Very High Temperature Laboratory CO2 Injection

Although gas flooding has been successfully applied for enhanced oil recovery throughout the world, most of its applications are conducted in low, ultralow, and tight oil reservoirs with light oil. Studies focused on a low-permeability reservoir with medium viscous oil are rarely reported, and there is little experience in the development of this type of reservoir for reference. Based on the special characteristics of low-permeability formation coupled with medium viscous oil in Niuquanhu Block, China, the gas-oil interactions of different gases are first evaluated through the pressure-volume-temperature (PVT) analysis. Then, the minimum miscibility pressure (MMP) of different gases is compared using slim tube experiments and a numerical simulation method. The oil recovery of different gas floodings is studied using core flooding experiments, and then the output oil compositions of different gas floodings are analyzed using a total hydrocarbon chromatograph. The PVT analysis results show that the interactions between hydrocarbons and medium viscous oil are the strongest compared with other gases. Under formation conditions, about 70 mol % hydrocarbons is dissolved in the medium viscous oil, leading to a 69% reduction of oil viscosity and a 48% increment of oil swelling, which is 1.19 and 1.35 times those of CO2. The reduction of oil viscosity and increment of oil swelling of hydrocarbons are 1.64 and 2.02 times those of CH4. And the reduction of oil viscosity and increment of oil swelling of hydrocarbons are 2.23 and 2.67 times those of N2. Slim tube experiments show that the MMPs of hydrocarbon flooding, CO2 flooding, CH4 flooding, and N2 flooding are 28.5, 36.8, 46.4, and 61.6 MPa, respectively. Therefore, compared with the other three types of gases, hydrocarbon flooding has the lowest MMP for low-permeability reservoirs with medium viscous oil. The errors between the MMPs of hydrocarbon flooding, CO2 flooding, CH4 flooding, and N2 flooding obtained by the numerical simulation method and the results obtained by the slim tube experiment method are 0.71, 0.82, 0.87, and 0.98%, respectively. The numerical simulation results of the slim tube experiment show that the flooding pressure and oil recovery curves of different gas floodings all have inflection points. Under the existing condition, the inflection point pressure value is unchanged by changing the PV values of different gas injections. According to the results of a series of core flooding experiments and the analysis of the output oil compositions of different gas floodings, the oil recoveries of hydrocarbon flooding, CO2 flooding, CH4 flooding, and N2 flooding are 57.02, 51.11, 36.88, and 21.35%, respectively, and the extraction ability of different gases to light hydrocarbon components is ranked as hydrocarbons > CO2 > CH4 > N2. The findings revealed in this paper can provide technical support for gas flooding development in similar low-permeability reservoirs with medium viscous oil.

One of the most effective enhanced oil recovery techniques is carbon dioxide (CO2) flooding. It is because of its high oil recovery rate and associated advantage on the environment. CO2 flooding has been broadly used and commercially proven. Depending on the reservoir and operational conditions, it can be implemented either in immiscible or miscible modes. Determining the injection mode depends on the minimum miscibility pressure (MMP). The conventional ways of determining the MMP (slim-tube experiments, supercritical extractor, etc.) are costly and time-consuming. A simulation approach has been deployed to determine the MMP of a synthetic reservoir model using a one-dimension compositional slim-tube model in ECLIPSE300. The MMP was also determined using the group method of data handling (GMDH) and other existing correlations. The MMP determined by slim-tube simulation was ~ 4176 psia. Comparing the MMPs of the correlations to the slim-tube simulation, the correlation by Maklavani et al. (Braz J Pet, 2010) was the most accurate with a mean absolute percentage error (MAPE) of 0.79%. The GDMH and the correlation of Firoozabadi and Khalid had MAPEs of 4.96% and 6.06%, respectively. The GMDH model introduced in this study was not as accurate as the correlation by Maklavani et al. (Braz J Pet, 2010) . The model could be improved, or other machine learning models with improved training and prediction could be deployed to estimate MMP more accurately. A synthetic reservoir model based on literature data was used to investigate the effect of the MMP and injection rate on oil recovery by CO2 flooding. The impact of MMP was investigated by the miscible and immiscible flooding scenarios. The injection rate was varied in each scenario to determine the optimum injection rate. However, the scenarios with optimum injection rates for both miscible and immiscible CO2 injection were compared to a waterflood scenario. The optimum injection rates for miscible and immiscible flooding were 2800 and 2200 Mscf/day, respectively. The oil recovery efficiencies for the optimum miscible and immiscible injection were 48% and 46%, respectively. In this study, miscible flooding proved to be the more effective method in oil recovery. However, considering the difference in oil recovery and the difficulty in achieving miscibility, the immiscible CO2 flooding proves to be the feasible option for improving oil recovery.

