Open Access

This article has an erratum: []

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 74, 2019
Article Number 30
Number of page(s) 11
Published online 21 March 2019
  • Lu J., Liyanage P.J., Solairaj S., Adkins S., Arachchilage G.P., Kim D.H., Britton C., Weerasooriya U., Pope G.A. (2014) New surfactant developments for chemical enhanced oil recovery, J. Pet. Sci. Eng. 120, 94–101. doi: 10.1016/j.petrol.2014.05.021. [Google Scholar]
  • Creton B., Nieto-Draghi C., Pannacci N. (2012) Prediction of surfactants’ properties using multiscale molecular modeling tools: A review, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 67, 6, 969–982. doi: 10.2516/ogst/2012040. [CrossRef] [Google Scholar]
  • Salager J.-L., Forgiarini A.M., Bullón J. (2013) How to attain ultralow interfacial tension and three-phase behavior with surfactant formulation for enhanced oil recovery: A review. Part 1. Optimum formulation for simple surfactant–oil–water ternary systems, J. Surfactants Deterg. 16, 4, 449–472. doi: 10.1007/s11743-013-1470-4. [Google Scholar]
  • Budhathoki M., Hsu T.-P., Lohateeraparp P., Roberts B.L., Shiau B.J., Harwell J.H. (2016) Design of an optimal middle phase microemulsion for ultra high saline brine using Hydrophilic Lipophilic Deviation (HLD) method, Colloids Surf. A: Physicochem. Eng. Aspects 488, 36–45. doi: 10.1016/j.colsurfa.2015.09.066. [CrossRef] [Google Scholar]
  • Salager J.L., Morgan J.C., Schechter R.S., Wade W.H., Vasquez E. (1979) Optimum formulation of surfactant/water/oil systems for minimum interfacial tension or phase behavior, Soc. Pet. Eng. J. 19, 2, 107–115. doi: 10.2118/7054-PA. [Google Scholar]
  • Acosta E.J., Yuan J.Sh., Bhakta A.Sh. (2008) The characteristic curvature of ionic surfactants, J. Surf. Deterg. 11, 2, 145–158. doi: 10.1007/s11743-008-1065-7. [CrossRef] [Google Scholar]
  • Marliere C., Creton B., Oukhemanou F., Wartenberg N., Courtaud T., Féjean C., Betoulle S., Defiolle D., Mougin P. (2016) Impact of live crude oil composition on optimal salinity of a surfactant formulation, Paper SPE 179792-MS presented at the SPE EOR Conference at Oil and Gas West Asia, 21–23 March, Muscat, Oman, (179792-MS). doi: 10.2118/179792-MS. [Google Scholar]
  • Oukhemanou F., Courtaud T., Morvan M., Moreau P., Mougin P., Fejean C., Pedel N., Bazin B., Tabary R. (2014) Alkaline surfactant-polymer formulation evaluation in live oil conditions: The impact of temperature, pressure and gas on oil recovery performance, Paper SPE 169130-MS presented at the SPE Improved Oil Recovery Symposium, 12–16 April, Tulsa, Oklahoma, USA, (169130-MS). doi: 10.2118/169130-MS. [Google Scholar]
  • Bouton F., Durand M., Nardello-Rataj V., Borosy A.P., Quellet C., Aubry J.-M. (2010) A QSPR model for the prediction of the fish-tail temperature of cie4/water/polar hydrocarbon oil systems, Langmuir 26, 11, 7962–7970. doi: 10.1021/la904836m. [CrossRef] [PubMed] [Google Scholar]
  • Lukowicz T., Benazzouz A., Nardello-Rataj V., Aubry J.-M. (2015) Rationalization and prediction of the equivalent alkane carbon number (EACN) of polar hydrocarbon oils with COSMO-RS σ-moments, Langmuir 31, 41, 11220–11226. doi: 10.1021/acs.langmuir.5b02545. [CrossRef] [PubMed] [Google Scholar]
  • Lukowicz T., Illous E., Nardello-Rataj V., Aubry J.-M. (2018) Prediction of the equivalent alkane carbon number (EACN) of aprotic polar oils with COSMO-RS σ-moments, Colloids Surf. A: Physicochem. Eng. Aspects 536, 53–59. doi: 10.1016/j.colsurfa.2017.07.068. [CrossRef] [Google Scholar]
