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

2011 ◽  
Vol 361-363 ◽  
pp. 516-519
Author(s):  
Ju Li ◽  
Xin Wei Liao ◽  
Su Kun
Keyword(s):  
Oil Recovery ◽  
Accurate Determination ◽  
Gas Injection ◽  
Analytical Calculation ◽  
Minimum Miscibility Pressure ◽  
Recovery Techniques ◽  
Miscible Gas Injection ◽  
Tie Lines ◽  
Successful Design ◽  
Complete Set

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.

scholarly journals A New Predictive Method for CO2-Oil Minimum Miscibility Pressure

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Dangke Ge ◽  
Haiying Cheng ◽  
Mingjun Cai ◽  
Yang Zhang ◽  
Peng Dong
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Accurate Determination ◽  
Contact Process ◽  
Gas Injection ◽  
New Model ◽  
Cell Method ◽  
Minimum Miscibility Pressure ◽  
Miscible Gas Injection ◽  
Tie Lines

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%.

Characteristics Curve of Multicontact for CO2 Flood

2013 ◽  
Vol 734-737 ◽  
pp. 1161-1164
Author(s):  
Ju Li ◽  
Chang Lin Liao ◽  
Shi Li
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Accurate Determination ◽  
Gas Injection ◽  
Design And Implementation ◽  
Recovery Techniques ◽  
Miscible Gas Injection ◽  
Successful Design

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.

Minimum Miscibility Pressure of CO2/Hydrocarbon Systems Within Nanopores

2021 ◽  
Author(s):  
Gang Yang ◽  
Xiaoli Li
Keyword(s):  
Oil Recovery ◽  
Gas Injection ◽  
Unconventional Reservoirs ◽  
Minimum Miscibility Pressure ◽  
Theoretical Approaches ◽  
Fluid Systems ◽  
Confined Fluid ◽  
Miscible Gas Injection ◽  
Fluid Characterization ◽  
The Impact

Abstract Minimum miscibility pressure (MMP), as a key parameter for the miscible gas injection enhanced oil recovery (EOR) in unconventional reservoirs, is affected by the dominance of nanoscale pores. The objective of this work is to investigate the impact of nanoscale confinement on MMP of CO2/hydrocarbon systems and to compare the accuracy of different theoretical approaches in calculating MMP of confined fluid systems. A modified PR EOS applicable for confined fluid characterization is applied to perform the EOS simulation of the vanishing interfacial tension (VIT) experiments. The MMP of multiple CO2/hydrocarbon systems at different pore sizes are obtained via the VIT simulations. Meanwhile, the multiple mixing cell (MMC) algorithm coupled with the same modified PR EOS is applied to compute the MMP for the same fluid systems. Comparison of these results to the experimental values recognize that the MMC approach has higher accuracy in determining the MMP of confined fluid systems. Moreover, nanoscale confinement results in the drastic suppression of MMP and the suppression rate increases with decreasing pore size. The drastic suppression of MMP is highly favorable for the miscible gas injection EOR in unconventional reservoirs.

MMP Prediction for CO2 Flood Based on Analytical Calculation

2012 ◽  
Vol 518-523 ◽  
pp. 1387-1390
Author(s):  
Ju Li ◽  
Chang Lin Liao ◽  
Shi Li
Keyword(s):  
Crude Oil ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Analytical Calculation ◽  
Displacement Efficiency ◽  
Local Displacement ◽  
Minimum Miscibility Pressure ◽  
Tie Lines ◽  
Key Parameter

CO2injection processes are among the effective methods for enhanced oil recovery. A key parameter in the design of CO2injection project is the minimum miscibility pressure (MMP), whereas local displacement efficiency from CO2injection is highly dependent on the MMP(Eissa M.2007).This paper predict the CO2–oil MMP(Minimum miscibility pressure)for the pure CO2streams based on analytical calculation. We find the sequence of the component disappearance in calculation of crossover tie lines is a key issue that wills influent the result of MMP prediction. Here we make a correction for the conventional principal. By this method, we predict the MMP of some crude oil samples coming from CHINA. Our predict result is closed to the result measured by slim tube apparatus, the accurate of prediction has been greatly improved.

Improved Method for the Estimation of Minimum Miscibility Pressure for Pure and Impure CO2–Crude Oil Systems Using Gaussian Process Machine Learning Approach

2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Gerald Kelechi Ekechukwu ◽  
Olugbenga Falode ◽  
Oyinkepreye David Orodu
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Oil Recovery ◽  
Superior Performance ◽  
Critical Parameters ◽  
Co2 Injection ◽  
Minimum Miscibility Pressure ◽  
Miscible Gas Injection ◽  
Successful Design ◽  
Intelligent Models

Abstract The minimum miscibility pressure (MMP) is one of the critical parameters needed in the successful design of a miscible gas injection for enhanced oil recovery purposes. In this study, we explore the capability of using the Gaussian process machine learning (GPML) approach, for accurate prediction of this vital property in both pure and impure CO2-injection streams. We first performed a sensitivity analysis of different kernels and then a comparative analysis with other techniques. The new GPML model, when compared with previously published predictive models, including both correlations and other machine learning (ML)/intelligent models, showed superior performance with the highest correlation coefficient and the lowest error metrics.

