Application of Memory Concept on Petroleum Reservoir Characterization: A Critical Review
- Mohammad Islam Miah (Department of Process Engineering Oil and Gas Program, Memorial University of Newfoundland, St. John's) | Pulok Kanti Deb (Department of Process Engineering Oil and Gas Program, Memorial University of Newfoundland, St. John's) | Md. Shad Rahman (Department of Process Engineering Oil and Gas Program, Memorial University of Newfoundland, St. John's) | M. Enamul Hossain (Department of Process Engineering Oil and Gas Program, Memorial University of Newfoundland, St. John's)
- Document ID
- Society of Petroleum Engineers
- SPE Kuwait Oil & Gas Show and Conference, 15-18 October , Kuwait City, Kuwait
- Publication Date
- Document Type
- Conference Paper
- 2017. Society of Petroleum Engineers
- 5.2.1 Phase Behavior and PVT Measurements, 5.9 Non-Traditional Resources, 5.2 Fluid Characterization, 5.9.2 Geothermal Resources, 0.2 Wellbore Design, 5.1 Reservoir Characterisation, 1.2.3 Rock properties, 5 Reservoir Desciption & Dynamics
- Memory concept, Fluid flow model, Fluid behaviour, Viscosity, Permeability
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- 151 since 2007
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Petroleum reservoir rock and fluid properties vary during any pressure disturbances or thermal actions in the reservoir formation. It is important to consider the rock properties such as permeability, porosity, etc. and fluid properties such as viscosity, PVT properties etc. as a function of time for applications including geothermal actions, chemical reactions, and other geological activities in the sub-surface of the reservoir complex structure. Memory is the effect of past events on the present and future course of developments. The continuous alteration of rock/fluid properties can be characterized using memory concept. It is also significant to consider the rock, and fluid properties as a function of time, and the inclusion of recently introduced memory concept in petroleum engineering study. In this paper, a detailed review of the existing techniques and models of reservoir characterization is presented. This study will provide an inclusive information on the present status of memory-based fluid flow modeling, rock and fluid properties models development under spurious assumptions during reservoir characterization. The variations of porosity and permeability over the distance are presented which are from the wellbore towards the outer boundary of the reservoir with time in actual reservoir conditions. Reservoir porosity and permeability are directly related to the reservoir formation depth and pressure. Reservoir porosity and pressure are decreasing over time. Permeability is changed over distance because it is directly related to the pressure of the complex reservoir system. In addition, the viscosity is a function of temperature of crude oil. Since memory-based diffusivity equation through porous media is more rigorous, as it incorporates continuous alteration of rock and fluid, and viscosity of oil predicts results from memory models should be preferred and reliable during the convergence process in reservoir simulators. This paper also aids as an insight of the future research opportunity toward developing models for reservoir properties, and models for fluid flow through porous media in the complex reservoir by the application of memory concept.
|File Size||1 MB||Number of Pages||27|
Albinali, A., and Ozkan, E. (2016). Anomalous Diffusion Approach and Field Application for Fractured Nano-Porous Reservoirs. Society of Petroleum Engineers. doi: 10.2118/181255-MS
Amaefule, J.O., Altunbay, M., Tiab, D., Kersey, D.G., and Keelan, D.K., (1993). Enhanced Reservoir Description: Using Core and Log Data to Identify Hydraulic (Flow) Units and Predict Permeability in Uncored Intervals/Wells. Paper SPE 26436 Presented at The SPE Annual Technical Conference and Exhibition, Houston, 3–6 October.
Azevedo, L. And Soares, A. (2017), Geostatistical Methods for Reservoir Geophysics, Advances in Oil and Gas Exploration & Production, DOI 10.1007/978-3-319-53201-1_4.
Bateman, R.M., (2015). Cased-Hole Log Analysis and Reservoir Performance Monitoring, DOI 10.1007/978-1-4939-2068-6_3.
Chang, D., Vinegar, H., Morriss, C., And Straley, C., 1994, Effective Porosity, Producible Fluid and Permeability in Carbonates from NMR Logging: Transactions of The Society of Professional Well Log Analysts, 35th Annual Logging Symposium, Paper A, 21 P. Later Published In 1997: The Log Analyst, V. 38, No. 2, Pp. 60–72.
Chen, C. and Raghavan, R. (2015). Transient flow in a linear reservoir for space&-time fractional diffusion. J. Pet. Sci. Eng. 128: 194-202. DOI: 10.1016/j.petrol.2015.02.021.
Di Giuseppe, E., Moroni, M. and Caputo, (2010). Flux in Porous Media with Memory: Models and Experiments, M. Transp Porous Med (2010) 83: 479. Doi:10.1007/S11242-009-9456-4.
Dubois, M.K., Byrnes, A.P., Bohling, G.C., and Doveton, J.H., (2006). Multiscale Geologic and Petrophysical Modeling of The Giant Hugoton Gas Field (Permian), Kansas And Oklahoma, In P.M. Harris And L.J. Webber, Eds., Giant Hydrocarbon Reservoirs of The World: From Rocks to Reservoir Characterization and Modeling: American Association of Petroleum Geologists Memoir 88, Tulsa, Oklahoma, P. 307–353.
El-Hoshoudy, A.N., Farag, A.B., Ali, O.I.M., EL-Batanoney, M.H., Desouky, S.E.M., and Ramzi, M., (2013). New Correlations for Prediction of Viscosity and Density of Egyptian Oil Reservoirs, Dx.Doi.Org/10.1016/J.Fuel.2013.05.045, Fuel 112 (2013) 277–282.