Summary Miscible gas injection is the most widely applied enhanced oil recovery (EOR) method in light oil carbonate reservoirs as a tertiary and secondary method. Miscible gas has high displacement efficiency and usually results in a low residual oil saturation (Sorm) in the parts of the reservoirs that are in contact with the gas. Accurate determination of Sorm and understanding the parameters that affect displacement efficiency are crucial for successful miscible gas EOR projects. In this paper, we present a comprehensive experimental program designed to investigate the effect of a number of parameters on oil recovery, displacement efficiency, and Sorm of miscible and near-miscible carbon dioxide (CO2) injection. The parameters investigated in this study are the experimental pressure, pore volume (PV) injected, injection rate, rock type, and initial water saturation (Swi). The coreflood experiments were performed using live crude oil at pressures starting below the minimum miscibility pressure (MMP) to pressure well above the MMP, using reservoir core samples of up to 1 ft long and 2 in. diameter. All CO2 injection experiments were performed using vertically oriented cores, with gas injection from the top to ensure stable displacement. The experimental results show that (1) Oil recovery decreases as pressure decreases with Sorm increasing by more than 20 saturation units as the pressure decreases from 4,250 psi to 2,700 psi; (2) CO2 breakthrough was much earlier at lower pressure, which leads to more CO2 recycling and potentially lower CO2 sequestration volume; (3) the recovery factor (RF) is strongly affected by the PV injected, and this effect is much more significant for the experiments performed at lower pressure; (4) the injection rate has an insignificant impact on oil recovery and Sorm for miscible or near-miscible CO2, due to the low interfacial tension (IFT) between oil and CO2; (5) rock heterogeneity has a strong effect on oil recovery and CO2 breakthrough and hence on CO2 recycling and economy of the projects; and (6) the presence of mobile water at the beginning of CO2 injection resulted in lower displacement efficiency and increased Sorm. However, this water blocking effect should be determined experimentally for a given reservoir rock/fluid system. The results of this study cannot be generalized for other reservoirs. The results of this study have important implications for the design and performance predictions of CO2 injection in the reservoirs under study. Starting CO2 injection at reservoir pressure, which, in some cases, is more than 1,500 psi above MMP, is recommended due to its superior displacement efficiency and less CO2 recycling due to later breakthrough. However, a higher pressure may negatively impact the required CO2 volume, the compression cost, and project economics.

Over the years, the slim tube experiment has been the most commonly used laboratory technique for determination of minimum miscibility pressure (MMP) for designing field miscible floods. However, till now, the design of these experiments is not standardized, neither in terms of set-up nor procedure. Often, the set-up, characteristics of the slim tube coil and even the experimental procedures are left to the discretion of the experimentalist, leading to very uncertain and non-unique MMP values, to say the least. Not just the uniqueness is of great concern, but also the lack of measurement repeatability; two measurements using same fluid samples under the "same experimental conditions" may result in too different MMP values. Matching these experiments with any PVT simulation package may pose a challenge, which even if a match is achieved, may be of questionable reliability. It is on this premise that this work was based. Slim tube experiments were designed and performed to study the effects of some parameters on the uniqueness and repeatability of the MMP measurements. It was found that MMP measurements are different with different injection rates. The lowest tested rate showed slightly lower MMP and better recovery performance than the other tested rates. No clear trend was noted, however. MMP was found to be lower for the larger coil diameter of the two investigated. MMP decreased as the coil length increased. The decrease in MMP with increase in coil length followed a parabolic trend. It was, therefore, concluded that laboratory measurements of MMP using the slim tube apparatus is a function of not just the characteristics of the interacting fluids but also those of the coil used as well as the choice of injection rates. The experimental design and procedure need to be unified to produce more reliable MMP data. It is the recommendation of the authors to design the experimental injection rate based on the expected field gas injection, to use the largest coil diameter possible, and to design the coil length, based on the expected well spacing between the injector and producer.

