Minimum Miscibility Pressure Research Articles

Novel strategy for reducing the minimum miscible pressure in a CO2–oil system using nonionic surfactant: Insights from molecular dynamics simulations

Effective CO2-oil miscibility is a vital factor in optimizing oil production during CO2 flooding and enhancing CO2 storage capacity. This research investigates the impact of various surfactants, temperatures, and pressures on CO2-oil interfacial tension (IFT) through experimental measurements. It also evaluates the reduction in minimum miscible pressure (MMP). Subsequently, molecular dynamics (MD) simulations analyze gas-liquid miscibility, focusing on relative concentration, interaction energy, radial distribution function (RDF), and miscibility degree (Dmix). Results indicate that introducing a compound nonionic surfactant SF significantly reduces IFT and MMP, achieving an impressive 19.59% MMP reduction. Moreover, SF inclusion boosts Dmix by 8.57%, reflecting enhanced miscibility. The highest absolute value of average interaction energy (EInter) is observed, primarily driven by van der Waals interactions. SF's augmented CO2 coordination number contributes to improved Dmix and reduced MMP. SF's nonpolar groups react with CO2, reducing asymmetric forces between phases and lowering IFT. Electronegative fluorine atoms in SF interact with electron-deficient carbon atoms in CO2, heightening CO2 solubility. Elevated system pressure or reduced temperature amplifies EInter, the coordination number, and subsequently enhances Dmix. Experimentally measured MMP results closely align with MD simulations, with an average relative error of 4.63%. This study elucidates CO2-oil miscibility mechanisms on experimental and molecular scales, offering a promising avenue for future CO2 flooding research.

The impacts of CO2 flooding on crude oil stability and recovery performance

Numerous studies have investigated the fundamental mechanisms by which CO2 flooding can increase oil production by altering the properties of the hydrocarbon fluid, including oil swelling, viscosity and interfacial tension reductions, and the extraction of light-to-intermediate components. However, the interactions between CO2 and hydrocarbon fluid may also cause several problems, such as asphaltene precipitation due to crude oil's instability during the CO2 flooding process. This study investigates the complex factors that affect the instability of crude oil, including CO2 injection pressures, temperatures, and crude oil compositions. The light-dead oil samples taken from two Indonesian oil fields were used. The impacts of the instability of crude oil on CO2 displacement performance were also observed to evaluate oil recovery and minimum miscibility pressure (MMP). The observation was performed using a slim tube under varying CO2 high-pressure injections at 90 °C and 70 °C. The produced oils were analyzed based on their polarity component, saturates, aromatics, resins, and asphaltenes fractions, to observe the changes in oil composition and colloidal index instability. The results showed that increasing temperatures at given pressures resulted in higher oil recovery. Moreover, the asphaltene and resin fractions in the oil produced at a lower temperature significantly decrease compared to those at a higher temperature. It was also shown that asphaltene tends to precipitate more easily at a lower temperature. The other phenomenon revealed that the lighter oil resulted in a lower recovery than the heavier oil at a given pressure and temperature and correspondingly higher MMP. It was also suggested that CO2 flooding is more likely to cause asphaltene precipitation in light oils.

The influence and mechanism of alkyl block polyethers on the interfacial tension and minimum miscibility pressure of CO2 and shale oil

The successful application of CO2 in developing shale oil can increase oil production and reduce CO2 emission. Reducing IFT and facilitating miscibility between CO2 and oil is the critical mechanism for enhancing shale oil recovery by CO2 flooding. Here, the effects of alkyl block polyethers on the interfacial tension and minimum miscibility pressure of CO2 and shale oil has been investigated by experiments and the influence mechanism of polyether on IFT and MMP has been explored by molecular dynamic simulations. The experimental results show that among the three polyethers, C4(PO)6 has the best effect to decrease the IFT and MMP of CO2 and shale oil. The IFT and MMP decrease with the increasing concentration of C4(PO)6 in CO2. The IFT and MMP can be decreased to a lower value when the polyether is dissolved in CO2 than in oil phase. The molecular dynamic simulations show that polyether molecules can diffuse from CO2 phase to the interface of CO2 and oil to decrease the IFT and further diffuse to oil phase to accelerate the miscibility process of CO2 and oil. The presence of polyether molecules can decrease the interaction energy, especially the vdW interactions between CO2 and oil molecules to decrease the IFT and MMP. The reduction of interaction energy is due to the dispersion force and LA-LB interactions between polyether and CO2, as well as the dispersion force interactions between polyether and oil molecules. The finding is significant to the chemical design for decreasing the IFT and MMP of CO2 and oil and further to successfully and efficiently develop shale oil by the CO2-surfactant mixed fluid.

