Minimum Miscibility Pressure Values Research Articles

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.

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.

Modelling minimum miscibility pressure of CO2-crude oil systems using deep learning, tree-based, and thermodynamic models: Application to CO2 sequestration and enhanced oil recovery

The energy demand is still increasing across the globe, while environmental concerns about global warming effect and greenhouse gases have augmented recently. CO2 injection into mature oil reservoirs is an interesting operation that could help us supply the uprising demand while saving the environment. Having accurate knowledge about CO2 minimum miscibility pressure (MMP) is of utmost importance in designing a successful operation. This study mainly focuses on proposing several tools based on powerful tree-based and deep learning algorithms for estimating the MMP of CO2-crude oil system based on an extensive databank. The models employed in this study include extreme gradient boosting (XGBoost), categorical boosting (CatBoost), light gradient boosting machine (LGBM), random forest (RF), deep multi-layer neural network (deep MLN), deep belief network (DBN), and convolutional neural network (CNN). The models were trained and verified using 310 data points. Along with intelligent models, seven popular empirical correlations and two computational approaches, which are based on thermodynamics, were utilized to be compared with the proposed models. The outcomes expressed that the CatBoost model could estimate CO2 MMP values, using mole percent of volatile (C1 and N2) and intermediate (CO2, H2S, and C2–C5) fractions of oil, the average critical temperature of injection gas (Tcave), reservoir temperature (Tres), and molecular weight of C5+ fraction of oil (MWc5+) as input variables, with a total AARD of 1.34 %. Moreover, the variable impact examination showed that reservoir temperature greatly affects the MMP predictions. Finally, the Leverage approach verified the reliability of the databank and wide applicability domain of the developed CatBoost model spotting 5 outlier points (out of 310 points) only. The findings of this communication shed light on the high accuracy and reliability of CatBoost model in estimating CO2 MMP in a wide range of operational conditions.

A novel experimental-theoretical method to improve MMP estimation using VIT technique

In the gas injection process for enhanced oil recovery (EOR), the interfacial tension (IFT) and the minimum miscibility pressure (MMP) are two key parameters for evaluating the miscibility condition. The vanishing interfacial tension (VIT) method is an efficient method for measuring the interfacial tension of oil and gas versus pressure and can estimate the minimum miscibility pressure. A problem in the VIT test of a hydrocarbon system is that during this test, oil and gas densities vary due to the composition variation of both phases. But in the conventional interfacial measurement, this issue is ignored, and the initial and non-equilibrium densities are utilized for estimating the interfacial tension. In this study, it is tried to nominate a novel method for estimating the most accurate value of IFT. Hence, for this purpose, first a VIT test has been performed for a hydrocarbon gas and a live oil system and using the axisymmetric drop shape analysis (ADSA), the oil droplet has been analyzed, and the geometry factor, which has been defined in this paper, was calculated. After that, the volume of oil droplet and the gas have been measured and were used for vapor-liquid-equilibrium (VLE) or flash calculation using Peng-Robinson equation of state (PR-EOS). By VLE calculation fulfillment, the final composition of two phases is determined. Eventually, the densities of two phases have been calculated for VIT modification. Finally, the IFT results were plotted versus the pressure steps, and the MMP were estimated. Furthermore, to evaluate the results of VIT test and its modification, slim tube displacement (STD) test, which is known as the most reliable laboratory method for measuring the MMP in the oil industry, has been performed. The results show that the values obtained for MMP values for the VIT test with the corrected densities which are lower than the values obtained for the VIT test for not-corrected densities and the suggested experimental-theoretical method has been estimated the MMP more accurately. The MMP obtained by VIT test and modified VIT method was equal to 3858.72 and 3722.0 psi, respectively. Meanwhile, the slim tube test has measured the MMP equal to 3667.13 psi.