Gas injection as an EOR method is being considered for the giant Al Shaheen field, located offshore Qatar. The field is characterized by large lateral variations in fluid properties; the oil gravity ranges from 16 to 38 °API and significant variations in initial GOR and saturation pressure are observed.An extensive experimental program aimed at establishing the miscibility behaviour for this complex fluid system has been performed. Experiments included a range of gas injection tests such as swelling and multi-contact miscibility tests, enrichment studies and slimtube measurements. The miscibility behaviour across the range of oil gravities has been very well captured with a single equation of state (EOS) model, as described by Lindeloff et al. (2008).Slimtube measurements are the preferred method for establishing minimum miscibility pressures experimentally as condensing/vaporizing effects can be captured in this setup. The physical dispersion of the slimtube was characterized by a specially designed experiment using first-contact miscible (FCM) fluids. The results of the FCM experiments were used to determine the degree of numerical dispersion required in a 1D slimtube simulation model to match the measured data. An extrapolation towards an infinite number of cells was then performed to estimate the dispersion-free minimum miscibility pressure (MMP) from the slimtube experiments conducted on live reservoir oil using carbon dioxide as injection gas.In addition to the slimtube simulations, several algorithms for estimating the minimum miscibility pressure have been compared; some are empirical correlations, others are based on analytical gas injection theory using the method of characteristics (MOC) limiting tie-line method and the last one relies on a mixing-cell approach. The advantages and drawbacks of each approach are discussed, and the results are compared to laboratory data. In general, there is a very large spread in predicted MMP using carbon dioxide as injection gas. Empirical correlations generally overpredict the MMP for light oils and underestimate the MMP for heavy oils. Various key tie-line methods using the same tuned EOS model provide very different estimates of the MMP and some of them exhibit convergence problems. The results of the present work suggest that the mixing-cell model provides the most robust estimate of MMP over a large range of oil compositions, subject to EOS description. In essence, there is currently no prediction method that can replace the slimtube experiments.

A comparison of CO 2 minimum miscibility pressure determinations for Weyburn crude oil

Summary An accurate minimum miscibility pressure (MMP) is one of the key factors in miscible-gasflood design. There is a variety of experimental and analytical methods to determine the MMP, but the most-reliable methods are slimtube experiments, 1D slimtube simulations, mixing-cell models, and the fast key-tie-line approach using the method of characteristics (MOC). Direct comparisons of all these methods generally agree well, but there are cases in which they do not. No explanation has yet been given for these anomalies, although the MMP is critically important to recovery. The focus of this paper is to explain when current MOC results assuming that shocks exist from one key tie line to the next may not be reliable, and how to identify when this is the case. We demonstrate, using fluid characterizations from Middle East oils, that the MMPs using this MOC method can be more than 6,500 psia greater than those calculated using a recently developed mixing-cell method. The observed differences in the MMP increase substantially as the API gravity of the oil decreases, likely the result of the onset of L1-L2-V behavior. We show that the key tie lines determined using this MOC method do not control miscibility for such cases. We explain the reasons for these differences using simplified pseudoternary models and show how to determine when an error exists. We also offer a way to correct the MMP predictions using the MOC for these complex gas/oil displacements without solving for the complete compositional path.

Carbon dioxide (CO2) miscible flooding is one of the Enhanced Oil Recovery (EOR) methods that has been recognized as a promising method to improve of oil recovery before abandonment. In addition, many issues related to global warming or greenhouse effect due to CO2. By using CO2 as either miscible or immiscible flooding to enhance oil recovery injected into reservoir, it may help reduce environmental problems. Carbon dioxide (CO2) is able to improve of oil recovery effectively by important key parameter: minimum miscibility pressure (MMP), viscosity, and density. This paper aims to determine the effect of CO2 volume injection to reservoir fluid characteristic in order to CO2 miscible flooding for displacing the oil production. This research was carried out by some series of laboratory experiment that involve PVT test, slim tube test, and swelling test. The result from laboratory experiments were used to observe the use of CO2 and its effect on reservoir fluid characteristics such as viscosity, solubility, and swelling factor. MMP obtained from slim tube test is 2805 Psi. Based on the results, all trend of parameters: viscosity, solubility, and swelling factor showed the positive impact of CO2 have on liquid recovery.

Minimum miscibility pressure (MMP) is defined as the minimum pressure at which the CO2 is dissolved in the oil phase inside the reservoir. Minimum miscibility pressure (MMP) plays a critical role in the CO2 injection process during miscible CO2 flooding. Experimentally, MMP is determined by slim-tube experiments, rising bubble method etc. However, experimental analysis is time consuming and can have high associated cost. Therefore, application of Artificial Intelligence (AI) techniques can assist in predicting the MMP based on the available input data. This will save significant time and efforts and predicted the MMP results faster and convenient way. Some authors have worked with AI tools to predict MMP, but the model proposed in this paper has a relatively lower error. Thus, the proposed model in this study is an improved model for the prediction of MMP for miscible CO2 flooding applications. A detailed optimization was carried out in this study for both ANN and ANFIS predictive tools. Single hidden layer with 12 neurons and ‘trainlm’ as training algorithm was found out after ANN optimization, whereas subtractive clustering with cluster radius of 0.3 was the optimum scenario for ANFIS technique. ANN prediction was overall better than ANFIS technique for the prediction of CO2 MMP.