Predicting minimum miscible pressure in pure CO2 flooding using machine learning: Method comparison and sensitivity analysis

CO2 injection for enhanced oil recovery (EOR) is widely recognized as an efficient technique for carbon capture, utilization, and storage (CCUS). This operation has a significant impact on various technical parameters, emphasizing the need to carefully consider and select the optimum approach. Among these factors, the minimum miscible pressure (MMP) plays a crucial role in determining the effectiveness and performance of CO2 injection. Therefore, this study aims to assess the reliability of machine learning (ML) in predicting the MMP of pure CO2 and examine the influence of different independent parameters. To achieve this, five ML methods were employed to predict the pure CO2 MMP, and the results were compared to statistical evaluations based on empirical correlations. In addition, three types of data with different functional input parameters were used in this research. Two types of data were obtained from existing literature, while the third category was collected from the thesis and PVT reports for specific Iraqi oil fields. The ML models were constructed by splitting the dataset into 20% for testing and 80% for training using Python programming. The significance of this study lies in its ability to identify the most efficient approach for forecasting MMP. The results of this work revealed that the K-nearest neighbors (KNN) model indicated the best statistical evaluation among the ML learning algorithms for two types of data (2) and (3) in predicting the MMP for pure CO2 flooding. This was evidenced by the lowest mean square error and the highest coefficient of determination. Additionally, the findings indicated that the support vector regression (SVR) method is an effective technique for smaller datasets. Moreover, the sensitivity analysis and assessment of the relative impacts of various input parameters revealed that the prediction of MMP is most sensitive to the composition of the injected gas and temperature, accounting for 46% and 28.5% of the variation, respectively. Finally, the presented ML models indicate exceptional accuracy, speed, adaptability in handling diverse conditions, and cost-effectiveness when compared to conventional approaches. These results verify the ability of ML models to provide high-quality predictions.

Techno-economical optimization of water-alternating-CO2/dimethyl ether process for enhanced oil recovery

The use of CO2 to improve oil recovery has the disadvantage of reduced sweep efficiency due to the large difference in density and viscosity between oil and CO2. Overcoming these drawbacks, the use of dimethyl ether (DME) is known to be more effective than CO2 in improving oil recovery. In this study, a CO2-DME mixed solvent, is thoroughly investigated by developing a compositional model. The oil recovery of a CO2-DME mixed solvent has been examined in terms of sweep efficiency and displacement efficiency by comparing CO2-water-alternating-gas (WAG) and CO2-DME WAG. According to the results from compositional simulation, the highest DME content investigated resulted in a 66.4% lower viscous gravity number and a 26.6% increase in sweep efficiency compared to CO2 WAG. Minimum miscible pressure (MMP) and interfacial tension (IFT) were reduced by 30.1 and 97.5%, respectively, significantly improving the mobility of the oil. As a result, the amount of oil remaining in the reservoir decreased by 40.7%, and oil recovery increased by 31%. An economic evaluation considering optimized injection design and reuse of recovered DME showed a 13% improvement in net present value (NPV) of CO2-DME WAG over CO2 WAG.

