling the system, the numerical results agree with the experiments and show only 7% differences in total recovery. The research offers novel natural surfactants that can be applied in offshore Kazakhstan.

Modeling crude oil pyrolysis process using advanced white-box and black-box machine learning techniques.

Accurate prediction of fuel deposition during crude oil pyrolysis is pivotal for sustaining the combustion front and ensuring the effectiveness of in-situ combustion enhanced oil recovery (ISC EOR). Employing 2071 experimental TGA datasets from 13 diverse crude oil samples extracted from the literature, this study sought to precisely model crude oil pyrolysis. A suite of robust machine learning techniques, encompassing three black-box approaches (Categorical Gradient Boosting-CatBoost, Gaussian Process Regression-GPR, Extreme Gradient Boosting-XGBoost), and a white-box approach (Genetic Programming-GP), was employed to estimate crude oil residue at varying temperature intervals during TGA runs. Notably, the XGBoost model emerged as the most accurate, boasting a mean absolute percentage error (MAPE) of 0.7796% and a determination coefficient (R2) of 0.9999. Subsequently, the GPR, CatBoost, and GP models demonstrated commendable performance. The GP model, while displaying slightly higher error in comparison to the black-box models, yielded acceptable results and proved suitable for swift estimation of crude oil residue during pyrolysis. Furthermore, a sensitivity analysis was conducted to reveal the varying influence of input parameters on residual crude oil during pyrolysis. Among the inputs, temperature and asphaltenes were identified as the most influential factors in the crude oil pyrolysis process. Higher temperatures and oil °API gravity were associated with a negative impact, leading to a decrease in fuel deposition. On the other hand, increased values of asphaltenes, resins, and heating rates showed a positive impact, resulting in an increase in fuel deposition. These findings underscore the importance of precise modeling for fuel deposition during crude oil pyrolysis, offering insights that can significantly benefit ISC EOR practices.

Unlocking the Power of Artificial Intelligence: Accurate Zeta Potential Prediction Using Machine Learning.

Nanoparticles have gained significance in modern science due to their unique characteristics and diverse applications in various fields. Zeta potential is critical in assessing the stability of nanofluids and colloidal systems but measuring it can be time-consuming and challenging. The current research proposes the use of cutting-edge machine learning techniques, including multiple regression analyses (MRAs), support vector machines (SVM), and artificial neural networks (ANNs), to simulate the zeta potential of silica nanofluids and colloidal systems, while accounting for affecting parameters such as nanoparticle size, concentration, pH, temperature, brine salinity, monovalent ion type, and the presence of sand, limestone, or nano-sized fine particles. Zeta potential data from different literature sources were used to develop and train the models using machine learning techniques. Performance indicators were employed to evaluate the models' predictive capabilities. The correlation coefficient (r) for the ANN, SVM, and MRA models was found to be 0.982, 0.997, and 0.68, respectively. The mean absolute percentage error for the ANN model was 5%, whereas, for the MRA and SVM models, it was greater than 25%. ANN models were more accurate than SVM and MRA models at predicting zeta potential, and the trained ANN model achieved an accuracy of over 97% in zeta potential predictions. ANN models are more accurate and faster at predicting zeta potential than conventional methods. The model developed in this research is the first ever to predict the zeta potential of silica nanofluids, dispersed kaolinite, sand-brine system, and coal dispersions considering several influencing parameters. This approach eliminates the need for time-consuming experimentation and provides a highly accurate and rapid prediction method with broad applications across different fields.

Polymer Screening for Efficient Water Cut Reduction in a Sandstone Oilfield in Kazakhstan.