Estimation of the minimum miscibility pressure for CO2–crude-oil systems by molecular dynamics simulation

CO2 injection is an effective enhanced oil recovery technique for energy security with the benefits of carbon neutrality. To reach the maximum oil recovery, the miscible condition between CO2 and oil needs to be maintained in the reservoir, which requires the operation pressure to be higher than the minimum miscibility pressure (MMP). There are two types of MMPs: the first-contact MMP (FC-MMP) and the multi-contact MMP (MC-MMP). In this study, molecular dynamics simulations were performed for the CO2–oil interface system using two simplified digital oil models: a Bakken dead oil with four lumping components and a live-crude-oil model with 50 types of oil molecules but with no asphaltenes and heavy oil fractions. The vanishing interfacial tension method was used to predict the MMP. Different CO2–oil volume ratios were considered to mimic the different degrees of vaporization. To estimate the MMP accurately and rapidly, the interfacial tension in the low-pressure regime was used for the prediction. Consequently, different MMPs were obtained, where the MMP value increased with increasing CO2–oil volume ratio. FC-MMP can be predicted when the CO2–oil volume ratio is sufficiently high. When the CO2–oil volume ratio was approximately 9–10, MMP was closest to the actual MC-MMP value. The condensing and vaporizing mechanism was also studied at the molecular scale. Because pure CO2 was used, only the vaporizing effect on MMP occurred. It was found that the intermediate C2–C6 components have the main effect on the MMP calculation. This study can help to establish a computational protocol to estimate FC-MMP and MC-MMP, which are widely used in reservoir engineering.

Reliable estimate of minimum miscibility pressure from multiple possible EOS models for a reservoir oil under data constraint

Multiple Equation of State (EOS) models are possible for a reservoir oil if limited laboratory data is used in the EOS model development; each EOS model has its own predicted minimum miscibility pressure (MMP) value with unknown reliability. This article presents a novel approach to estimate a reliable MMP value using the multiple MMP values calculated from multiple EOS models developed with limited laboratory data such as bubble point and density at bubble point. MMP predicted using the proposed approach has better accuracy than the estimated MMP from an EOS model developed using a large set of data at the regression stage. Each possible EOS model for a reservoir oil has a specific set of values of total Gibbs free energy of mixing (g) at bubble point and predicted MMP for a given injection gas. The MMP estimate is developed using the trend of g versus MMP (predicted) from multiple EOS models in the proposed approach. The AARD in MMP prediction for 22 oils is 5.21% using SRK EOS and 6.65% using PR EOS, which is lower than the earlier approach (7.6%) that uses all PVT, swelling test, and multi-contact test data in EOS model development.

Miscibility characteristics of the CO2/n-hexadecane system with presence of water component based on the phase equilibrium calculation on the interface region

In correspondence to the bright prospects of CO2 EOR technology on greenhouse gas geological storage as well as oil recovery enhancement practices, the phase equilibrium characteristics of CO2/oil/water system was investigated in this paper. n-Hexadecane (n-C16H34) is employed as the oil component and water is introduced into the two phase system as the dissolved component in CO2. PR-EOS with modified alpha functions and Binary Interaction Parameters (BIPs) is employed to calculate the Minimum Miscibility Pressure (MMPs) of the CO2/n-C16H34 system with or without water presence at three temperatures of 40.3 ℃, 55.4 ℃ and 70 ℃. Calculation model and the employed parameters were validated through comparison with corresponding measurements, including the observation on decreased MMPs of the CO2/H2O/n-C16H34 system in comparison with the CO2/n-C16H34 system. Parameter studies were carried out for the CO2/n-C16H34 system with or without water presence at different molar ratios. It is found the existence of water component could reduce the MMP values of the CO2/n-C16H34 system and the degree of the MMP reduction was related to the molar ratio of CO2 in the system. Higher CO2 molar ratio could result in larger MMP deviation between CO2/C16H34 system and CO2/H2O/C16H34 system.

Chemistry of Reservoir Fluids in the Aspect of CO2 Injection for Selected Oil Reservoirs in Poland