Study on Interaction Characteristics of Injected Natural Gas and Crude Oil in a High Saturation Pressure and Low-Permeability Reservoir

Natural gas injection is considered for enhanced oil recovery (EOR) in a high saturation pressure reservoir in block B111 of the Dagang oilfield, China. To investigate the interaction characteristics of injected natural gas and crude oil, the ability for dissolution–diffusion and miscibility–extraction of natural gas in crude oil was tested using a piece of high-temperature and high-pressure PVT equipment. The physical properties and minimum miscible pressure (MMP) of the natural gas–crude oil system and their interaction during dynamic displacement were analyzed using the reservoir numerical simulation method. The results show the following: (1) Under static gas–oil contact conditions, natural gas has a significant dissolution–diffusion and miscibility–extraction effect on the crude oil in block B111, especially near the gas–oil interface. The content of condensate oil in gas phase is 10.14–18.53 wt%, while the content of dissolved gas in oil phase reaches 26.17–57.73 wt%; (2) Under the reservoir’s conditions, the saturated solubility of natural gas injected in crude oil is relatively small. The effect of swelling and viscosity reduction on crude oil is limited. As the pressure increases with more natural gas dissolved in crude oil, the phase state of crude oil can change from liquid to gas; accordingly, the density and viscosity of crude oil will be greatly reduced, presenting the characteristics of condensate gas; (3) The MMP of natural gas and crude oil is estimated to be larger than 40 MPa. It mainly forms a forward-contact evaporative gas drive in block B111. The miscible state depends on the maintenance level of formation pressure. The injected natural gas has a significant extraction effect on the medium and light components of crude oil. The content of C2–C15 in the gas phase at the gas drive front, as well as the content of CH4 and C16+ in the residual oil at the gas drive trailing edge, will increase markedly. Accordingly, the residual oil density and viscosity will also increase. These results have certain guiding significance for understanding gas flooding mechanisms and designing gas injection in block B111.

Prediction of Key Parameters in the Design of CO2 Miscible Injection via the Application of Machine Learning Algorithms

The accurate determination of key parameters, including the CO2-hydrocarbon solubility ratio (Rs), interfacial tension (IFT), and minimum miscibility pressure (MMP), is vital for the success of CO2-enhanced oil recovery (CO2-EOR) projects. This study presents a robust machine learning framework that leverages deep neural networks (MLP-Adam), support vector regression (SVR-RBF) and extreme gradient boosting (XGBoost) algorithms to obtained accurate predictions of these critical parameters. The models are developed and validated using a comprehensive database compiled from previously published studies. Additionally, an in-depth analysis of various factors influencing the Rs, IFT, and MMP is conducted to enhance our understanding of their impacts. Compared to existing correlations and alternative machine learning models, our proposed framework not only exhibits lower calculation errors but also provides enhanced insights into the relationships among the influencing factors. The performance evaluation of the models using statistical indicators revealed impressive coefficients of determination of unseen data (0.9807 for dead oil solubility, 0.9835 for live oil solubility, 0.9931 for CO2-n-Alkane interfacial tension, and 0.9648 for minimum miscibility pressure). One notable advantage of our models is their ability to predict values while accommodating a wide range of inputs swiftly and accurately beyond the limitations of common correlations. The dataset employed in our study encompasses diverse data, spanning from heptane (C7) to eicosane (C20) in the IFT dataset, and MMP values ranging from 870 psi to 5500 psi, covering the entire application range of CO2-EOR. This innovative and robust approach presents a powerful tool for predicting crucial parameters in CO2-EOR projects, delivering superior accuracy, speed, and data diversity compared to those of the existing methods.

Effect of water saturation on CO2 minimum miscibility pressure and oil displacement performance

The CO2 miscible flooding is an effective technology for development of low permeability reservoirs due to high oil displacement efficiency. However, CO2 miscible flooding for tertiary recovery technology typically occur after water flooding. Water hindered the contact and mass transfer of CO2 and oil, produce water resistance effect. Water can block CO2 and contact and mass transfer of crude oil (ie water blocking effect). The impact of this effect on the miscibility pressure and oil displacement effect is still unclear. In this study, homogeneous artificial cores with the same permeability as the reservoir were designed according to the miscible mechanism. Subsequently, the minimum miscibility pressure(MMP) between CO2 and crude oil at different water saturation was measured by the coreflood test. Based on the MMP, CO2 miscible flooding experiments were conducted by natural cores at different water saturation. The results showed that when the water saturation was 30%, 45%, and 60%, respectively, the corresponding MMP between CO2 and crude oil was 18.56, 19.48, and 21.76 MPa. The higher the water saturation, the longer the gas breakthrough time. But the oil recovery factor did not rise with the increase of water saturation. When the water saturation was 45%, the oil recovery factor in the miscible flooding experiment was the highest. In addition, the higher the water saturation, the weaker the CO2 extraction of various components in the crude oil. And the light components below C5 were most affected by water saturation. The mechanisms underlying these results are discussed. This study contributes to the development of CO2 miscible flooding reservoir plan.