Gharbi, R.B., Elsharkawy, A.M., and Karkoub, M. (1999). Universal Neural-Network-Based Model for Predictring PVT Properties of Crude Oil Systems, Energy Fuels, 1999, 13 (2), Pp 454–458, DOI: 10.1021/Ef980143v.
Hagemann, S., and Stacke T., (2015). Impact of The Soil Hydrology Scheme on Simulated Soil Moisture Memory, Clim Dyn 44:1731–1750. DOI 10.1007/S00382-014-2221-6, 2015.
Hanafy, H.H., Macary, S.M., Elnady, Y.M., Bayomi, A.A., and El-Batanoney, M.H., (1997). Empirical PVT Correlations Applied to Egyptian Crude Oils Exemplify Significance of Using Regional Correlations. SPE 37295, Presented at The SPE International Symposium on Oil Field Chemistry Held in Houston, Texas, 18–21 Febreuary, 1997.
Hassan, A.M., And Hossain, E.M., (2016). Coupling Memory-Based Diffusivity Model with Energy Balance Equation to Estimate Temperature Distributions During Thermal EOR Process. Society of Petroleum Engineers (2016). Doi:10.2118/182767-MS.
Hossain, M. E., and Mousavizadegan, S.H., (2009a). Modified Engineering Approach with The Variation of Permeability Over Time Using the Memory Concept, Proceedings of The Third International Conference on Modeling, Simulation and Applied Optimization Sharjah, U.A.E January 20-22, 2009, Paper ID, 41-77246.
Hossain, M.EMousavizadegan., S.H., and Islam, M.R., (2009c). Modified Engineering Approach with The Variation of Permeability Over Time Using the Memory Concept, Proceedings of The Third International Conference on Modeling, Simulation and Applied Optimization Sharjah, U.A.E January 20-22, 2009, Paper ID: 41 – 77246.
Hossain, M.E., and Abu-Khamsin, S., (2011). Utilization of Memory Concept to Develop Heat Transfer Dimensionless Numbers for Porous Media Undergoing Thermal Flooding with Equal Rock and Fluid Temperatures, J. Porous Media. 15 18. Doi:10.1615/Jpormedia.V15.I10.50, 2011.
Izadi, M., and Ghalambor, A. (2012). A New Approach in Permeability and Hydraulic Flow Unit Determination. Society of Petroleum Engineers. Doi:10.2118/151576-MS.
Lan, C., Chen, S., Mendez, F. E., and Sy, R. (2010). Sourceless Porosity Estimation in Gas Reservoirs Using Integrated Acoustic and NMR Logs. Society of Petroleum Engineers. doi: 10.2118/133487-MS
Minh, C. C., Gubelin, G., Ramamoorthy, R., and Mcgeoch, S. (2001). Sonic-Magnetic Resonance Method: A Sourceless Porosity Evaluation in Gas-Bearing Reservoirs. Society of Petroleum Engineers. Doi:10.2118/72180-PA.
Page, G., Fanini, O., Kriegshäuser, B., Mollison, R., Liming, Y., and Colley, N., (2001). Field Example Demonstrating a Significant Increase in Calculated Gas-In-Place: An Enhanced Shaly Sand Reservoir Characterisation Model Utilizing 3DEX Multicomponent Induction Data: Society of Petroleum Engineers, SPE 71724-MS, 14 P.
Shahvar, M.B., Kharrat, R., and Matin, M., (2010). Applying Flow Zone Index Approach and Artificial Neural Networks Modeling Technique for Characterizing a Heterogeneous Carbonate Reservoir Using Dynamic Data: Case Study of An Iranian Reservoir. In: Proceedings of The SPE Trinidad And Tobago Energy Resources Conferences, Trinidad.
Shenawi, S.H., Al-Mohammadi, H., and Faqehy, M., (2009). Development of Generalized Porosity–Permeability Transforms by Hydraulic Units for Carbonate Oil Reservoirs in Saudi Arabia. Paper SPE 125380, Prepared for Presentation at the 2009 SPE/EAGE Reservoir Characterization and Simulation Conference Held in Abu Dhabi, UAE, 19-21 October.
Shenawi, S.H., White, J.P., Elrafie, E.A., and Kilany, K.A. (2007). Permeability and Water Saturation Distribution by Lithologic Facies and Hydraulic Units: A Reservoir Simulation Case Study. Paper SPE 105273, Presented at the 15th SPE Middle East Oil & Gas Show and Conference, Kingdom of Bahrain.
Soto, R.B., Torres, F., Arango, S., Cobaleda, G., (2001). Improved Reservoir Permeability Models from Flow Units and Soft Computing Techniques: A Case Study, Suria And Reforma-Libertad Fields, Columbia. In: Proceedings of The SPE Latin American And Caribbean Petroleum Engineering Conference, Buenos Aires.
Yang, S., (2017). Fundamentals of Petrophysics, Spinger Mineralogy, Pp. 501, DOI 10.1007/978-3-662-53529-5.
Zhang, H.M., (2003). Driver Memory, Traffic Viscosity and A Viscous Vehicular Traffic Flow Model, Transp. Res. Part B Methodol. 37 27–41. Doi:10.1016/S0191-2615(01)00043-1, 2003.