Miscible Gas Injection Processes Research Articles

Physical-informed deep learning framework for CO[formula omitted]-injected EOR compositional simulation

CO2 injection for enhanced oil recovery (CO2-EOR) is one of the industry’s most widely applied techniques for CO2 utilization. People use the compositional simulation technique to clearly describe CO2 injection processes for EOR, which is always computational-expensive. The main objective of this study is to utilize deep learning (DL) techniques to describe phase behaviors and accelerate compositional simulations. First, we constructed a new DL-based compositional simulation framework. Instead of solving equations of state for every grid cell, this framework can aggregate millions of phase behavior solvers and determine all mixtures’ phase status in one single round of calculation. This trait can significantly improve the efficiency of solving numerical equations. Next, we illustrated how to develop DL-based phase behavior models to determine phase status accurately. Our newly proposed single-phase identification model can resolve the difficulty in inaccurate single-phase labeling within compositional simulations, greatly benefiting the numerical convergence of simulation. Finally, we tested abundant complicated cases covering near-miscible and miscible gas injection processes and demonstrated the new DL-based method’s strength in accelerating the compositional simulation. Besides, we also presented the DL-based method’s more substantial power in numerical convergences that it could succeed in cases where the standard simulation method fails. This work can contribute to more efficiently and effectively describing complex fluid displacement processes, benefiting CO2 injection EOR and other utilizations like CO2 sequestrations.

To optimize well pattern during miscible gas injection process via heuristic techniques

To detect optimum well locations for new injection wells one must generally notice to existing well locations, reservoir shape, capital cost per well construction in each area as well as recovery increase relevant to new well layout. Designing injection process presents inverse optimization issue whereas adjusting exploitation wells prior to primary recovery exhibits classic optimization problem. Most important design factor namely injection well layout has no unique explicit solution to solve via analytical or numerical techniques thus one can propose meta or hyper heuristic approaches to solve such problems. Our main novelty in this work is that here we cooperate four heuristic optimization approaches with our self made fast simulation technique to optimize well locations for two exemplar miscible gas injection processes. We employ MATLAB software to construct artificial porous media prototypes with different uncertainties to investigate optimization technique performances in low rather than high risk media. Outcomes illustrate that approaches like artificial immune system or particle swarm optimization which exhibit strong local search can effectively detect optimal well locations in high risk porous media. Results also show that solution techniques such as Monte Carlo that have strong global search capabilities at expense of weak local search can discover optimum well locations only in media with low uncertainty.

A New Predictive Method for CO2-Oil Minimum Miscibility Pressure

Gas injection processes are among the effective methods for enhanced oil recovery. Miscible and/or near miscible gas injection processes are among the most widely used enhanced oil recovery techniques. The successful design and implementation of a miscible gas injection project are dependent upon the accurate determination of minimum miscibility pressure (MMP), the pressure above which the displacement process becomes multiple-contact miscible. This paper presents a method to get the characteristic curve of multiple-contact. The curve can illustrate the character in the miscible and/or near miscible gas injection processes. Based on the curve, we suggest a new model to make an accurate prediction for CO2-oil MMP. Unlike the method of characteristic (MOC) theory and the mixing-cell method, which have to find the key tie lines, our method removes the need to locate the key tie lines that in many cases is hard to find a unique set. Moreover, unlike the traditional correlation, our method considers the influence of multiple-contact. The new model combines the multiple-contact process with the main factors (reservoir temperature, oil composition) affecting CO2-oil MMP. This makes it is more practical than the MOC and mixing-cell method, and more accurate than traditional correlation. The method proposed in this paper is used to predict CO2-oil MMP of 5 samples of crude oil in China. The samples come from different oil fields, and the injected gas is pure CO2. The prediction results show that, compared with the slim-tube experiment method, the prediction error of this method for CO2-oil MMP is within 2%.

Determination of Minimum Miscibility Pressure (MMP) using PVTi Software, Eclipse 300 and Empirical Correlations

One of the most important factors through the miscible gas injection process is to determine the Minimum Miscibility Pressure. According to the definition, the minimum miscibility pressure is the minimum pressure at which, at a constant temperature, the oil and gas injected can dissolve together to form a single phase. This pressure is typically abbreviated as MMP. Among the available methods for determining the minimum miscibility pressure, laboratory methods including slim tube test and ascending bubble apparatus test are more widely utilized. Although the mentioned tests have high measurement accuracy, they are very time consuming and expensive. Therefore, the determination of the minimum miscibility pressure is usually done using computational and simulation approaches that also have high accuracy. Conducting PVT tests and determining their MMP using slim tube method was previously performed. In this study, the minimum miscibility pressure of reservoirs was determined by applying three methods of simulation with PVTi software, simulation with Eclipse 300 software and using Empirical Correlations. By comparing the obtained results and the laboratory results, it was revealed that the simulation by Eclipse 300 is regarded as the fastest and most accurate approach.

