Determination of Minimum Miscibility Pressure by Analytical Method

Miscible gas injection processes are among the effective methods for enhanced oil recovery (EOR). A key parameter in the design of gas injection project is the minimum miscibility pressure (MMP), whereas local displacement efficiency from gas injection is highly dependent on the MMP. Because experimental determination of MMP is very expensive and timeconsuming, searching for fast and robust mathematical determination of gas-oil MMP is usually wished. A new CO2 MMP correlation based on Multiple-Linear-Regression modeling (MLR) technique has been successfully developed to more accurately estimate the CO2 MMP for a wide range of live and heavy crude oils. The newly developed CO2 MMP correlation is originated from CO2 MMP experimental data in addition to database from the worldwide published literature that covers 103 pure CO2 MMP data for various live and dead oil samples. The proposed model is trained by exploiting 80% (82 data points) of the data bank. This correlation is expressed as a function of reservoir temperature, C7+ molecular weight, mole fractions of; non-hydrocarbon components (CO2, H2S and N2), direct correlating components (C1, C2 and C5) and indirect correlating components (C3, C4, C6 and C7). Further, to investigate the authenticity in depth, the proposed correlation is compared with five most commonly used pure CO2 MMP correlations from the literature. A statistical comparison is performed for both training data set (82 data points) as well as testing data set (21 data points). It is found that the proposed CO2 MMP correlation provides the best reproduction of MMP data with a percentage average absolute error of 6.083% and 6.328% for training and testing categories respectively. Finally, the proposed model shows great performance using new set of samples compared with other correlations.

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.

Hydrocarbon and non-hydrocarbon gas injection are among the most effective methods to enhance oil recovery. A key design parameter in any gas injection project is the minimum miscibility pressure (MMP). MMP can be measured in the laboratory with slim tube test, rising bubble apparatus and vanishing-interfacial-tension. Although laboratory measurements are more reliable, their high cost and longer period of time to get a few data sets made them less advantageous. There are numerous analytical, numerical, and empirical approaches devised to determine the MMP through studying thermodynamic behavior of reservoir and injection fluids in a given reservoir condition. Some numerical approaches need additional fluid and rock interaction properties such as relative permeability and capillary pressure. Conceptually, miscibility between injected gas and reservoir oil can occur through three multi-contact mechanisms, namely condensing drive mechanism (CDM), vaporizing drive mechanism (VDM) and both condensing and vaporizing (CV) drive mechanism. Some models such as single-cell algorithm usually give overestimated MMP values since the model is based on the assumption that the drive mechanism is dictated only by CDM or VDM. In most cases, as we will see from the case studies of this research and reported by others as well, miscibility develops through both condensing and vaporizing (CV) driving mechanisms. Multiple mixing cell approach is a very effective way to handle CV drive mechanism. In this study, we modify the algorithm proposed by Ahmadi and Johns (2008), by including additional checking criterion. In spite of increased computational time overhead, our added checking criterion is found to be very useful to crosscheck the validity of the determined MMP, hence improve the reliability.

A Rapid Method for Determining CO2/oil MMP and Visual Observations of CO2/Oil Interactions at Reservoir Conditions

Molecular insight into the miscible mechanism of CO2/C10 in bulk phase and nanoslits

Favorable interactions between injection gas and crude oil are crucial for successful carbon dioxide (CO2) recovery processes. The miscibility behavior and thereby the flooding scheme changes with the pressure applied. Although first contact miscibility (FCM) flooding schemes result in most efficient recovery processes, in many cases multiple contact miscibility (MCM) provides economically viable recovery rates already at lower injection pressure. Thus, the determination of the miscibility pressure is a key step in the lab evaluation for CO2 EOR. Miscibility enhancing additives are able to improve the interactions between CO2 and crude oil leading to reduced miscibility pressure. This paper illustrates an easily applicable procedure to identify the pressure required for full miscibility. Using a pressure resistant sapphire cell the phase behavior of mixtures of different crude oils and CO2 with and without additives was investigated at common reservoir conditions. The effect of the additives on the physical phase behavior of CO2/crude oil mixtures and the benefit that can be achieved by their application will be discussed. The miscibility gaps are determined by measuring the phase behavior of CO2/additive/crude oil mixtures as a function of pressure and temperature. The pressure required for full miscibility (physical minimum miscibility pressure (MMPP)), coming along with an FCM scheme, can easily be detected as the pressure above which the miscibility gap closes and a homogeneous mixture is obtained. Another important point, which was determined in this study, was the critical point of the miscibility gap. Its corresponding pressure is the maximum value of the minimum miscibility pressure (MMP) from a thermodynamical viewpoint, above which MCM schemes take place. Hence, knowledge of the critical point of the mixture is an easy to use method to estimate the maximum value of the MMP for a specific reservoir. Adding proper additives to the CO2 improves the miscibility of injection gas and crude oil. By this the miscibility gap shrinks and both the MMP and the MMPP will be reduced significantly compared to the pure CO2/crude oil system. The method presented is a proper, quick, and low-cost alternative to the time-consuming and expensive slim tube experiments commonly used in the oil industry to measure the MMP. Since at pressures above the MMP an MCM procedure is ensured by physics it is the lowest injection pressure that needs to be applied to ensure miscible CO2 EOR. Reducing the MMP and the MMPP using proper additives can lead to a more economical CO2 flood or can even make reservoirs accessible for this technology, which are naturally not.