Minimum miscibility pressure (MMP) is defined as the minimum pressure at which the CO2 is dissolved in the oil phase inside the reservoir. Minimum miscibility pressure (MMP) plays a critical role in the CO2 injection process during miscible CO2 flooding. Experimentally, MMP is determined by slim-tube experiments, rising bubble method etc. However, experimental analysis is time consuming and can have high associated cost. Therefore, application of Artificial Intelligence (AI) techniques can assist in predicting the MMP based on the available input data. This will save significant time and efforts and predicted the MMP results faster and convenient way. Some authors have worked with AI tools to predict MMP, but the model proposed in this paper has a relatively lower error. Thus, the proposed model in this study is an improved model for the prediction of MMP for miscible CO2 flooding applications. A detailed optimization was carried out in this study for both ANN and ANFIS predictive tools. Single hidden layer with 12 neurons and ‘trainlm’ as training algorithm was found out after ANN optimization, whereas subtractive clustering with cluster radius of 0.3 was the optimum scenario for ANFIS technique. ANN prediction was overall better than ANFIS technique for the prediction of CO2 MMP.

Objectives/Scope: The purpose of this thesis is to reduce CO2-oil minimum miscible pressure (MMP) in CO2 flooding some heavy oil which is difficult to miscible with CO2 in general cases. 2 Methods, Procedures, Process: In order to reduce CO2-oil minimum miscible pressure (MMP), a brave idea of injection miscible-slug instead of pure CO2 into reservoir was proposed, and then several slim-tube tests with different pressures were deployed to acquire the composition of miscible-slug, and a consecutive series of output samples including oil and gas from slim-tube at different injection pore-volume CO2 were collected, composition of every output samples was tested and analyzed by using equipment of liquid phase chromatograph and gas phase chromatograph. 3 Results, Observations, Conclusions: Composition of consecutive output samples at different injection pore-volume CO2 were obtained through the help of gas & oil phase chromatograph, and the result above shows the quit difference between miscible-slug and immiscible-slug. The components with molecular weight lighter than C18 are mainly extracted by CO2 immiscible-slug, while some additional components with molecular weight between C18 and C25 are also extracted by CO2 miscible-slug. Moreover, low-carbon molecules are initially extracted, with the ongoing flooding, higher-carbon molecules are gradually extracted. Based on the composition of consecutive output samples, man-made miscible-slug for the this oil reservoir was made up and the slug PV was amplified used for injection instead of CO2, another slim-tube test using above man-made miscible-slug was deployed again with pressure lower than MMP obtained from above series of slim-tube tests, the result shows a CO2 –oil miscible flooding and the idea of CO2 –oil MMP reduction comes true. 4 Novel/Additive Information: A method of reduction CO2 –oil MMP by injection man-made miscible-slug made up from slim-tube tests was proved, which would improve a lot of oil reservoir immiscible with CO2 into miscible with CO2 under reservoir temperature.

Low-temperature oil displacements by CO2 involve complex phase behavior, where three hydrocarbon phases can coexist. Reliable design of miscible gas flooding requires knowledge of the minimum miscibility pressure (MMP), which is the pressure required for 100% recovery in the absence of dispersion or as defined by slim-tube experiments as the "knee" in therecovery curve with pressure where displacement efficiency is greater than 90%. There are currently no analytical methods to estimate the MMP for multicomponent mixtures exhibiting three hydrocarbon phases. Also, there are no reliable numerical methods to estimate the MMP using compositional simulation largely because of robustness issues of three-phase equilibrium calculations, inaccurate three-phase relative permeability models, and phase identification and labeling problems that can cause significant discontinuities and failures in the simulation results. How miscibility is developed, or not developed, for a three-phase displacement is not well known. We developed a new multiple three-phase mixing cell method that gives a relatively easy and robust way to determine the pressure for miscibility or more importantly the pressure for high displacement efficiency. The procedure that moves fluid from cell to cell is robust because it is independent of phase labeling (i.e. vapor or liquid), has a robust way to provide good initial guesses for three-phase flash calculations, and is also not dependent on three-phase relative permeability (fractional flow). These three aspects give the mixing cell approach significant advantages over using compositional simulation to estimate MMP or to understand miscibility development. The approach can be integrated with previously developed two-phase multiple mixing cell models because it uses the tie-line lengths from the boundaries of tie triangles to recognize when the MMP or pressure for high displacement efficiency is obtained. Application of the mixing cell algorithm shows that unlike most two-phase displacements the dispersion-free MMP may not exist for three-phase displacements, but rather a pressure is reached where the dispersion-free displacement efficiency is maximized. This is the first paper to examine a multiple mixing cell model where two- and three-hydrocarbon phases occur and to calculate the MMP and/or pressure required for high displacement efficiency for such systems.