Prediction of CO2‐Oil Minimum Miscibility Pressure Using Soft Computing Methods

AbstractSearching for computational approaches for determination of the minimum miscibility pressure (MMP) is highly requested during the miscible gas injection process. New models, namely, the stochastic gradient boosting (SGB) algorithm and two distinct hybrid artificial neural network (ANN) models were used to predict CO2 MMP as a function of reservoir temperature, mole percent of volatile oil components, mole percent of intermediate oil components, molecular weight of pentane‐plus fraction in the oil phase, mole percentage of CO2 in injected gas, volatile components, and intermediate components in the injected gas based on 144 published data points. The SGB model was found to provide the better performance. The reservoir temperature turned out to be the most important factor.

Enhanced Method-of-Characteristics Approach for Determination of Minimum Miscibility Pressure in Displacements with Bifurcated Phase Behavior

Determination of minimum miscibility pressure (MMP) is an imperative component of optimally designing miscible gas injection processes. Semianalytical method of characteristics (MOC) is superior to...

Effects of oligomers dissolved in CO2 or associated gas on IFT and miscibility pressure with a gas-light crude oil system

The solubility of an oligomer in a supercritical gas solvent (e.g. CO2 or associated gas (AG) mixture) and the subsequent effects on the phase behaviour, interfacial tension (IFT) and miscibility pressure of the in-situ oil/oligomer-thickened gas system at a molecular level are crucial to understanding and designing a thickened miscible gas injection (MGI) process. We have conducted cloud point pressure measurements, which revealed that the phase behaviour of P-1-D-thickened CO2 would follow a UCST (upper critical solution temperature) trend while P-1-D-thickened AG mixture would lie close to a LCST (lower critical solution temperature) behaviour. Moreover, our measured equilibrium IFTs of crude oil/P-1-D-thickened CO2 system and crude oil/PVEE-thickened CO2 system were found to be slightly lower than those of the crude oil/CO2 system. This results in a slight reduction in the MMP (minimum miscibility pressure) and considerable reduction in the first contact miscibility pressure (Pmax). We found the dissolution of P-1-D in the AG mixture to cause an increase in the equilibrium IFT for the crude oil/P-1-D-thickened AG mixture system, resulting in an increase in both of the MMP and Pmax. This indicates that the dissolution of an oligomer may have a considerable effect on the crude oil/thickened gas IFT behaviour at a pressure close to the cloud point pressure.

Application of Streamline Simulation to Gas Displacement Processes

Performance evaluation of miscible and near-miscible gas injection processes is available through conventional finite difference (FD) compositional simulation. Streamline methods have also been developed in which fluid is transported along the streamlines instead of using the finite difference grid. In streamline-based simulation, a 3D flow problem is decoupled into a set of 1D problems solved along streamlines. This reduces simulation time relative to FD simulation, and suppresses the numerical dispersion errors that are present in FD simulations. Larger time steps and higher spatial resolution can be achieved in these simulations. Thus, streamline-based reservoir simulation can be orders of magnitude faster than the conventional finite difference methods. Streamline methods are traditionally only applied to incompressible flow processes. In this paper, the method is adopted and assessed for application to compressible flow processes. A detailed comparison is given between the results of conventional FD simulation and the streamline approach for gas displacement processes. Finally, some guidelines are given on how the streamline method can potentially be used to good effect for gas displacement processes.

Performance of multiple thermal fluids assisted gravity drainage process in post SAGD reservoirs