Worldwide experiences related to geological CO2 storage show that the process of the injection of carbon dioxide into depleted oil reservoirs (CCS-EOR, Carbon Capture and Storage—Enhanced Oil Recovery) is highly profitable. The injection of CO2 will allow an increasing recovery factor (thus increasing CCS process profitability) and revitalize mature reservoirs, which may lead to oil spills due to pressure buildups. In Poland, such a solution has not yet been implemented in the industry. This work provides additional data for analysis of the possibility of the CCS-EOR method’s implementation for three potential clusters of Polish oil reservoirs located at a short distance one from another. The aim of the work was to examine the properties of reservoir fluids for these selected oil reservoirs in order to assure a better understanding of the physicochemical phenomena that accompany the gas injection process. The chemical composition of oils was determined by gas chromatography. All tested oils represent a medium black oil type with the density ranging from 795 to 843 g/L and the viscosity at 313 K, varying from 1.95 to 5.04 mm/s. The content of heavier components C25+ is up to 17 wt. %. CO2–oil MMP (Minimum Miscibility Pressure) was calculated in a CHEMCAD simulator using the Soave–Redlich–Kwong equation of state (SRK EoS). The oil composition was defined as a mixture of n-alkanes. Relatively low MMP values (ca. 8.3 MPa for all tested oils at 313 K) indicate a high potential of the EOR method, and make this geological CO2 storage form more attractive to the industry. For reservoir brines, the content of the main ions was experimentally measured and CO2 solubility under reservoir conditions was calculated. The reservoir brines showed a significant variation in properties with total dissolved solids contents varying from 17.5 to 378 g/L. CO2 solubility in brines depends on reservoir conditions and brine chemistry. The highest calculated CO2 solubility is 1.79 mol/kg, which suggest possible CO2 storage in aquifers.

Estimation of Minimum Miscibility Pressure for Hydrocarbon Gas Injection Based on EOS

The important parameter used for determining the probable application of miscible displacement is the MMP (minimum miscibility pressure). In enhanced oil recovery, the injection of hydrocarbon gases can be a highly efficient method to improve the productivity of the well especially if miscibility developed through the displacement process. There are a lot of experiments for measuring the value of the miscibility pressure, but they are expensive and take a lot of time, so it's better to use the mathematical equations because of it inexpensive and fast. This study focused on calculating MMP required to inject hydrocarbon gases into two reservoirs namely Sadi and Tanomaa/ East Baghdad field. Modified Peng Robenson Equation of State was used to estimate MMP values for the two samples. The parameters of this equation have been tuned by splitting the plus component and regression process to obtain the best match for PVT properties between the calculated and that measured in the laboratory. Then the MMPs value compared with the results most reliable correlation. Ternary diagram for these samples has been constructed to illustrate the occurrence of miscibility.

Application of Miscible Ethane Foam for Gas EOR Conformance in Low-Permeability Heterogeneous Harsh Environments

SummaryUnconventional plays pose a challenging set of operational conditions, including high temperature, high salinity, low permeability, and fracture networks. Aggressive development of these plays and the low primary recovery factors present an opportunity for using enhanced oil recovery (EOR) methods. This work presents a laboratory investigation of miscible ethane (C2H6) foam for gas EOR conformance in low-permeability, heterogeneous, harsh environments [<15 md, 136,000 ppm total dissolved solids (TDS) with divalent ions, 165°F]. The use of C2H6 as an alternative to carbon dioxide (CO2) offers several operational and availability strengths, which might expand gas EOR applications to depleted or shallower wells. Coupling gas conformance also helps improve displacement efficiencies and maximize overall recovery. Minimum miscibility pressure (MMP) displacement tests were performed for dead crude oil from the Wolfcamp Spraberry Trend area using C2H6 and CO2. Aqueous stability, salinity scan, and static foam tests were performed to identify a formulation. Subsequent foam quality and coreflood displacement tests in heterogeneous carbonate outcrop cores were conducted to compare the recovery efficiencies of three processes: gravity-unstable, miscible C2H6 foam; gravity-stable, miscible C2H6; and gravity-unstable, miscible C2H6 processes. Slimtube tests comparing C2H6 to CO2 resulted in a lower MMP value for C2H6. We identified a stable surfactant blend capable of Type I microemulsion and persistent foams in the presence of oil. Corefloods conducted with gravity-unstable miscible C2H6 foam, gravity-stable miscible C2H6, and gravity-unstable miscible C2H6 recovered 98.4, 61.9, and 42.6% oil originally in place, respectively. Our work shows that miscible C2H6 injection processes achieved significant recoveries even under gravity-unstable conditions. The addition of foam provides better conformance control, enhancing overall recovery at the laboratory scale, showing promise for field applications.