Microfluidic Studies on Minimum Miscibility Pressure for n-Decane and CO2

Oil production is a complex process that can be made more efficient by applying gas enhanced oil recovery (EOR) methods. Thus, it is essential to know the minimum miscibility pressure (MMP) and minimum miscibility enrichment (MME) of gas in oil. Conventional slim-tube experiments for the measurement of MMP require hundreds of millilitres of real or recombined oil and last over 30 days. Advances in microfluidic technology allow the reduction of the amount of fluid and the time required in determining MMP (or MME), hence making the process rapid. In this study, we developed a microfluidic model with a stochastically distributed pore network, porosity of 74.6% and volume of 83.26 nanolitres. Although the volume was six orders of magnitude smaller than the slim tube, it retained the same proportions, guaranteeing a proper comparison between the tests. This microfluidic chip allowed the study of the MMP of n-decane with carbon dioxide at two different temperature conditions. The experimental results coincided with the results received both from conventional and microfluidic experiments. Furthermore, a numerical simulation of a section of the microfluidic model under the experimental conditions presented results within acceptable margins of the experimental ones. The results of the presented methodology indicate the potential to replace conventional technology for the measurement of MMP with microfluidic technology. Its promise lies in accelerating laboratory tests and increasing the reliability of experimental results and, subsequently, the quality of field gas EOR operations.

Molecular insight into minimum miscibility pressure estimation of shale oil/CO2 in organic nanopores using CO2 huff-n-puff

CO2-enhanced oil recovery (EOR) has been regarded as an essential means of tertiary oil recovery worldwide, which has been gradually applied in exploiting shale oil and gas resources. In this study, we proposed a new method to estimate the MMP (minimum miscibility pressure) of shale oil/CO2 systems using huff-n-puff molecular dynamics (MD) simulations. The bulk MMP of the shale oil/CO2 system obtained agrees reasonably well with the vanishing interfacial tension (VIT) and the available experimental results. The organic nanopore oil reservoir is modeled with graphene as a substrate and octane molecules as shale oil. We found that oil recovery increases up to near miscible pressure and plateaus after that. The oil recovery increases with the rise of the reservoir temperature and slit height. Due to the nanopore’s confinement effect, the predicted MMP is lower inside the nanopore than the bulk counterpart. The MMP inside the nanopore decreases with a slit height up to a specific size and then starts to climb up due to the increased adsorption effect of nanopore walls. It means that CO2 flooding will be more efficient in shale oil reservoirs with more prominent pores and throats. Some CO2 molecules remain inside the nanopore after the completion of the huff-n-puff process. Like the oil recovery, the amount of CO2 trapped inside the pore after the huff-n-puff procedure plateaus after some critical pressure. So, CO2 huff-n-puff has two benefits — oil recovery and carbon sequestration. Our method of simulating huff-n-puff using MD can be a quick and economic supplement to the CO2-EOR experiments, which might benefit the development of shale oil reservoirs.