Multiple thermal fluids injection process is a new heat-carrier process proposed in recent years as an EOR process for heavy oil reservoirs. Compared with the conventional saturated-steam injection process, it combines the multiple advantages of immiscible and/or miscible gas injection and thermal recovery processes. In this paper, based on the ideas of the multiple thermal fluids injection process and the conventional steam assisted gravity drainage (SAGD) process, a new recovery process, multiple thermal fluids assisted gravity drainage (MFAGD) process is proposed to enhance heavy oil recovery for post SAGD reservoirs. Two 3D gravity drainage experiments (SAGD and SAGD-MFAGD) are first conducted to explore EOR mechanisms of the multiple thermal fluids in heavy oil reservoirs. Subsequently, numerical simulations are performed to match the experimental measurements. Then the EOR mechanisms and the remaining oil saturation distribution are analyzed. Furthermore, the differences between the SAGD, steam-and-gas-push (SAGP) and MFAGD processes are discussed. From a dimensionless scaling analysis for gravity drainage process, lab scale parameters are converted to field scale ones, and a field scale simulation model is developed. Through the analysis and simulation, the reservoir adaptability of the MFAGD process is investigated, and its operation parameters are numerically optimized. Experimental results indicate that a strategic combination of the SAGD and MFAGD processes can tremendously improve the development of heavy oil reservoirs. The MFAGD process can be adopted as a follow-up recovery technique after the SAGD process for heavy oil reservoirs. As its EOR mechanisms, in addition to the conventional thermal recovery mechanisms of steam injection, the results show that heat insulation, energy recovery, gas dissolution, foamy oil and auxiliary well cleanup are all its important mechanisms. In comparison with SAGD, this new process has a higher recovery rate, a lower steam injecting volume and a lower cumulative steam-oil ratio (cSOR). Numerical results also show that the steam chamber from MFAGD is shaped like a liquid drop instead of a conventional inverted triangle from SAGD. The net-to-gross value and formation thickness have a great influence on the performance of MFAGD. It is found that for MFAGD, the optimal steam-gas ratio in the standard conditions is 1:1, the steam injection rate is 200m3/d, and the operation pressure is 3.0MPa for the study reservoir. The MFAGD process will be a potentially important EOR method for post SAGD heavy oil and oil sands reservoirs.

Uniqueness, repeatability analysis and comparative evaluation of experimentally determined MMPs

Miscible gas injection processes like CO2 flooding are recommended to be carried out at minimum miscibility pressure (MMP) for effective enhanced recovery of trapped oil. There are several methods for MMP determination, but slim tube and vanishing interfacial tension (VIT) are deployed experimental techniques in this study. Uniqueness and repeatability of slim tube determined MMP was tested by conducting 55 slim tube runs for three different Omani crude oil samples (L-721, MZE and N) using three different coil lengths of constant diameter and three different injection rates. VIT technique accuracy and reliability was evaluated by comparing VIT determined MMPs, for same three considered crude oil samples, with aforementioned different slim tube systems determined MMPs. A trend of decrease in MMP with increase in coil length was found. No unique trend was found between MMP and injection rate. Lowest MMP and highest recovery were observed with highest coil length and lowest injection rate. It may be attributed to more stable displacement process which results in earlier developed miscibility and almost complete displacement of remaining more coil length retained oil. Therefore, both slim tube design and procedure need to be standardized. PVT software predicted MMP close to lower coil length slim tube system determined MMP for sample L-721 and higher coil length measured MMP for sample MZE. VIT approach determined MMPs were found to lie in between the MMPs measured by slim tube system with medium and longer coil lengths for same three oil samples. Since VIT estimated MMPs are in close match with more liable slim tube design determined MMPs, this technique can be utilized as a reliable and cheap alternative compared to more expensive and time consuming slim tube technique for accurate MMP determination without any potential of significant error.

Integrating support vector regression with genetic algorithm for CO2-oil minimum miscibility pressure (MMP) in pure and impure CO2 streams

Accurate knowledge of the minimum miscibility pressure (MMP) is essential in successful design of any miscible gas injection process, particularly in CO2 flooding. It is however well-acknowledged that experimental measurements are expensive, time-consuming, and cumbersome. As a direct consequence, a support vector regression model combined with genetic algorithm (GA-SVR) was proposed to predict pure and impure CO2-crude oil MMP. The accuracy and reliability of the proposed model were evaluated through 150 data sets collected in the open literature and compared with approaches commonly used to estimate the MMP (Lee correlation, Shokir correlation, Orr-Jensen correlation, Yellig-Metcalfe correlation, Alston correlation, Emera-Sarma correlation, Cronquist correlation, Kamari et al. correlation, and Fathinasab-Ayatollahi correlation). The results showed that the proposed model for predicting the MMP is in excellent agreement with experimental data and outperforms all the existing methods considered in this work in prediction of pure and impure CO2-oil MMP. Furthermore, outlier diagnosis was performed on the whole data sets to identify the applicable range of all models investigated in this work by detecting the probable doubtful MMP data.