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.

A miscibility study was conducted to investigate the effects of the C5+ content in injection gases on Minimum Miscibility Pressure (MMP). Currently available common MMP correlations are based on data from injection gases containing no C5+ fraction. However, laboratory analyses suggest that having a small (and yet relatively significant) C5+ fraction could have a large effect on reducing the MMP to considerably below the predicted values from existing correlations. This paper aims at investigating possible benefits for miscibility and CO2 EOR flooding with impurities, particularly with C5+ fraction. Previously, a PVT and miscibility study was conducted on a Cooper Basin (located in central Australia) reservoir fluid, including solubility-swelling and viscosity studies. Slim tube tests were performed using two injection gases – pure CO2 and a CO2-rich synthetic gas (80mol% CO2), which contained a small amount of C5+ fraction (0.3mol%). The MMP was expected to increase substantially due to the presence of a large amount of methane (15mol%). Correlations from literature predicted the MMP to be above 3433psia, but the MMP was measured to be 2880psia1. As most currently available correlations are based on injection gases with no C5+ fraction, a major contributing source to error with these correlations may have been the C5+ content of the gas. In order to investigate the effects of the C5+ fraction in the injection gas, a series of Rising Bubble Apparatus (RBA) experiments were conducted on the reservoir fluid with three injection gases at three different temperatures to investigate the effect of C5+ in the injection gas stream. Results indicate that the C5+ fraction does have a significant effect on the MMP that needs to be factored into current correlations when the injection gas has a C5+ content.

Nitrogen has been found to be a suitable recovery agent for conventional oil with API gravity larger than 35 that provides the reservoir pressure is above the minimum miscibility pressure and the reservoir oil contains a high concentration of intermediate hydrocarbon components. Nitrogen has been found to achieve dynamic miscibility at high pressures. The miscibility obtained by nitrogen injection in light crude oil reservoir is a conditional miscibility, where the fluids are not miscible on first contact, but form two phases, with one of the fluids absorbing components from the other. After sufficient contacts and exchanges of components, at minimum miscible pressure, the system becomes miscible. The main purpose of this study is to investigate, the effect of temperature, composition of the reservoir fluid and injected gas, on the MMP of nitrogen injection in light oil reservoir by a simulator. The injected gas is pure Nitrogen or a combination of nitrogen with other gas like propane. The effect of varying the percentage of nitrogen and CO2 in the injection gas mixture on MMP has been previously investigated by experiment. Results of the Simulation have shown that the most important factor to achieve miscibility between nitrogen and reservoir oil is the amount of light and intermediate components in the oil. Increasing the intermediate components and decreasing the methane content decrease the MMP. Nitrogen develops miscibility of oil by the same mechanism as methane (vaporizing gas drive). With sufficient amount of methane in oil reservoir, MMP of nitrogen and methane injection is almost the same but decreasing the methane content causes difference. Studies have shown that injecting nitrogen-propane combination will decrease MMP but combining nitrogen with methane does not have significant effects on the MMP. Result show that MMP of nitrogen increases slightly when temperature decreases.