Polymer flooding is one of the most widely used and effective enhanced oil recovery techniques. It can improve the macroscopic sweep efficiency of a reservoir by controlling the fractional flow of water. The applicability of polymer flooding for one of the sandstone fields in Kazakhstan was evaluated in this study and polymer screening was carried out to choose the most appropriate polymer among four hydrolyzed polyacrylamide polymer samples. Polymer samples were prepared in Caspian seawater (CSW) and assessed based on rheology, thermal stability, sensitivity to non-ionic materials and oxygen, and static adsorption. All the tests were performed at a reservoir temperature of 63 °C. Based on the results of the screening study, tolerance of a polymer towards high-temperature reservoir conditions, resistance to bacterial activity and dissolved oxygen present in make-up brine, chemical degradation, and reduced adsorption on rock surface were considered the most important screening parameters. As a result of this screening study, one out of four polymers was selected for the target field as it showed a negligible effect of bacterial activity on thermal stability. The results of static adsorption also showed 13-14% lower adsorption of the selected polymer compared to other polymers tested in the study. The results of this study demonstrate important screening criteria to be followed during polymer selection for an oilfield as the polymer should be selected based on not only polymer characteristics but also the polymer interactions with the ionic and non-ionic components of the make-up brine.

Laboratory Investigation of Nanofluid-Assisted Polymer Flooding in Carbonate Reservoirs.

In the petroleum industry, the remaining oil is often extracted using conventional chemical enhanced oil recovery (EOR) techniques, such as polymer flooding. Nanoparticles have also greatly aided EOR, with benefits like wettability alteration and improvements in fluid properties that lead to better oil mobility. However, silica nanoparticles combined with polymers like hydrolyzed polyacrylamide (HPAM) improve polymer flooding performance with better mobility control. The oil displacement and the interaction between the rock and polymer solution are both influenced by this hybrid approach. In this study, we investigated the effectiveness of the injection of nanofluid-polymer as an EOR approach. It has been observed that nanoparticles can change rock wettability, increase polymer viscosity, and decrease polymer retention in carbonate rock. The optimum concentrations for hydrolyzed polyacrylamide (2000 ppm) and 0.1 wt% (1000 ppm) silica nanoparticles were determined through rheology experiments and contact angle measurements. The results of the contact angle measurements revealed that 0.1 wt% silica nanofluid alters the contact angle by 45.6°. The nano-silica/polymer solution resulted in a higher viscosity than the pure polymer solution as measured by rheology experiments. A series of flooding experiments were conducted on oil-wet carbonate core samples in tertiary recovery mode. The maximum incremental oil recovery of 26.88% was obtained by injecting silica nanofluid followed by a nanofluid-assisted polymer solution as an EOR technique. The application of this research will provide new opportunities for hybrid EOR techniques in maximizing oil production from depleted high-temperature and high-salinity carbonate reservoirs.

Spontaneous Imbibition Oil Recovery by Natural Surfactant/Nanofluid: An Experimental and Theoretical Study.

Organic surfactants have been utilized with different nanoparticles in enhanced oil recovery (EOR) operations due to the synergic mechanisms of nanofluid stabilization, wettability alteration, and oil-water interfacial tension reduction. However, investment and environmental issues are the main concerns to make the operation more practical. The present study introduces a natural and cost-effective surfactant named Azarboo for modifying the surface traits of silica nanoparticles for more efficient EOR. Surface-modified nanoparticles were synthesized by conjugating negatively charged Azarboo surfactant on positively charged amino-treated silica nanoparticles. The effect of the hybrid application of the natural surfactant and amine-modified silica nanoparticles was investigated by analysis of wettability alteration. Amine-surfactant-functionalized silica nanoparticles were found to be more effective than typical nanoparticles. Amott cell experiments showed maximum imbibition oil recovery after nine days of treatment with amine-surfactant-modified nanoparticles and fifteen days of treatment with amine-modified nanoparticles. This finding confirmed the superior potential of amine-surfactant-modified silica nanoparticles compared to amine-modified silica nanoparticles. Modeling showed that amine surfactant-treated SiO2 could change wettability from strongly oil-wet to almost strongly water-wet. In the case of amine-treated silica nanoparticles, a strongly water-wet condition was not achieved. Oil displacement experiments confirmed the better performance of amine-surfactant-treated SiO2 nanoparticles compared to amine-treated SiO2 by improving oil recovery by 15%. Overall, a synergistic effect between Azarboo surfactant and amine-modified silica nanoparticles led to wettability alteration and higher oil recovery.

