Determination of minimum miscibility pressure in N2–crude oil system: A robust compositional model

Nitrogen has been valued as an economical alternative injection gas for gas-based enhanced oil recovery (EOR) processes. Minimum miscibility pressure (MMP) is the most important parameter to successfully design N2 flooding. In this communication, a data bank covering wide ranges of thermodynamic and compositional conditions was gathered from open literature. Afterward, a rigorous approach, namely least square support vector machine (LSSVM) optimized with coupled simulated annealing (CSA) was proposed to develop a reliable and robust model for the prediction of MMP of pure/impure N2–crude oil. The results of this study showed that the proposed model is more reliable and accurate than the pre-existing models in a wider range of thermodynamic and process conditions. The proposed model predicts the total dataset (84 MMP data points of pure N2, nitrogen mixture streams and lean gases) with an average absolute relative error of 5.17%. Finally, by employing the relevancy factor, it was found that the intermediate components of crude oil have the most significant impact on the nitrogen MMP estimation and Leverage approach shows that only two data points (2.4%) are outside the applicability domain of the model proving the reliability of the developed model.

[1]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machines , 2002 .

[2]  Colin R. Goodall,et al.  13 Computation using the QR decomposition , 1993, Computational Statistics.

[3]  J. Hanssen.  Nitrogen as a Low-Cost Replacement for Natural Gas Reinjection Offshore , 1988 .

[4]  Farhad Gharagheizi,et al.  Robust Model for the Determination of Wax Deposition in Oil Systems , 2013 .

[5]  Abdolhossein Hemmati-Sarapardeh,et al.  Toward a predictive model for estimating viscosity of ternary mixtures containing ionic liquids , 2014 .

[6]  Abdolhossein Hemmati-Sarapardeh,et al.  On determination of natural gas density: Least square support vector machine modeling approach , 2015 .

[7]  S. Ayatollahi,et al.  Experimental Determination of Equilibrium Interfacial Tension for Nitrogen-Crude Oil during the Gas Injection Process: The Role of Temperature, Pressure, and Composition , 2014 .

[8]  S. Shedid,et al.  Investigation of supercritical carbon dioxide, aspheltenic crude oil, and formation brine interactions in carbonate formations , 2009 .

[9]  Ali Eslamimanesh,et al.  Phase equilibrium modeling of clathrate hydrates of methane, carbon dioxide, nitrogen, and hydrogen + water soluble organic promoters using Support Vector Machine algorithm , 2012 .

[10]  Kaiyun Fu,et al.  The genetic algorithm based back propagation neural network for MMP prediction in CO2-EOR process , 2014 .

[11]  Miriam Lev-On,et al.  Reducing Carbon Dioxide Emissions with Enhanced Oil Recovery Projects: A Life Cycle Assessment Approach , 2001 .

[12]  F. Stalkup.  Displacement Behavior of the Condensing/Vaporizing Gas Drive Process , 1987 .

[13]  D. Rao,et al.  Comparative Evaluation of a New MMP Determination Technique , 2006 .

[14]  R. Hwang,et al.  Mitigation of asphaltics deposition during CO 2 flood by enhancing CO 2 solvency with chemical modifiers , 2000 .

[15]  O. Glaso.  Miscible displacement : recovery tests with nitrogen , 1990 .

[16]  S. Ayatollahi,et al.  A rigorous approach to predict nitrogen-crude oil minimum miscibility pressure of pure and nitrogen mixtures , 2015 .

[17]  F. Chung,et al.  Nitrogen miscible displacement of light crude oil : a laboratory study , 1990 .

[18]  S. Ayatollahi,et al.  Toward mechanistic understanding of heavy crude oil/brine interfacial tension: The roles of salinity, temperature and pressure , 2014 .

[19]  Peter J. Rousseeuw,et al.  Robust regression and outlier detection , 1987 .

[20]  Vladimir Alvarado,et al.  Enhanced Oil Recovery: An Update Review , 2010 .

[21]  A. Fazlali,et al.  Computational procedure for determination of minimum miscibility pressure of reservoir oil , 2013 .

[22]  Moudi Fahad Al-Ajmi,et al.  Planning Miscibility Tests And Gas Injection Projects For Four Major Kuwaiti Reservoirs , 2009 .

[23]  R. Johns,et al.  Effect of Dispersion on Local Displacement Efficiency for Multicomponent Enriched-Gas Floods Above the Minimum Miscibility Enrichment , 2002 .

[24]  S. S. Kuo.  Prediction of Miscibility for the Enriched-Gas Drive Process , 1985 .

[25]  Abdolhossein Hemmati-Sarapardeh,et al.  A rigorous approach for determining interfacial tension and minimum miscibility pressure in paraffin-CO2 systems: Application to gas injection processes , 2016 .

[26]  Shahin Kord,et al.  Asphaltene Deposition during CO2 Injection and Pressure Depletion: A Visual Study , 2012 .

[27]  Jean-Noël Jaubert,et al.  A crude oil data bank containing more than 5000 PVT and gas injection data , 2002 .

[28]  F. Orr,et al.  Component Partitioning in CO2/Crude Oil Systems: Effects of Oil Composition on CO2 Displacement Performance , 1994 .

[29]  Brij B. Maini,et al.  Evaluation of CO2 Based Vapex Process for the Recovery of Bitumen from Tar Sand Reservoirs , 2003 .

[30]  H. Belhaj,et al.  Miscible oil recovery utilizing N2 and/or HC gases in CO2 injection , 2013 .

[31]  Babak Aminshahidy,et al.  A soft computing approach for the determination of crude oil viscosity: Light and intermediate crude oil systems , 2016 .

[32]  Alexander J. Smola,et al.  Support Vector Method for Function Approximation, Regression Estimation and Signal Processing , 1996, NIPS.

[33]  Hadil Abu Khalifeh,et al.  Potential of Nitrogen Gas Miscible Injection in South East Assets, Abu Dhabi , 2013 .

[34]  K. Aziz,et al.  Analysis and correlation of nitrogen and lean gas miscibility pressure , 1985 .

[35]  Amir H. Mohammadi,et al.  Toward prediction of petroleum reservoir fluids properties: A rigorous model for estimation of solution gas-oil ratio , 2016 .

[36]  Amir H. Mohammadi,et al.  Effect of operational parameters on SAGD performance in a dip heterogeneous fractured reservoir , 2014 .

[37]  Johan A. K. Suykens,et al.  Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.

[38]  Johan A. K. Suykens,et al.  Intelligence and Cooperative Search by Coupled Local Minimizers , 2002, Int. J. Bifurc. Chaos.

[39]  H. Sebastian,et al.  Nitrogen Minimum Miscibility Pressures , 1992 .

[40]  S. Thomas,et al.  The Promise And Problems of Enhanced Oil Recovery Methods , 1996 .