Comparative numerical study on the co-optimization of CO2 storage and utilization in EOR, EGR, and EWR: Implications for CCUS project development

Carbon capture, utilization, and storage (CCUS) and the geological sequestration of carbon dioxide (CO2) have become effective means of mitigating CO2 emissions and combating global warming. Currently, two main issues influence the implementation and progress of major CCUS technologies (e.g., CO2 geo-storage combined with CO2-enhanced oil recovery (CO2-EOR), CO2-enhanced gas recovery (CO2-EGR), and CO2-enhanced deep saline water/brine recovery (CO2-EWR)): high development costs and negative environmental impacts. Additionally, certain operating and reservoir critical parameters could influence the performance of CCUS technologies, making it difficult to design an optimal development scheme. In this study, a comparative numerical simulation analysis on the co-optimization of CO2 storage and utilization in EOR, EGR, and EWR was performed. A geological model based on the Bakken formation was built, and the influence of critical reservoir parameters (reservoir permeability, porosity, initial reservoir pressure, injection pressure, and production pressure) was observed through sensitivity analysis. The following results were obtained: (1) For CO2-EOR, the CO2 storage capacity increases with operating pressure above the minimum miscibility pressure. (2) Based on the best-case scenario, the CO2 storage capacities of EWR, EOR, and EGR were 189.4 × 106 scf, 252 × 106 scf, and 97 × 106 scf, respectively. (3) According to the best-case analysis, the recovery factor of EWR, EOR, and EGR were 5.2%, 91%, and 12%, respectively. (4) By comparing the best-case storage capacity and recovery factor, the optimal CCUS process was the CO2-EOR technology. The research results will guide future decisions on the development of CCUS projects.

Feasibility of CO2 Injection for Enhance Oil Recovery: A Case Study in the KMJ Layer of HKY Field

Carbondioxide (CO2) injection is a very effective and proven technology for enhanced oil recovery (EOR). Minimum miscibility pressure (MMP) and oil swelling are two important factors of the CO2 gas displacement mechanism that occurs in the reservoir when CO2 injection is applied to enhance oil recovery. In this study, MMP determination between crude oil samples and CO2 gas has been conducted using three methods, i.e., empirical equation, correlations method, and laboratory experiment using slimtube. The determination of the swelling factor was conducted using a PVT cell, where recombined fluid is injected at the reservoir temperature. The MMP value from the empirical equation (2810 psig) is relatively close to the MMP value from the laboratory experiment (2807 psig), with a difference of 3 psig. The swelling test results show that the bubble point pressure and the swelling factor increase from 410 psig to 2200 psig and from 1.0 to 1.442, respectively, as the CO2 gas injection reaches 46.82% mole. Since the fracture pressure of the KMJ Layer in the HKY Field is 2200 psig and the MMP is 2807 psig, only immiscible CO2 flooding can be applied in the field because the CO2 MMP is higher than the fracture pressure.

Impact of water on miscibility characteristics of the CO2/n-hexadecane system using the pendant drop shape analysis method

Miscible CO2 flooding has shown bright prospects for improving oil recovery from unconventional reservoirs as well as for storing greenhouse gas in underground formations. Although the favorable water presence effect has been reported in the near miscible CO2 flooding practices, there is still a lack of target research works on the impact of water on the miscibility characteristics of the oil/gas systems. Therefore in this paper, the effect of water presence on the Minimum Miscibility Pressure (MMP) of the CO2/n-Hexadecane (n-C16H34) system is experimentally investigated based on the Oil Droplet Volume Measurement (ODVM) method. By pre-saturating CO2 with water in the high-pressure high-temperature cell, the water component is introduced at the CO2/oil interface. Measurement results show the water presence could result in lower MMPs of the CO2/oil system. Under five temperature levels of 40 °C, 51 °C, 61 °C, 72 °C, and 82 °C, the water presence decreases the MMPs of the CO2/n-C16H34 system from 8.2 to 7.8 MPa, from 9.6 to 8.8 MPa, from 11.6 to 10.2 MPa, from 13.0 MPa to 12.2 MPa and from 14.6 MPa to 13.2 MPa respectively. Thermodynamic calculations provide consistent results as the experimental observations, indicating the main mechanism behind the lower MMPs of the water presence CO2/oil system could be the decreased CO2 molar fraction in the water presence system. This research is expected to provide an innovative viewpoint to understand the water presence effect in the CO2 flooding processes.

