A robust approach to predict distillate rate through steam distillation process for oil recovery

References

• Ahmadi, M. A. (2015). Connectionist approach estimates gas-oil relative permeability in petroleum reservoirs: application to reservoir simulation. Fuel 140C:429–439.
   Web of Science ®Google Scholar
• Ahmadi, M. A. (2016). Toward reliable model for prediction drilling fluid density at wellbore conditions: A LSSVM model. Neurocomputing 211:143–149.
   Web of Science ®Google Scholar
• Ahmadi, M. A., and Bahadori, A. (2015). A LSSVM approach for determining well placement and conning phenomena in horizontal wells. Fuel 153:276–283.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Bahadori, A., and Shadizadeh, S. R. (2015a). A rigorous model to predict the amount of dissolved calcium carbonate concentration through oil field brines: side effect of pressure and temperature. Fuel 139:154–159.
   Web of Science ®Google Scholar
• Ahmadi, M. A., and Ebadi, M. (2014). Evolving predictive model to determine condensate-to-gas ratio in retrograde condensate gas reservoirs. Fuel 124:241–257.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Ebadi, M., and Hosseini, S. M. (2014). Prediction breakthrough time of water coning in the fractured reservoirs by implementing low parameter support vector machine approach. Fuel 117:579–589.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Galedarzadeh, M., and Shadizadeh, S. R. (2016a). Low parameter model to monitor bottom hole pressure in vertical multiphase flow in oil production wells. Petroleum 2:258–266.
   Google Scholar
• Ahmadi, M. A., and Golshadi, M. (2012). Neural network based swarm concept for prediction asphaltene precipitation due to natural depletion. J. Pet. Sci. Eng. 98–99:40–49.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Kashiwao, T., and Bahadori, A. (2015b). Prediction of oil production rate using vapor-extraction technique in heavy oil recovery operations. Pet. Sci. Technol. 33:1764–1769.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Kashiwao, T., Rozyn, J., and Bahadori, A. (2016b). Accurate prediction of properties of carbon dioxide for carbon capture and sequestration operations. Pet. Sci. Technol. 34:97–103.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Kashiwao, T., Rozyn, J., and Bahadori, A. (2016c). Estimation of water-hydrocarbon mutual solubility in gas processing operations using an intelligent model. Pet. Sci. Technol. 34:328–334.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Lee, M., and Bahadori, A. (2015c). Prediction of a solid desiccant dehydrator performance using least squares support vector machines algorithm. J. Taiwan Instit. Chem. Eng. 50:115–122.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Mahmoudi, B., and Yazdanpanah, A. (2016d). Development of robust model to estimate gas–oil interfacial tension using least square support vector machine: experimental and modeling study. J. Supercrit. Fluids 107:122–128.
   Web of Science ®Google Scholar
• Ahmadi, M. A., and Pournik, M. (2016). A predictive model of chemical flooding for enhanced oil recovery purposes: application of least square support vector machine. Petroleum 2:177–182.
   Google Scholar
• Ahmadi, M. A., and Shadizadeh, S. R. (2012). New approach for prediction of asphaltene precipitation due to natural depletion by using evolutionary algorithm concept. Fuel 102:716–723.
   Web of Science ®Google Scholar
• Ahmadi, M. A., Zeinali Hasanvand, M., and Bahadori, A. (2015). A LSSVM approach to predict temperature drop accompanying a given pressure drop for the natural gas production and processing systems. Int. J. Ambient Energy 38:122–129.
   Web of Science ®Google Scholar
• Amedi, H. R., Baghban, A., and Ahmadi, M. A. (2016). Evolving machine learning models to predict hydrogen sulfide solubility in the presence of various ionic liquids. J. Mol. Liquids 216:411–422.
   Web of Science ®Google Scholar
• Cao, S.-G., Liu, Y.-B., and Wang, Y.-P. (2008). A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM. J. China Univ. Mining Technol. 18:172–176.
   Google Scholar
• Duerksen, J. H., and Hsueh, L. (1983). Steam distillation of crude oils. SPE J. 23:265–271.
   Google Scholar
• Fazeli, H., Soleimani, R., Ahmadi, M. A., Badrnezhad, R., and Mohammadi, A. H. (2013). Experimental study and modeling of ultrafiltration of refinery effluents using a hybrid intelligent approach. Energy Fuels 27:3523–3537.
   Web of Science ®Google Scholar
• Jaiswal, N. J., and Mamora, D. D. (2007). Distillation effects in heavy oil recovery under steam injection with hydrocarbon additives. SPE 110712, SPE Annual Technical Conference and Exhibition, Anaheim, California, November 11–14.
   Google Scholar
• Kisi, O. (2012). Modeling discharge-suspended sediment relationship using least square support vector machine. J. Hydrol. 456–457:110–120.
   Web of Science ®Google Scholar
• Lim, K. T., Ramey, H. J. Jr., and Brigham, W. E. (1992). Steam distillation and oil quality change during thermal oil recovery. SPE 23718, SPE Latin America Petroleum Engineering Conference, Caracas, Venezuela, March 8–11.
   Google Scholar
• Mamora, D. D., and Sutadiwiria, G. (1999). An analytical model for light oil recovery by steam distillation. SPE 54094, International Thermal Operations/Heavy Oil Symposium, Bakersfield, California, March 17–19.
   Google Scholar
• Sukar, J. K. (1966). Calculation of oil distilled during steam flooding of light crude. SPE 1609, Annual Fall Meeting of SPE, Dallas, Texas, October 2–5.
   Google Scholar
• Suykens, J. A. K., Van Gestel, T., De Brabanter, J., De Moor, B., and Vandewalle, J. (2002). Least squares support vector machines. Singapore: World Scientific.
   Google Scholar
• Suykens, J. A. K., and Vandewalle, J. (1999). Least squares support vector machine classifiers. Neural Process. Lett. 9:293–300.
   Web of Science ®Google Scholar
• Vafaiei, M. T., Eslamloueyan, R., and Ayatollahi, S. (2009a). Simulation of steam distillation process using neural networks. Chem. Eng. Res. Des. 87:997–1002.
   Web of Science ®Google Scholar
• Vafaei, M. T., Eslamloueyan, R., Enfeali, L., and Ayatollahi, S. (2009b). Analysis and simulation of steam distillation mechanism during the steam injection process. Energy Fuels 23:327–333.
   Web of Science ®Google Scholar
• Willman, B. T., Valleroy, V. V., Runberg, G. W., Cornelius, A. J., and Powers, L. W. (1961). Laboratory studies of oil recovery by steam injection. J. Pet. Sci. Technol. 222:681–690.
   Google Scholar
• Wu, C. H., and Elder, R. B. (1983). Correlation of crude oil steam distillation yield with basic crude oil properties. SPE J. 23:937–945.
   Google Scholar