The minimum miscibility pressure (MMP) of crude oil–CO2 systems was determined through analyzing the experimental data of swelling/extraction tests. First, the oil swelling factor (SF) as a result of CO2 dissolution in a crude oil sample was determined at four different temperatures in the range of T=21–40 °C. In addition, three sets of swelling/extraction data of previous studies were collected and included so that more conclusive and satisfactory results can be obtained. The results demonstrated that the oil swelling factor increases with the equilibrium pressure (Peq), reaches the maximum value at light hydrocarbon extraction pressure (Pext), and then reduces with further increase in equilibrium pressure. It was found that the reduction behavior of oil swelling factor occurs in two distinct regions. In the upper extraction phase (UEP), the oil swelling factor decreased sharply at pressures just over extraction pressure and then declined gradually in what is called the lower extraction phase (LEP). Finally, the MMP of the crude oil–CO2 system at a specific temperature was estimated by finding the intersection of the linear regression correlation corresponding to each of the aforementioned regions (i.e., UEP and LEP). The crude oil–CO2 MMP was also determined by employing the vanishing interfacial tension (VIT) technique and a series of CO2 injection tests. Comparing the MMP values of the crude oil–CO2 systems determined by three methods revealed that the MMP values estimated by swelling/extraction data are in approximate agreement with those determined by the two other methods.

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.

Minimum miscibility pressure (MMP) is a key variable for monitoring miscibility between reservoir fluid and injection gas. Experimental and non-experimental methods are used to estimate MMP. Available miscibility correlations attempt to predict the minimum miscibility pressure for a specific type of gas. Here an artificial neural network (ANN) model is applied to a dataset involving 251 data records from around the world in a novel way to estimate the gas-crude oil MMP for a wide range of injected gases and crude oil compositions. This approach is relevant to sequestration projects in which injected gas compositions might vary significantly. The model is correlated with the reservoir temperature, concentrations of volatile (C1 and N2) and intermediate (C2, C3, C4, CO2 and H2S) fractions in the oil (Vol/Inter), C5+ molecular weight fractions in the oil and injected gas specific gravity. A key benefit of the ANN model is that MMP can be determined with reasonable accuracy for a wide range of oil and gas compositions. Statistical comparison of predictions shows that the developed ANN model yields better predictions than empirical-correlation methods. The ANN model predictions achieve a mean absolute percentage error of 13.46%, root mean square error of 3.6 and Pearson's correlation coefficient of 0.95. Sensitivity analysis reveals that injected gas specific gravity and temperature are the most important factors to consider when establishing appropriate miscible injection conditions. Among the available published correlations, the Yellig and Metcalfe correlation demonstrates good prediction performance, but it is not as accurate as the developed ANN model.

SummaryFor many years, miscible gas injection has been the most beneficial enhanced oil recovery method in the oil and gas industry. However, injecting a miscible gas to displace oil often causes the flocculation and deposition of asphaltenes, which subsequently leads to a number of production problems. Nitrogen gas (N2) injection has been used to enhance oil recovery in some oil fields, seeking to improve oil recovery. However, few works have implemented N2 injection and investigated its effect on asphaltene precipitation and deposition. This research investigated the N2 miscible flow mechanism in nanopores and its impact on asphaltene precipitations, which can plug pores and reduce oil recovery. First, a slimtube was used to determine the minimum miscibility pressure (MMP) of N2 to ensure that all of the experiments would be conducted at levels above the MMP. Second, filtration experiments were conducted using nanocomposite filter membranes to study asphaltene deposition on the membranes. A filtration apparatus was designed specifically and built to accommodate the filter membranes. The factors studied include N2 injection pressure, temperature, N2 mixing time, and pore size heterogeneity. Visualization tests were conducted to highlight the asphaltene precipitation process over time. Increasing the N2 injection pressure resulted in an increase in the asphaltene weight percent in all experiments. Decreasing the pore size of the filter membranes increased the asphaltene weight percent. More N2 mixing time also resulted in an increase in asphaltene weight percent, especially early in the process. Visualization tests revealed that after 1 hour, the asphaltene particles were conspicuous, and more asphaltene clusters were found in the test tubes of the oil samples from the filter with the smallest pore size. Chromatography analysis of the produced oil confirmed the reduction in the asphaltene weight percent. Microscopy and scanning electron microscopy (SEM) imaging of the filter membranes indicated significant pore plugging from the asphaltenes, especially for the smaller pore sizes. This research highlights the severity of asphaltene deposition during miscible N2 injection in nanopore structures so as to understand the main factors that may affect the success of miscible N2 injection in unconventional reservoirs.

Experimental study of asphaltene precipitation prediction during gas injection to oil reservoirs by interfacial tension measurement

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.