Applicability of Enhanced Oil Recovery techniques on mature fields - Interest of gas injection

2005 ◽  
Author(s):  
Frederic Maubeuge ◽  
Danielle Christine Morel ◽  
Jean-Pierre Charles Fossey ◽  
Said Hunedi ◽  
Jacques Albert Danquigny
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Gas Injection ◽  
Recovery Techniques

scholarly journals Minimum miscibility pressure computation in eor by flare gas flooding

2018 ◽  
Vol 10 (2) ◽  
pp. 61
Author(s):  
Tjokorde Walmiki Samadhi ◽  
Utjok W.R. Siagian ◽  
Angga P Budiono
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Gas Injection ◽  
Molar Ratio ◽  
Co2 Injection ◽  
Co2 Flooding ◽  
Minimum Miscibility Pressure ◽  
Gas Flooding ◽  
Model Oil ◽  
Gas Drive

The technical feasibility of using flare gas in the miscible gas flooding enhanced oil recovery (MGF-EOR) is evaluated by comparing the minimum miscibility pressure (MMP) obtained using flare gas to the MMP obtained in the conventional CO2 flooding. The MMP is estimated by the multiple mixing cell calculation method with the Peng-Robinson equation of state using a binary nC5H12-nC16H34 mixture at a 43%:57% molar ratio as a model oil. At a temperature of 323.15 K, the MMP in CO2 injection is estimated at 9.78 MPa. The MMP obtained when a flare gas consisting of CH4 and C2H6 at a molar ratio of 91%:9% is used as the injection gas is predicted to be 3.66 times higher than the CO2 injection case. The complete gas-oil miscibility in CO2 injection occurs via the vaporizing gas drive mechanism, while flare gas injection shifts the miscibility development mechanism to the combined vaporizing / condensing gas drive. Impact of variations in the composition of the flare gas on MMP needs to be further explored to confirm the feasibility of flare gas injection in MGF-EOR processes. Keywords: flare gas, MMP, miscible gas flooding, EORAbstrakKonsep penggunaan flare gas untuk proses enhanced oil recovery dengan injeksi gas terlarut (miscible gas flooding enhanced oil recovery atau MGF-EOR) digagaskan untuk mengurangi emisi gas rumah kaca dari fasilitas produksi migas, dengan sekaligus meningkatkan produksi minyak. Kelayakan teknis injeksi flare gas dievaluasi dengan memperbandingkan tekanan pelarutan minimum (minimum miscibility pressure atau MMP) untuk injeksi flare gas dengan MMP pada proses MGF-EOR konvensional menggunakan injeksi CO2. MMP diperkirakan melalui komputasi dengan metode sel pencampur majemuk dengan persamaan keadaan Peng-Robinson, pada campuran biner nC5H12-nC16H34 dengan nisbah molar 43%:57% sebagai model minyak. Pada temperatur 323.15 K, estimasi MMP yang diperoleh dengan injeksi CO2 adalah 9.78 MPa. Nilai MMP yang diperkirakan pada injeksi flare gas yang berupa campuran CH4-C2H6 pada nisbah molar 91%:9% sangat tinggi, yakni sebesar 3.66 kali nilai yang diperoleh pada kasus injeksi CO2. Pelarutan sempurna gas-minyak dalam injeksi CO2 terbentuk melalui mekanisme dorongan gas menguap (vaporizing gas drive), sementara pelarutan pada injeksi flare gas terbentuk melaui mekanisme kombinasi dorongan gas menguap dan mengembun (vaporizing/condensing gas drive). Pengaruh variasi komposisi flare gas terhadap MMP perlu dikaji lebih lanjut untuk menjajaki kelayakan injeksi flare gas dalam proses MGF-EOR.Kata kunci: flare gas, MMP, miscible gas flooding, EOR

Modified Method of Characteristics for Generating EOR Oil Recovery Curves

2021 ◽  
Author(s):  
Christian Agger ◽  
Henrik Sørensen
Keyword(s):  
Oil Recovery ◽  
Method Of Characteristics ◽  
Gas Injection ◽  
Oil Reservoir ◽  
Simulation Algorithm ◽  
Recovery Curves ◽  
Minimum Miscibility Pressure ◽  
Modified Method ◽  
Percent Recovery ◽  
Modified Method Of Characteristics

Abstract The paper describes a fast and approximate 1D simulation algorithm for calculating the percent recovery that can be obtained from an oil reservoir if gas injection is carried out at a pressure lower than the minimum miscibility pressure. The algorithm is based on the Method of Characteristics. While a conventional 1D reservoir simulation of a gas injection scenario may take minutes or even hours, the proposed algorithm allows a full evaluation of the recovery to be completed within seconds. To make the method numerically robust, a number of approximations were needed. The result is an extremely fast algorithm that not only provides a good estimate of the recovery obtained by gas injection, but also gives a good visualization of how the gas displaces the oil.

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