Gas injection has become a significant enhanced oil recovery (EOR) measure to develop low permeability reservoirs. CO2 injection can achieve miscible displacement, but its cost is relatively high and CO2 is corrosive. N2 injection is cheap, but it is difficult to achieve miscible displacement in the formation with a limited EOR efficiency. Based on these problems, a feasibility analysis of CO2 slug+N2 to boost the recovery in low permeability reservoirs is studied through experiment. In this paper, with slim-tube test and core flood experiment, an analysis of minimum miscibility pressure, recovery of different gas injection scheme, and sensitivity of oil displacement efficiency of CO2 slug+N2 are obtained. The results show that the scheme of CO2 slug+N2 gets low miscibility pressure and can achieve miscible displacement with high ultimate recovery approximate to the scheme of continuous injection of CO2. Besides, injection timing, slug size of injected CO2, and formation pressure recovery before CO2 slug injection greatly influence the ultimate recovery. This study is significant for the understanding of EOR mechanism of CO2 slug+N2, optimization of injection parameters, and associated numerical simulation in low permeability reservoirs.

Miscible gas injection nowadays becomes an imperative enhanced oil recovery (EOR) approach for increasing oil recovery. Due to the massive cost associated with this approach a high degree of accuracy is required for predicting the outcome of the process. Such accuracy includes, the preliminary screening parameters for gas miscible displacement; the "minimum miscibility pressure" (MMP) and the availability of the gas. All conventional and stat-of-the-art MMP measurement methods are either time consuming or decidedly cost demanding. Therefore, in order to address the immediate industry demands a nonparametric approach (ACE) is employed in this study to estimate an important parameter MMP. ACE algorithm correlates optimal transforms of a set of predictors with an optimal response transform. Finally, the proposed model has produced a maximum linear effect between these transformed variables. More than 100 MMP data points are considered both from the relevant published literature and experimental work. The test data points also MMP measurements that are experimentally obtained for Kuwaiti crude Oil. The proposed model is validated using detailed statistical analysis and it reveals that the results are more reliable than the existing correlations for pure CO2 injection to enhance oil recovery. In addition to its accuracy, the ACE approach is more powerful, quick and can handle a huge data.

Multicontact miscible displacement processes are becoming increasingly popular as a means of recovering secondary and tertiary oil reserves in the U.S. and Canada. Economics of multicontact miscible flooding are governed to some extent by the availability of large sources of high purity CO2 or suitable liquefied petroleum gas (LPG) streams. This is because achievement of miscibility depends on the solvent composition as well as the system temperature and pressure. Atypical components in a CO2 or solvent stream therefore may increase the required pressure or enrichment levels for achievement of miscibility. Several papers have been published discussing the pressure (for CO2) and composition (for rich gas) levels required for miscible displacement. The potential CO2 supply could be increased if complicated cleanup procedures for injected and produced fluids were not required. For engineering studies it is important that CO2 streams containing H2S and hydrocarbons be evaluated for their miscible flooding potential. It is also important to evaluate the effects of CO2 and C5 + components in rich gas mixtures to determine whether they can be used to reduce calculated enrichment levels for solvent systems. This paper presents results of studies using mixtures of CO2, H2S, and C1, CO2-LPG, and rich gas solvents containing CO2 or C5 to displace oil miscibly in slim-tube experiments. The purpose of this work is to show the effects of various components on pressure and compositions required for miscibility. As expected, the changes in CO2 miscibility pressure are direct functions of temperature. It is reported that the addition of H2S and C2+ hydrocarbons lowers the miscibility pressure for CO2, whereas the presence of C1 in a CO2 solvent increases it. More important, the results give a quantitative titative measure of the degree of reduction/elevation in miscibility pressure to be expected with impure CO2 streams. The paper also presents similar results from displacements with typical rich gas solvents mixed with CO2 and/or C5. It is reported that CO2 increases the minimum enrichment required, while a heavier hydrocarbon component actually can reduce anticipated enrichment levels.