Nanometer-Scale CO2-Shale Oil Minimum Miscibility Pressure Calculations Based on Modified PR-EOS

CO2 flooding is recognized as an efficient method for enhancing shale oil recovery, while CO2-oil MMP (minimum miscibility pressure) in the micro-nanoscale is a crucial parameter. This paper presents a method for calculating the MMPs of pure hydrocarbons (C4H10, C6H14, C8H18, and C10H22) and CO2 systems in nanopores (3 nm to 10 nm) with temperature ranging from 290.15 K to 373.15 K. Firstly, we modify the Peng-Robinson equation of state (PR-EOS) by considering the influence of confinement effect and capillary pressure in nanopores. Secondly, the flash calculation algorithm is employed to determine whether the oil and gas phases in nanopores have reached an equilibrium state according to the equality of the fugacity of the two phases. Thirdly, we calculate the interfacial tension (IFT) between the two phases using the Macleod-Sugden equation. When the extrapolated IFT is zero, we treat the corresponding pressure as the MMP of the CO2-oil system in nanopores. Simulation results indicate that the calculated MMP using this method has a relative error of about 0.62% compared to the MMP calculated using the multiple mixing cell (MMC) method, indicating high reliability for MMP prediction. Moreover, the measured MMP at the nanoscale is generally smaller than that in the bulk phase due to the influence of the confinement effect. The MMP is positively correlated with the reservoir temperature, the carbon atom number in alkanes, and the nanopore radius.

Calculation of IFT in porous media in the presence of different gas and normal alkanes using the modified EoS

Gas injection can increase oil recovery because the gas–oil interfacial tension is less than the water–oil interfacial tension (IFT) and tends to zero in the miscibility state. However, little information has been provided on the gas–oil movement and penetration mechanisms in the fracture system at the porosity scale. The IFT of oil and gas in the porous medium changes and can control oil recovery. In this study, the IFT and the minimum miscibility pressure (MMP) are calculated using the cubic Peng-Robinson equation of state that has been modified using the mean pore radius and capillary pressure. The calculated IFT and MMP change with the pore radius and capillary pressure. To investigate the effect of a porous medium on the IFT during the injection of CH4, CO2, and N2 in the presence of n-alkanes and for validation, measured experimental values in references have been used. According to the results of this paper, changes in IFT vary in terms of pressure in the presence of different gases and, the proposed model has good accuracy for measuring the IFT and the MMP during the injection of hydrocarbon gases and CO2. In addition, as the average radius of the pores gets smaller, the interfacial tension tends to lower values. This effect is different with increasing the mean size of interstice in two different intervals. In the first interval, i.e. the Rp from 10 to 5000 nm, the IFT changes from 3 to 10.78 mN/m and in the second interval, i.e. the Rp from 5000 nm to infinity, the IFT changes from 10.78 to 10.85 mN/m. In other words, increasing the diameter of the porous medium to a certain threshold (i.e. 5000 nm) increases the IFT. As a rule, changes in IFT affected by exposure to a porous medium affect the values of the MMP. In general, IFT decreases in very fine porous media, causing miscibility at lower pressures.

Decreasing Asphaltene Precipitation and Deposition during Immiscible Gas Injection Via the Introduction of a CO2-Soluble Asphaltene Inhibitor

Summary In this study, the ability of dilute concentrations of toluene to act as a CO2-soluble asphaltene stabilization agent capable of inhibiting asphaltene precipitation during immiscible CO2 injection was assessed. Phase behavior results indicated that 1,000 to 20,000 ppm toluene could readily dissolve in CO2 at cloudpoint pressures that are well below the formation pressure and typical CO2 minimum miscibility pressure (MMP) values during gas-based enhanced oil recovery (EOR). Single-phase solutions of the modified gas (CO2/toluene) were then combined with asphaltenic oils in oil swelling phase behavior tests to demonstrate that the presence of toluene increased the amount of CO2 that dissolved into reservoir crude oil at a specified temperature and pressure. However, asphaltene precipitation diminished, apparently because the effect of the increased asphaltene solvent strength of toluene was more significant than the increased amount of CO2 (an asphaltene antisolvent) that entered the oil-rich phase. During the injection of CO2/toluene solution into cores initially saturated with crude oil and brine, compared to the injection of pure CO2, asphaltene deposition declined during the injection of CO2/toluene mixtures for asphaltenic volatile and intermediate oils from 3.7 wt% to 0.7 wt% and 5.9 wt% to 1.7 wt%, respectively. Based on the asphaltene particle-size analysis, the CO2/toluene mixtures can stabilize oil particles and simultaneously reduce asphaltene aggregation more effectively than pure CO2.