Investigation of Brine pH Effect on the Rheological and Viscoelastic Properties of HPAM Polymer for an Optimized Enhanced Oil Recovery Design.

A novel approach to improve viscous and viscoelastic properties by exploiting the pH and salinity sensitivity of HPAM polymer is proposed in this paper. Polymer flooding is a well-developed and effective enhanced oil recovery technique. The design of the makeup brine is one of the most critical phases of a polymer flood project, since the brine composition, salinity, and pH directly influence the polymer viscosity and viscoelasticity. However, the viscoelastic properties of hydrolyzed polyacrylamide polymers have not been given much consideration during the design phase of polymer flood projects. Our experimental study focuses on the optimization of the makeup water design for polymer flooding by evaluating the optimum solution salinity and pH for better stability and improved viscoelastic behavior of the polymer. Initially, the brine salinity and ionic composition is adjusted and then hydrolyzed polyacrylamide (HPAM) polymer solutions of varying pH are prepared using the adjusted brine. Rheological experiments are conducted over a temperature range of 25-80 °C and at different aging times. Polymer thermal degradation as a function of pH is assessed by examining the solutions at 80 °C for 1 week. Amplitude sweep and frequency sweep tests are performed to determine the viscoelastic properties such as storage modulus, loss modulus, and relaxation time. A 15-40% increase in the polymer solution viscosity and a 20 times increase in relaxation time is observed in the pH range of 8-10 in comparison to the neutral solution. This can be attributed to the low-salinity ion-adjusted environment of the makeup brine and further hydrolysis and increased repulsion of polymer chains in an alkaline environment. These results indicate that the viscoelastic properties of a polymer are tunable and a basic pH is favorable for better synergy between the brine and the polymer. Alkaline low-salinity polymer solutions have exhibited 60% higher thermal stability in comparison to acidic solutions and thus can be successfully applied in high-temperature reservoirs. The results of this study show that polymer solutions with an optimum pH in the basic range exhibit a higher viscoelastic character and an increased resistance toward thermal degradation. Hence, the polymer solution salinity, ionic composition, and pH should be adjusted to obtain maximum oil recovery by the polymer flooding method. Finally, this study shows that more effective polymer solutions can be prepared by adjusting the pH and designing a low-salinity water/polymer recipe to get the additional benefit of polymer viscoelasticity. The optimized low-salinity alkaline conditions can reduce the residual oil saturation by stronger viscous and viscoelastic forces developed by more viscous polymers. The findings of this study can be employed to design an optimum polymer recipe by tuning the brine pH and salinity for maximum incremental oil recovery, particularly in high-temperature and high-salinity formations.

Toward Reducing Surfactant Adsorption on Clay Minerals by Lignin for Enhanced Oil Recovery Application.

The significant loss of surfactants during reservoir flooding is a challenge in oil field operations. The presence of clay minerals affects the surfactant performance, resulting in surfactant losses. This is because the mineralogical composition of the reservoir results in unpredicted adsorption quantity. Therefore, this paper seeks to investigate Aerosol-OT's adsorption on different quartz/clay mineral compositions during the flow. Also, it investigates adsorption mitigation by preflushing with lignin. The dynamic experiments were conducted on sand packs composed of quartz-sand and up to a 7% clay mineral content. The results obtained from the surfactant losses were compared with/without lignin preflush at different pH values. The main observation was the direct relationship between increasing the composition of clay minerals and the surfactant pore volume required to overcome the adsorption. The highest adsorption calculated was 46 g/kg for 7% kaolinite. Moreover, lignin successfully reduced the adsorption of Aerosol-OT by 60%. Therefore, the results demonstrate that the effects of the clay mineral content on adsorption could be efficiently minimized using lignin at a high pH.

Catalytic Effects of Temperature and Silicon Dioxide Nanoparticles on the Acceleration of Production from Carbonate Rocks.