On the determination of CO2–crude oil minimum miscibility pressure using genetic programming combined with constrained multivariable search methods

In addition to reducing carbon dioxide (CO2) emission, the high oil recovery efficiency achieved by CO2 injection processes makes CO2 injection a desirable enhance oil recovery (EOR) technique. Minimum miscibility pressure (MMP) is an important parameter in successful designation of any miscible gas injection process such as CO2 flooding; therefore, its accurate determination is of great importance. The current experimental techniques for determining MMP are expensive and time-consuming. In this study, multi-gene genetic programming has been combined with constrained multivariable search methods, and a simple empirical model has been developed which provides a reliable estimation of MMP in a wide range of reservoirs, injection gases and crude oil systems. The experimental data for developing the proposed correlation consists of 270 data points from twenty-six authenticated literature sources. This model utilizes reservoir temperature, molecular weight of C5+, volatile (N2 and C1) to intermediate (H2S, CO2, C2, C3, C4) ratio and pseudo critical temperature of the injection gas as input parameters. Both statistical and graphical error analyses have been employed to evaluate the accuracy and validity of the proposed model compared to the pre-existing correlations. The results showed that the new model provides an average absolute relative error of 11.76%. Moreover, the relevancy factor indicated that the reservoir temperature has the greatest impact on the minimum miscibility pressure.

Technical and economic feasibility study of flue gas injection in an Iranian oil field

Nowadays, the non-hydrocarbon gases are the main sources for gas injection projects in different countries. The main advantages of the flue gas injection are low cost, readily available sources (which consists mainly of N2 and CO2) and low compressibility in comparison with other gases like CO2 or CH4 (for a given volume at the same conditions). In addition, it occupies more space in the reservoir and it is an appropriate way for CO2 sequestering and consequently reducing greenhouse gases. In the aforementioned method, N2 and/or CO2 is injected into the oil reservoir for miscible and/or immiscible displacement of remaining oil. Moreover, a key parameter in the designing of a gas injection project is the minimum miscibility pressure (MMP) which is commonly calculated by running simulation case or implementing conventional correlations. From technical viewpoints, the lower MMP values are more flavor for miscible gas injection process due to lower injection pressure and consequently lower maintenance and lower injection costs. The main aim of this research is to investigate various gas injection methods (N2, CO2, produced reservoir gas, and flue gas) in one of the northern Persian gulf oil fields by a numerical simulation method. Moreover, for each scenario of gas injection technical and economical considerations are took into account. Finally, an economic analysis is implemented to compare the net present value (NPV) of the different gas injection scenarios in the aforementioned oil field.

Determination of Gas-oil Interfacial Tension

Reliable knowledge of minimum miscibility pressure plays a vital parameter in the design and implementation of any miscible gas injection process and gas-oil interfacial tension extremely impacts on minimum miscibility pressure values. In this article two Iranian oil fields were investigated. Gas-oil interfacial tension technique relies on the measurements of gas/oil interfacial tension by pendant drop at several pressures and reservoir temperature for the first field and results were compared with generated values by the Parachor method. Then at different pressures and constant temperature (115°F) condition in the second field interfacial tension values have been evaluated for different oil-gas molar ratios.

Experimental investigation of miscible gas injection with different gases in petroleum reservoirs

Miscible gas injection processes are among the effective methods for enhanced oil recovery. Aiming at three different types of light oil reservoir, we study the feasibility of miscible gas flooding of light oil reservoirs using the method of physical simulation. Several slimtube displacement experiments with different injected gases are carried out at the various pressure levels. These injected gases include carbon dioxide, hydrocarbon gas and flue gas. Thus, the minimum miscibility pressures of gas-oil system are studied, and the influence of oil components, injected gas, and reservoir properties on MMP are also discussed. Thereafter, we do a survey on the multiple-parameter correlations of CO2-oil MMP prediction. Then, two models are selected to correct for accurately predicting the CO2-oil MMP in this reservoir. This study could be used as a tool for the successful design of miscible gas injection project to enhance crude oil recovery in light oil reservoirs. [Received: February 23, 2013; Accepted: June 6, 2013]

Comparison of oil removal in surfactant alternating gas with water alternating gas, water flooding and gas flooding in secondary oil recovery process.