Studying Phase Behavior of Oil/Natural-Gas Systems for Designing Gas-Injection Operations: A Montney Case Study

SummaryAdvances in horizontal drilling and multistage hydraulic fracturing have unlocked tight-oil resources, such as the Montney Formation in the Western Canadian Sedimentary Basin. However, the average oil-recovery factor after primary production is 5 to 10% of the original oil in place. The aims of this study are to investigate phase behavior and to estimate the minimum miscibility pressure (MMP) of the Montney oil/natural-gas systems.First, we measure the MMPs of the oil/gas systems using the vanishing interfacial tension (VIT) technique. The gas samples are methane (C1) and mixtures of methane and ethane (C1/C2). Second, we perform constant-composition-expansion (CCE) tests to study the phase behavior of the oil/gas systems using a pressure/volume/temperature (PVT) cell. To complement the VIT and CCE tests, we perform bulk-phase tests to visualize vaporizing/condensing phenomena at the oil/gas interface using a visualization cell. Finally, we use the measured CCE and MMP data to calibrate the Peng-Robinson (Robinson and Peng 1978) equation of state (PR-EOS) and predict the MMP of the oil/gas systems using ternary diagrams. The results suggest that the dominant mechanism for developing miscibility conditions for oil/C1 and oil/C1/C2 systems is vaporizing and condensing gas drive, respectively. According to the results of the VIT and CCE tests, increasing C2 mole fraction in the gas mixtures significantly reduces MMP of the oil/gas system (from 4,366 psi for oil/C1 to 1,467 psi for oil/C1/C2 with 71.3 mol% C2) and increases the oil-swelling factor (from 1.47 to 1.61 by increasing C2 mol% from 0 to 70 mol%). The results of visualization tests show that the presence of C2 in the injection gas significantly enhances oil swelling compared with the pure-C1 case. We observe vaporizing flows of oil components in all tests and strong condensing flows of C1 and C2 into the oil phase in the C1/C2 test with increasing gas-injection pressure. The MMP values predicted by plotting two-phase equilibrium data on ternary diagrams appear to be in good agreement with the measured ones. The results can be used to optimize the injection-gas composition and operating pressure in the Montney.

Modeling minimum miscibility pressure of pure/impure CO2-crude oil systems using adaptive boosting support vector regression: Application to gas injection processes

Carbon dioxide based enhanced oil recovery (CO2-EOR) techniques have been of great interest due to CO2 effectiveness as an oil solvent under supercritical condition and potential application to the sequestration purposes of CO2. Appropriate design of these techniques such as CO2 gas injection process needs accurate knowledge of the minimum miscibility pressure (MMP) allowing to the injected gas to be miscible with the oil. In this paper, three intelligent models named group method of data handling (GMDH), adaptive boosting support vector regression (AdaBoost SVR) and multi-layer perceptron (MLP) were implemented for MMP prediction in systems oil - CO2 streams. To this end, a widespread databank covering extended range of reservoirs and thermodynamic conditions was considered. The data bank covers dead and live oils under reservoir temperatures up to 388.73 K, while the gathered real MMP values were ranged between 6.54 MPa and 31.30 MPa. Graphical and statistical assessment criteria were performed to examine the reliability of the implemented paradigms and to compare them with the most well-known models. The results of this study indicated that the established models outperform the existing ones. In addition, among the proposed models, AdaBoost SVR has the highest accuracy with an Average Absolute Percent Relative Error (AAPRE) of 3.09% and Root Mean Square Error (RMSE) of 0.9 MPa. All of the proposed models can be applied in gas injection processes to prevent overestimation and underestimation of MMP, leading to appropriate performance of gas injection.