The use of engineered water (EW) nanofluid flooding in carbonates is a new enhanced oil recovery (EOR) hybrid technique that has yet to be extensively investigated. In this research, we investigated the combined effects of EW and nanofluid flooding on oil-brine-rock interactions and recovery from carbonate reservoirs at different temperatures. EW was used as dispersant for SiO2 nanoparticles (NPs), and a series of characterisation experiments were performed to determine the optimum formulations of EW and NP for injection into the porous media. The EW reduced the contact angle and changed the rock wettability from the oil-wet condition to an intermediate state at ambient temperature. However, in the presence of NPs, the contact angle was reduced further, to very low values. When the effects of temperature were considered, the wettability changed more rapidly from a hydrophobic state to a hydrophilic one. Oil displacement was studied by injection of the optimised EW, followed by an EW-nanofluid mixture. An additional recovery of 20% of the original oil in place was achieved. The temperature effects mean that these mechanisms are catalytic, and the process involves the initiation and activation of multiple mechanisms that are not activated at lower temperatures and in each standalone technique.

Fine Migration Control in Sandstones: Surface Force Analysis and Application of DLVO Theory.

Formation damage caused by fine migration and straining is a well-documented phenomenon in sandstone reservoirs. Fine migration and the associated permeability decline have been observed in various experimental studies, and this phenomenon has been broadly explained by the analysis of surface forces between fines and sand grains. The Derjaguin-Landau-Verwey-Overbeek (DLVO) theory is a useful tool to help understand and model the fine release, migration, and control phenomena within porous media by quantifying the total interaction energy of the fine-brine-rock (FBR) system. Fine migration is mainly caused by changes in the attractive and repulsive surface forces, which are triggered by mud invasion during drilling activity, the utilization of completion fluid, acidizing treatment, and water injection into the reservoir during secondary and tertiary recovery operations. Increasing pH and decreasing water salinity collectively affect the attractive and repulsive forces and, at a specific value of pH, and critical salt concentration (CSC), the total interaction energy of the FBR system (V T) shifts from negative to positive, indicating the initiation of fine release. Maintaining the system pH, setting the salinity above the CSC, tuning the ionic composition of injected water, and using nanoparticles (NPs) are practical options to control fine migration. DLVO modeling elucidates the total interaction energy between fines and sand grains based on the calculation of surface forces of the system. In this context, zeta potential is an important indicator of an increase or decrease in repulsive forces. Using available data, two correlations have been developed to calculate the zeta potential for sandstone reservoirs in high- and low-salinity environments and validated with experimental values. Based on surface force analysis, the CSC is predicted by the DLVO model; it is in close agreement with the experimental value from the literature. The critical pH value is also estimated for alkaline flooding. Model results confirm that the application of NPs and the presence of divalent ions increase the attractive force and help to mitigate the fine migration problem. Hence, a new insight into the analysis of quantified surface forces is presented in current research work by the practical application of the DLVO theory to model fine migration initiation under the influence of injection water chemistry.

Effects of Slug Size, Soaking, and Injection Schemes on the Performance of Controlled Ions Water Flooding in Carbonates.

The results of many previous studies on low salinity/controlled ions water (CIW) flooding suggest that future laboratory and modeling investigations are required to comprehensively understand and interpret the achieved observations. In this work, the aim is co-optimization of the length of the injected slug and soaking time in the CIW flooding process. Furthermore, the possibility of the occurrence of several governing mechanisms is studied. Therefore, the experimental results were utilized to develop a compositional model, using CMG GEM software, in order to obtain the relative permeability curves by history matching. It was concluded that CIW slug injection, concentrated in the potential-determining ion, can increase oil recovery under a multi ion exchange (MIE) mechanism. The wettability of the carbonate rocks was changed from a mixed or oil wet state toward more water wetness. However, there is a CIW slug length, beyond which extending the length does not significantly improve the rock wettability, and consequently, the oil production, which is known as the optimum slug size. This implies that the optimization of the injection process, by minimizing the slug size, can decrease the need for the CIW supply, therefore lowering the process expenditure. Moreover, if the exposure time of the rock and CIW is increased (soaking), a higher level of ion substitution is probable, leading to more oil detachment and production. Rock dissolution/precipitation (leading to a pH change) was found to have a negligible contribution.