Growing oil prices coupled with large amounts of residual oil after operating common enhanced oil recovery methods has made using methods with higher operational cost economically feasible.Nitrogen is one of the gases used in both miscible and immiscible gas injection process in oil reservoir. In heterogeneous formations gas tends to breakthrough early in production wells due to overriding, fingering and channeling. Surfactant alternating gas (SAG) injection is one of the methods commonly used to decrease this problem. Foam which is formed on the contact of nitrogen and surfactant increases viscosity of injected gas. This increases the oil–gas contact and sweep efficiency, although adsorption of surfactant on rock surface can causes difficulties and increases costs of process. Many parameters must be considered in design of SAG process. One of the most important parameters is SAG ratio that should be in optimum value to improve the flooding efficiency.In this study, initially the concentration of surfactant was optimized due to minimization of adsorption on rock surface which results in lower cost of surfactant. So, different sodium dodecyl sulfate (SDS) concentrations of 100, 500, 1000, 2000, 3000 and 4000 ppm were used to obtain the optimum concentration at 70 °C and 144.74×105 Pa. A simple, clean and relatively fast spectrophotometric method was used for determination of surfactant which is based on the formation of an ion-pair. Then the effect of surfactant to gas volume ratio on oil recovery in secondary oil recovery process during execution of immiscible surfactant alternating gas injection was examined experimentally. The experiments were performed with sand pack under certain temperature, pressure and constant rate. Experiments were performed with surfactant to gas ratio of 1:1, 1:2, 1:3, 2:1 and 3:1 and 1.2 pore volume injected. Then, comparisons were made between obtained results (SAG) with water flooding, gas flooding and water alternating gas (WAG) processes.This study shows that using the concentration of 1500 ppm of surfactant solution is practical and economical. Results also show that the SAG ratio of 1:1 with 0.2 cm3/min at temperature and pressure of 70 °C and 144.74×105 Pa, has the maximum oil removal efficiency. In this SAG ratio, stable foam was formed and viscous fingering delayed in comparison to other ratios. Finally, the results demonstrated that SAG injection has higher oil recovery in comparison to other displacement methods (water flooding, gas flooding and WAG).

Characteristics Curve of Multicontact for CO<sub>2</sub> Flood

Miscible and/or near miscible CO2 flood are among the most widely used enhanced oil recovery techniques. The successful design and implementation of a miscible gas injection project is dependent upon the accurate determination of MMP[1]-[9], the pressure above which the displacement process becomes multicontact miscible. This paper presents a method to get the characteristics curve of multicontact. The curve can illustrate the character in the Miscible and/or near miscible gas injection processes, based the curve, From the change of characteristics curve of multicontact ,we can known the type of the displacement, and the influence of injection gas to the MMP.

Investigation of asphaltene precipitation in miscible gas injection processes: experimental study and modeling

Asphaltene precipitation during natural depletion and miscible gas injection is a common problem in oilfields throughout the world. In this work, static precipitation tests are conducted to investigate the effects of pressure, temperature and gas type and concentration on asphaltene instability. Three different oil samples have been studied under reservoir conditions with/without nitrogen and methane injection. Besides applying common thermodynamic models, a new scaling equation is presented to predict asphaltene precipitation under HPHT gas injection. Extensive published data from the literature are also used in model development. The scaling approach is attractive because it is simple and complex asphaltene properties are not involved in the calculations. Moreover, the proposed model provides universal parameters for different fluid samples over a wide range of pressure and temperature that makes it novel for evaluation of future gas injection projects when simple PVT data are available.

The Lessons Learned From Miscible Gas Flooding in Naturally Fractured Reservoirs: Integrated Studies, and Pilot and Field Cases

Suitable methods have to be employed for secondary and tertiary oil recovery from the naturally fractured reservoirs (NFRs). The miscible gas injection has shown some promising results for enhancing oil recovery from NFRs. However, proper design of the field-scale miscible gas injection projects in NFRs is still a major challenge. The authors evaluate the technical issues of the miscible gas injection in NFRs. The classification of NFRs and their production characteristics, the mechanisms of oil production in NFRs, and significant findings of integrated studies, pilot and field trials, and commercial field projects of the miscible gas injection in NFRs are reviewed. Finally, important issues are identified, which need detailed investigations for the design and performance assessment of the field projects. It is hoped that this paper will serve as a helpful reference for the engineers interested in miscible gas injection process in NFRs.

Key Problems in the Calculation of Minimum Miscibility Pressure Based on Analytical Method

Miscible and/or near miscible gas injection processes are among the most widely used enhanced oil recovery techniques. The successful design and implementation of a miscible gas injection project is dependent upon the accurate determination of minimum miscible pressure (MMP), the pressure above which the displacement process becomes multi-contact miscible. Analytical methods, which are inexpensive and quick to use, have been developed to estimate MMP for complex fluid characterizations. However, many problems still existed in the analytical calculation, which will lead to the failure of calculation, or wrong result. This paper shows how the initial tie line could be calculated when the component of injection gas doesn’t included in the crude oil. And moreover, how to get a complete set of initial value for the equations of crossover tie lines, and the influence of EOS for the result of key tie lines is analyzed simultaneously.