An improved correlation to determine minimum miscibility pressure of CO2–oil system

An accurate and reliable estimation of minimum miscibility pressure (MMP) of CO2–oil system is a critical task for the design and implementation of CO2 miscible displacement process. In this study, an improved CO2–oil MMP correlation was developed to predict the MMP values for both pure and impure CO2 injection cases based on ten influential factors, i.e. reservoir temperature (TR), molecular weight of C7+ oil components (MWC7+), mole fraction of volatile oil components (xvol), mole fraction of C2C4 oil components (xC2-C4), mole fraction of C5C6 oil components (xC5-C6), and the gas stream mole fractions of CO2 (yCO2), H2S (yH2S), C1 (yC1), hydrocarbons (yHC) and N2 (yN2). The accuracy of the improved correlation was evaluated against experimental data reported in literature concurrently with those estimated by several renowned correlations. It was found that the improved correlation provided higher prediction accuracy and consistency with literature experimental data than other literature correlations. In addition, the predictive capability of the improved correlation was further validated by predicting an experimentally measured CO2–oil MMP data, and it showed an accurate result with the absolute deviation of 4.15%. Besides, the differential analysis of the improved correlation was analyzed to estimate the impact of parameters uncertainty in the original MMP data on the calculated results. Also, sensitivity analysis was performed to analyze the influence of each parameter on MMP qualitatively and quantitatively. The results revealed that the increase of xC2-C4, xC5-C6 and yH2S lead to the decrease of MMP, while the increase of TR, MWC7+, xvol, yCO2, yC1, yHC and yN2 tend to increase the MMP. Overall, the relevance of each parameter with MMP follows the order of TR > xC5-C6 > MWC7+ >xvol > yH2S > yHC > yCO2 >yC1 >yN2 >xC2-C4.

Prediction of minimum miscibility pressure of pure CO2, carbon dioxide gas mixtures and polymer-supercritical CO2 in oil using modified quadrupole Cubic Plus Association Equation of State (mqCPA EoS)

In this work, the modified quadrupole Cubic Plus Association Equation of State (mqCPA EoS) is used to predict the minimum miscibility pressure (MMP) of pure carbon dioxide, carbon dioxide gas mixtures and polymer-supercritical carbon dioxide (scCO2) systems with the different oils. Carbon dioxide is accounted as a quadruple molecule and by applying Ahmadi and Johns's algorithm, which is a multiple mixing cell (MMC) method, minimum miscibility pressures (MMP) for some scCO2-oil systems are predicted. Moreover, a specific parameterization work was performed so that the new binary interaction parameters, kij, were optimized for the hydrocarbon-CO2 pairs using mqCPA with the quadropolar term. For comparison of the present equation of state (EoS) with the common EoSs, the predictive Peng-Robinson 78 (PPR78) and Soave-Redlich-Kwong (SRK) are applied along with the binary interaction parameter correlations of the Pedesen and Xu et al. kij (Industrial & Engineering Chemistry Research, 54 (2015) 2816–2824). The obtained MMP values by mqCPA EoS are compared to the experiments and those obtained using the PPR78 and SRK EoSs. It is shown that the calculated results by mqCPA EoS demonstrate a good agreement with the experimental values, especially for injected of pure CO2 and leads to the better results in comparison with PPR78 and SRK EoSs. To predict MMP of the polymer-scCO2 systems, three types of poly(lactic acid) (PLA), three types of poly(1-O-(vinyloxy) ethyl-2,3,4,6-tetra-O-acetyl-β-d-glucopyranoside) (P(AcGlcVE)) and seven types of poly(vinyl acetate-alt-dibutyl maleate) (PVAc-alt-PDBM) are used. To our best knowledge, this is the first effort to predict the MMP of these polymer-scCO2-oil systems.

Estimation of minimum miscibility pressure (MMP) in enhanced oil recovery (EOR) process by N2 flooding using different computational schemes

Nitrogen is an effective agent to be considered in gas injection processes as a part of enhanced oil recovery (EOR) process. Successful design and implementation of nitrogen flooding scenarios greatly depend on accurate prediction of minimum miscibility pressure (MMP). This work highlights the application of three models namely GA-RBF, PSO-ANFIS and MLP for estimation of pure and impure MMP value in nitrogen-crude oil systems based on reliable and valid experimental data covering a wide range of operational parameters gathered from literature. Various statistical and graphical methods were utilized to evaluate the performance of the developed models. The results of the developed models are also compared with reported literature methods for estimation of nitrogen MMP. Results show that the proposed GA-RBF, CHPSO-ANFIS and MLP models are accurate for estimation of experimental data with overall average absolute relative errors of 1.9%, 2.92% and 3.59% and overall R2 values of 0.9847, 0.9686 and 0.9485, respectively. Moreover, the proposed models successfully outperform other literature methods and present more accurate and reliable results.