A Systematic Experimental Study to Understand the Performance and Efficiency of Gas Injection in Carbonate Reservoirs

Summary Gas injection is the most widely applied recovery method in light, condensate, and volatile oil carbonate reservoirs. Gas has high displacement efficiency and usually results in a low residual oil saturation in the part of the reservoir that is contacted with gas. The displacement efficiency increases when the injected gas is near-miscible or miscible with the oil. In addition to nitrogen and hydrocarbon gas projects, carbon dioxide (CO2) enhanced oil recovery (EOR) has been the dominant gas EOR process. Gas-based EOR has been implemented in both mature and waterflooded carbonate reservoirs. In this paper, we present the results of a detailed experimental study aimed at understanding the performance and efficiency of gas injection in carbonate reservoirs. A series of immiscible and miscible gas injection coreflood experiments were performed using limestone reservoir cores under different injection strategies. To minimize laboratory artifacts, long cores were used in the experiments, and to observe the effect of gravity, both 2 in. diameter and 4 in. diameter (whole core) were used. The experiments were performed under reservoir conditions using live crude oil. The core wettability was restored by aging the core in crude oil for several weeks under reservoir temperature. Hydrocarbon gas (methane) was used as the immiscible injectant, and both CO2 and a mixture of 50% C1 and 50% CO2 were used as miscible injectant. All gas injection experiments were performed using vertically oriented cores, and the gas was injected from the top unless it is stated otherwise. The main parameters investigated in this study are as follows: The effect of miscibility on oil recovery for both continuous gas injection and water alternating gas (WAG). The effect of gravity on gas sweep efficiency compared to waterflooding. The effect of gas-oil interfacial tension (IFT) on oil recovery when using the same oil. The effect of oil type on oil recovery using the same injected gas at miscible and immiscible conditions. The effect of immiscible gas injection on subsequent miscible gas injection performance. Impact of CO2 cycle length on ultimate oil recovery. The impact of the order of fluid injection where multiple WAG injection cycles were performed in separate experiments after water or gas injection. The main conclusions of this study are as follows: As expected, miscibility has a significant impact on displacement efficiency and oil recovery where miscible gas recovered more than 20% extra oil compared to immiscible gas. A significant variation in oil recovery is observed for miscible gas injection (i.e., more than 10 saturation units difference) depending on the minimum miscibility pressure (MMP) between the injected gas and crude oil, even when both experiments are performed at miscible conditions using the same injected gas. The performance of tertiary CO2 flood was adversely affected by the slug of immiscible gas injected. Therefore, it is not recommended to have immiscible gas injection before miscible gas injection. Regardless of injected gas type, gas injection with similar IFTs achieved similar oil recovery. During WAG experiments, starting the injection cycles with water or gas did not have any impact on the ultimate oil recovery for both miscible and immiscible cases for one of the reservoirs, while WAG_G (WAG starting with gas injection) recovered more oil for another reservoir. Gravity has a significant impact on oil recovery for both miscible and immiscible gas injections. A significant difference is observed in oil recovery when comparing CO2 injection on 2-in.- and 4-in.-diameter core samples or when comparing horizontal vs. vertical immiscible gas injection and WAG experiment. The longer the CO2 slug size, the higher the oil recovery observed in gas injection experiments. The results of this study provide a rich and rarely available set of experimental data that can help improve and optimize gas and WAG injection in oil-wet carbonates.