  • Cayias J.L., Schechter R.S., Wade W.H. (1976) Modeling crude oils for low interfacial tension, Soc. Pet. Eng. J. 16, 6, 351–357. doi: 10.2118/5813-PA. [CrossRef] [Google Scholar]
  • Cash L., Cayias J.L., Fournier G., Macallister D., Schares T., Schechter R.S., Wade W.H. (1977) The application of low interfacial tension scaling rules to binary hydrocarbon mixtures, J. Colloid Interface Sci. 59, 1, 39–44. doi: 10.1016/0021-9797(77)90336-8. [Google Scholar]
  • Creton B., Mougin P. (2016) Equivalent alkane carbon number of live crude oil: A predictive model based on thermodynamics, Oil Gas Sci. Technol. - Rev. IFP Energies nouvelles 71, 5, 62. doi: 10.2516/ogst/2016017. [CrossRef] [Google Scholar]
  • Soave G. (1972) Equilibrium constants from a modified Redlich-Kwong equation of state, Chem. Eng. Sci. 27, 6, 1197–1203. doi: 10.1016/0009-2509(72)80096-4. [Google Scholar]
  • Péneloux A., Rauzy E., Fréze R. (1982) A consistent correction for Redlich-Kwong-Soave volumes, Fluid Phase Equilib. 8, 1, 7–23. doi: 10.1016/0378-3812(82)80002-2. [Google Scholar]
  • Creton B. (2017) Chemoinformatics at IFP Energies nouvelles: Applications in the fields of energy, transport, and environment, Mol. Informatics 36, 10, 1700028. doi: 10.1016/0009-2509(72)80096-4. [CrossRef] [Google Scholar]
  • Katritzky A.R., Kuanar M., Slavov S., Hall C.D., Karelson M., Kahn I., Dobchev D.A. (2010) Quantitative correlation of physical and chemical properties with chemical structure: utility for prediction, Chem. Rev. 110, 10, 5714–5789. doi: 10.1021/cr900238d. [CrossRef] [PubMed] [Google Scholar]
  • Nieto-Draghi C., Fayet G., Creton B., Rozanska X., Rotureau P., de Hemptinne J.-C., Ungerer P., Rousseau B., Adamo C. (2015) A general guidebook for the theoretical prediction of physicochemical properties of chemicals for regulatory purposes, Chem. Rev. 115, 24, 13093–13164. doi: 10.1021/acs.chemrev.5b00215. [CrossRef] [PubMed] [Google Scholar]
  • Wan W., Zhao J., Harwell J.H., Shiau B.-J. (2016) Characterization of crude oil equivalent alkane carbon number (EACN) for surfactant flooding design, J. Dispers. Sci. Technol. 37, 2, 280–287. doi: 10.1080/01932691.2014.950739. [Google Scholar]
  • Jewell D.M., Weber J.H., Bunger J.W., Plancher H., Latham D.R. (1972) Ion-exchange, coordination, and adsorption chromatographic separation of heavy-end petroleum distillates, Anal. Chem. 44, 8, 1391–1395. doi: 10.1021/ac60316a003. [Google Scholar]
  • Kharrat A.M., Zacharia J., Cherian V.J., Anyatonwu A. (2007) Issues with comparing SARA methodologies, Energy Fuels 21, 6, 3618–3621. doi: 10.1021/ef700393a. [Google Scholar]
  • Behar F., Roy S., Jarvie D. (2010) Artificial maturation of a type I kerogen in closed system: Mass balance and kinetic modelling, Org. Geochem. 41, 11, 1235–1247. doi: 10.1016/j.orggeochem.2010.08.005. [Google Scholar]
  • Aske N., Kallevik H., Sjöblom J. (2001) Determination of saturate, aromatic, resin, and asphaltenic (SARA) components in crude oils by means of infrared and near-infrared spectroscopy, Energy Fuels 15, 5, 1304–1312. doi: 10.1021/ef010088h. [Google Scholar]
  • Fan T., Buckley J.S. (2002) Rapid and accurate SARA analysis of medium gravity crude oils, Energy Fuels 16, 6, 1571–1575. doi: 10.1021/ef0201228. [Google Scholar]
  • Molina D., Uribe U.N., Murgich J. (2010) Correlations between SARA fractions and physicochemical properties with 1H NMR spectra of vacuum residues from colombian crude oils, Fuel 89, 1, 185–192. doi: 10.1016/j.fuel.2009.07.021. [CrossRef] [Google Scholar]