Minimum miscibility pressure and interfacial tension measurements for N2 and CO2 gases in contact with W/O emulsions for different temperatures and pressures

In this research, the IFT behavior of two different specimens of W/O emulsion with distinctive soluble ingredients of water in contact with CO2 and N2 was examined. The Minimum Miscibility Pressure (MMP) of the mentioned gases with emulsion specimens were measured and compared with the case of the original crude oil with no water content. This study focuses on the quantity of water in the W/O emulsion specimens and its effects on IFT and MMP values. The IFT behavior of W/O emulsions was surveyed for two different cases of distinctive water soluble ingredients, i.e. sea water and reservoir brine. The tests were performed under high pressure-high temperature (HPHT) conditions utilizing Axisymmetric Drop Shape Analysis (ADSA) procedure. The equilibrium IFT values between the two distinctive specimens of W/O emulsions with different amounts and compositions of dispersed water and two types of gases, i.e. CO2 and N2, were measured. The outcomes were compared with the behavior of original crude oil, i.e. crude oil with no water content. The temperature was set in two distinctive values of 313.15 K and 333.15 K, and the pressure changes in the scope of 1 MPa–20.68 MPa. The outcomes manifested that the IFT behavior of the emulsion could be correlated directly with pressure for two distinctive variation rates, categorized in two different regions. Comparing to the original crude oil, in the case of W/O emulsion the equilibrium IFT increases, and this incremental behavior is much significant in the case of N2-emuslion system. Additionally, the outcomes of IFT versus pressure, in the case of N2-emulsion system, manifested that the slope of the first part of the curve decreases with increment in dispersed water content in the crude oil. However, the IFT values versus pressure in the second region were not affected by the water content of the emulsion. Also, Vanishing Interfacial Tension (VIT) technique was used to estimate the MMP of N2-emulsion systems. According to the outcomes, MMP was increased in the existence of water, and the incremental behavior becomes significant when the water content is increased. It is worthy to note that the outcomes of the CO2-emulsion systems manifested that both IFT behavior and MMP values were not changed significantly by water content. Finally, in light of the test information gathered in this research, various relationships were proposed to express the IFT and MMP correlations as dependants of pressure at distinctive temperatures.

Application of adaptive neuro fuzzy interface system optimized with evolutionary algorithms for modeling CO2-crude oil minimum miscibility pressure

CO2 injection is known as one of the most reliable enhanced oil recovery techniques. The success of every gas injection process depends highly on the minimum miscibility pressure (MMP) needed for the injected gas and the oil to reach miscibility. Therefore, determination of the MMP between the two fluids is of great importance. In this study, a novel intelligent model based on adaptive neuro fuzzy interface system (ANFIS) was developed for predicting MMP values between pure/impure CO2 and reservoir oil at different reservoir conditions based on 270 experimental data points for pure and impure CO2, dead and live oils, reservoir temperature ranges from 293.72K to 388.73K, and experimental MMP values range from 6.54MPa to 31.30MPa. The ANFIS model was optimized by five different approaches; including Back Propagation (BP), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Differential Evolution (DE). A large number of data points from various sources of literature were gathered for model development and verification. In addition, various statistical and graphical error analyses were employed to evaluate the performance of the developed models as well as to compare them with major literature models for MMP prediction. The results showed that the ANFIS model optimized by PSO has the highest accuracy among all the models developed in this study as well as literature models, with an average absolute percent relative error of only 7.53%. In addition, all models developed in this study are more accurate than the existing models and their accuracy are as follows: ANFIS-PSO>ANFIS-GA>ANFIS-ACO>ANFIS-BP>ANFIS-DE. Lastly, the ANFIS models developed here can be inserted in any simulator to increase the accuracy of predicting pure and impure CO2-crude oil MMP.