Impact of gas composition and reservoir heterogeneity on miscible sour gas flooding — A simulation study

Proper handling of the produced sour gas is a big challenge for operating companies due to the serious environmental and technical problems caused by H2S and CO2. The reinjection of the produced sour gas into oil reservoirs is an environmentally friendly as well as an economically attractive method due to the low investment cost and incremental oil recovery. However, the sour gas injection for enhanced oil recovery (EOR) is a relatively new approach with numerous uncovered perspectives, especially in a heterogeneous reservoir. The objective of this study is to investigate the effect of gas composition and reservoir heterogeneity on the miscible displacement of reservoir oil using sour gas.The reservoir oil consisting of 15 mol% H2S and 4 mol% CO2 from an oilfield in the North Caspian region was used. First, the phase behavior alteration of reservoir oil due to the injection of various gases, namely H2S, CO2, CH4, acid, and sour gas was analyzed. Then, the effect of gas type on minimum miscibility pressure (MMP) was investigated based on a semi-analytical tie-line method. Moreover, 2D and 3D numerical simulations were conducted to understand the oil recovery performance of various gas injection options and the effect of permeability heterogeneity on sour gas flooding efficiency. The findings showed that higher H2S content in the injected gas narrows the two-phase envelope and decreases the bubble point pressure. Moreover, it was observed that MMP decreases with increasing H2S concentration, which provides a favorable condition for achieving miscibility. Additionally, an increase in H2S concentration in sour gas improves its oil recovery efficiency by extending gas breakthrough time and elongating the plateau period of oil rate. These results are useful for designing, optimizing, and implementing sour gas injection for EOR in oil reservoirs that have access to sour gas sources.

Exploring the power of machine learning in analyzing the gas minimum miscibility pressure in hydrocarbons

Minimum Miscibility Pressure (MMP) plays a crucial role in subsurface gas injection processes. Hence, the accurate determination and analysis of the effective parameters on MMP are vital for a successful injection project. In this study, different Machine Learning (ML) algorithms are used to identify the most influential parameters on the MMP and develop reliable predictive models. A comprehensive database containing 812 samples (almost all the available experimental data set published from 1961 to 2022) is collected from 66 open literature studies. Six algorithms were employed for feature selection: Sequential Forward Selection (SFS), Sequential Backward Selection (SBS), Sequential Forward Floating Selection (SFFS), Sequential Backward Floating Selection (SBFS), Lasso Regression (LR), and Random Forest Feature Importance (RFFI). These feature selection algorithms were evaluated using a Decision Tree (DT) regressor. The most important features from 42 potential features were x C₅, x C₆, x C₂-C₆, MW C₇⁺, MW Gas, TC, and T, selected using the SBFS method based on the Root Mean Squared Error (RMSE). Using the best-selected features, six predictive models were developed, including LR, DT, Random Forest (RF), Extra Trees (ET), Stacking Regressor (SR), and Voting Regressor (VR). The SR predictive model performed the best with RMSE and R2 values of 18.37 bars and 0.96, respectively, for the testing dataset. The outcomes of this research can be employed for any industrial process involving gas injection into hydrocarbon reservoirs to select the most relevant features in designing the experimental and field trials.

Modeling and comparing minimum miscibility pressure using multiple mixing cells for injection of enriched gases with Naphta, LPG, and NGL

The increase in oil production from hydrocarbon reservoirs has always been of interest due to the increase in global oil consumption. One of the effective and useful methods for enhancing oil recovery from hydrocarbon reservoirs is gas injection. Injectable gas can be injected into two modes, miscible and immiscible. However, to inject more efficiently, different factors, including Minimum Miscibility Pressure (MMP) in the gas near-miscible injection mode, should be investigated and determined. In order to investigate the minimum miscible pressure, different laboratory and simulation methods have been prepared and developed. This method uses the theory of multiple mixing cells to simulate, calculate and compare the minimum miscible pressure in gas injection enriched with Naptha, LPG, and NGL. Also vaporizing and condensing process is also considered in the simulation. The constructed model is presented with a new algorithm. This modeling has been validated and compared with laboratory results. The results showed that dry gas enriched by Naphta due to having more intermediate compounds at lower pressure (16 MPa) is miscible. In addition, dry gas, due to very light compounds, needs higher pressures (20 MPa) than all enriched gases for miscibility. Therefore, Naptha can be a good option for injecting rich gas into oil reservoirs to enrich gas.