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Experimental Investigation of Immiscible Supercritical Carbon Dioxide Foam Rheology for Improved Oil Recovery

Journal of Earth Science 2017年第5期28卷 835-841页

作者： Shehzad Ahmed Khaled Abdalla Elraies jalal foroozesh Siti Rohaida Bt Mohd Shafian Muhammad Rehan Hashmet Ivy Chai Ching Hsia Abdullah Almansour Petroleum Engineering Department Universiti Teknologi PETRONAS PETRONAS Research Sdn Bhd Department of Petroleum Engineering Petroleum Institute National Center for Oil & Gas Technology King Abdulaziz City for Science and Technology

This paper presents the rheological behaviour of supercritical CO2 （sCO2） foam at reser- voir conditions of I 500 psi and 80 ℃. Different commercial surfactants were screened and utilized in or- der to generate a fairly stable CO2 foam. Mixed surfactant system was also introduced to generate strong foam. Foam rheology was studied for some specific foam qualities using a high pressure high tempera- ture （HPHT） foam loop rheometer. A typical shear thinning behaviour of the foam was observed and a significant increase in the foam viscosity was noticed with the increase of foam quality until 85%. A de- sired high apparent viscosity with coarse texture was found at 85% foam quality. Foam visualization above 85% showed an unstable foam due to extremely thin lamella which collapsed and totally disap- peared in the loop rheometer. Below 52%, a non-homogenous and unstable foam was found having low viscosity with some liquid accumulation at the bottom of the circulation loop. This research has demon- strated rheology of sCO2 foams at different qualities at HPHT to obtain optimal foam quality region for immiscible CO2 foam co-injection process.

关键词： supercritical CO2 foam apparent viscosity foam quality foam stability.

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Application of Artificial Intelligence (AI) Modeling in Kinetics of Methane Hydrate Growth

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American Journal of Analytical Chemistry 2013年第11期4卷 616-622页

作者： jalal foroozesh Abbas Khosravani Adel Mohsenzadeh Ali Haghighat Mesbahi Department of Chemical Engineering Polymer Engineering Group Isfahan University of Technology Isfahan Iran Department of Computer Science and Engineering Amirkabir University of Technology Tehran Iran Heriot-Watt University Institute of Petroleum Engineering Edinburgh UK School of Chemical and Petroleum Engineering Shiraz University Shiraz Iran

Determining thermodynamic and kinetic conditions for natural gas hydrate formation is an interesting subject for many researches. At the present, suitable information including experimental data and the thermodynamic models of hydrate formation are available which predict the thermodynamic conditions of hydrate formation. Conversely, there is no sufficient study about the kinetics of natural gas hydrate and most of experimental data and kinetic models in the literature are incomplete. Artificial Intelligence (AI) having sub-branches such as artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) has been proved as a novel tool with acceptable accuracy for modeling of engineering systems. Therefore, this paper aims to investigate the kinetics of hydrate formation by predicting the relationship of growth rate of methane hydrate with temperature and pressure using ANN and ANFIS. This goal can also be achieved by solving complicated governing equations while artificial intelligence provides an easier way to accomplish this goal. The result has shown that ANIFS is a more potential tool in predication relationship of kinetics of hydrate formation with temperature and pressure in comparison of ANN in present work.

关键词： ANFIS ANN Kinetic Growth Rate Hydrate Simulation

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