Investigation of the minimum miscibility pressure for injection of two different gases into two Iranian oil reservoirs: Experimental and theory

AbstractThe results of the minimum miscibility pressure (MMP) determination for miscible injection of two gases (CO2 and an associated gas of one of Iranian gas reservoirs) into two different oil samples from two Iranian oil reservoirs using a slim tube apparatus are presented in this work. For efficient determination of MMP, prior to slim tube experimentation, cell‐to‐cell simulation of the slim tube experiment was performed using a tuned Peng Robinson equation of state as a pre‐experiment and the results were used as initial estimates of MMP to select the pressure steps for the slim tube experiment. Finally, a comparison between the measured MMP values obtained by the slim tube experiments and those calculated by cell‐to‐cell simulation was made. It was shown that the cell‐to‐cell slim tube simulation predicts the results of slim tube experiments with a relative error of less than 6 %. This low error value shows that cell‐to‐cell simulation can replace the slim tube test in the cases where time is a major concern. Moreover, since the slim tube is an expensive and time‐consuming experiment and selecting the pressures to run the test is very important, cell‐to‐cell simulation can help us select the pressures for performing a slim tube experiment.

Experimental and analytical methods to determine minimum miscibility pressure (MMP) for Bakken formation crude oil

The Bakken is one of the shale reservoirs that has been discovered to hold a vast amount of resource and is contributing to the production boom in the US. This unconventional reservoir, like most others, displays favorable initial production rates due to stimulation by hydraulic fracturing, but production rates quickly decline after few months. Due to the extremely low permeability and low recoveries, miscible gas injection is considered for improving the recovery of oil in the Bakken formation. Feasibility of miscible gas injection in the Bakken would depend on the analysis of minimum miscibility pressure (MMP) experiments.The Rising Bubble Apparatus (RBA) has been chosen for the purpose of these experiments. The RBA provides results in a short amount of time using small amounts of fluid samples. The RBA consists of a cell gage containing a flat glass tube where oil samples are placed and an injection needle where gas is injected into the flat glass tube. To simulate reservoir conditions, the glass tube is pressurized using de-ionized water, and heating plates surrounding the cell are used to regulate temperature. Visual observation of the injected gas bubble behavior is captured by a camera as it rises and moves upward along the oil column. By observing the shape and dissolution behavior of the bubble, the MMP can be determined.MMP results from a Bakken crude sample are shown to range from 2100 to 3500psi at temperatures from 160 to 240°F using CO2 as the injection fluid. Other injection fluids such as nitrogen and hydrocarbon gases have been tested and also provided reasonable MMP values. MMP results from Bakken crude oil samples were compared to existing correlations, and the correlations were found to produce mostly unreliable MMP results for the Bakken oils evaluated in the study. On the other hand, an equation of state phase behavior program showed similarities with the RBA MMP results.The impact of different injection fluids, inclusive of CO2 and enriched hydrocarbon gases is the subject of this study. MMP results are influenced by the choice of injection fluids, providing valuable information for economic production and increased recovery in the Bakken formation. The results from this study provide a range of MMP data that can be used in planning pilot tests for miscible gas injection in the Bakken.

Experimental Determination of Minimum Miscibility Pressure

Minimum miscibility pressure (MMP) plays a great role in determining the displacement efficiency of different gas injection processes. Experimental techniques for MMP determination include industrially recommended slim tube, vanishing interfacial tension (VIT) and rising bubble apparatus (RBA). In this paper, MMP measurement study using slim tube and VIT experimental techniques for two different crude oil samples (M and N) both in live and stock tank oil forms is being presented. VIT measured MMP values for both’M’ and’N’ live crude oils were close to slim tube determined MMP values with 6.4 and 5% deviation respectively. Whereas for both oil samples in stock tank oil form, VIT measured MMP showed a higher unacceptable deviation from slim tube determined MMP. This higher difference appears to be related to high stabilized crude oil heavier fraction and lack of multiple contacts miscibility. None of the different nine deployed crude oil – CO2 MMP computing correlations could result in reliable MMP, close to slim tube determined MMP. Since VIT determined MMP values for both considered live crude oils are in close match with slim tube determined MMP values, it confirms reliable, reproducible, rapid and cheap alternative for live crude oil MMP determination. Whereas VIT MMP determination for stock tank oil case needed further investigation about stabilization / destabilization mechanism of oil heavier ends and multiple contacts miscibility development issues.