  • Chamkalani A. (2012) Correlations between SARA fractions, density, and RI to investigate the stability of asphaltene, ISRN Anal. Chem. 2012, 219276. doi: 10.5402/2012/219276. [CrossRef] [Google Scholar]
  • Mohan Sinnathambi C., Mohamad Nor N. (2012) Relationship between SARA fractions and crude oil fouling, J. Appl. Sci. 12, 23, 2479–2483. doi: 10.3923/jas.2012.2479.2483. [CrossRef] [Google Scholar]
  • Ashoori S., Sharifi M., Masoumi M., Mohammad Salehi M. (2017) The relationship between SARA fractions and crude oil stability, Egypt. J. Pet. 26, 1, 209–213. doi: 10.1016/j.ejpe.2016.04.002. [CrossRef] [Google Scholar]
  • Weigel S., Stephan D. (2018) Relationships between the chemistry and the physical properties of bitumen, Road Mater. Pavement Des. 19, 7, 1636–1650. doi: 10.1080/14680629.2017.1338189. [CrossRef] [Google Scholar]
  • Materials Studio. version 7.0, Accelrys Software Inc.: San Diego, USA, 2014 [Google Scholar]
  • Gramatica P. (2007) Principles of QSAR models validation: Internal and external, QSAR Comb. Sci. 26, 5, 694–701. doi: 10.1002/qsar.200610151. [Google Scholar]
  • Kuei Lin L.I. (1989) A concordance correlation coefficient to evaluate reproducibility, Biometrics 45, 1, 255–268. [Google Scholar]
  • Chirico N., Gramatica P. (2011) Real external predictivity of QSAR models: How to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient, J. Chem. Inf. Model. 51, 9, 2320–2335. doi: 10.1021/ci200211n. [CrossRef] [PubMed] [Google Scholar]
  • Chirico N., Gramatica P. (2012) Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection, J. Chem. Inf. Model. 52, 8, 2044–2058. doi: 10.1021/ci300084j. [CrossRef] [PubMed] [Google Scholar]
  • Searson D.P., Leahy D.E., Willis M.J. (2010) GPTIPS: an open source genetic programming toolbox for multigene symbolic regression, Proceedings of the International MultiConference of Engineers and Computer Scientists 2010 (IMECS 2010), 17–19 March, Hong Kong, pp. 77–80. [Google Scholar]
  • 37Searson D.P. (2015) Chapter GPTIPS 2: an open-source software platform for symbolic data mining, in: Handbook of genetic programming applications, Gandomi A.H., Alavi A.H., Ryan C. (eds), Springer International Publishing, New York, NY, pp. 551–573. [CrossRef] [Google Scholar]
  • Gandomi A.H., Alavi A.H., Ryan C. (2015) Handbook of genetic programming applications, Springer International Publishing, New York, NY. [CrossRef] [Google Scholar]
  • Tropsha A., Gramatica P., Gombar V.K. (2003) The importance of being earnest: Validation is the absolute essential for successful application and interpretation of QSPR models, QSAR Comb. Sci. 22, 1, 69–77. doi: 10.1002/qsar.200390007. [Google Scholar]
  • Garg A., Garg A., Tai K. (2014) A multi-gene genetic programming model for estimating stress-dependent soil water retention curves, Comput. Geosci. 18, 1, 45–56. doi: 10.1007/s10596-013-9381-z. [Google Scholar]
  • Mohamadi-Baghmolaei M., Azin R., Sakhaei Z., Mohamadi-Baghmolaei R., Osfouri S. (2016) Novel method for estimation of gas/oil relative permeabilities, J. Mol. Liq. 224, 1109–1116. doi: 10.1016/j.molliq.2016.08.055. [Google Scholar]
  • Garg A., Garg A., Tai K., Sreedeep S. (2014) Estimation of factor of safety of rooted slope using an evolutionary approach, Ecol. Eng. 64, 314–324. doi: 10.1016/j.ecoleng.2013.12.047. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.