TEM-function

In petroleum engineering, TEM (True Effective Mobility), also called TEM-function, is a criterion to characterize dynamic two-phase flow characteristics of rocks (or dynamic rock quality). [1][2][3][4][5][6][7][8] TEM is a function of Relative permeability, Porosity, absolute Permeability and fluid Viscosity, and can be determined for each fluid phase separately. TEM-function has been derived from Darcy's law for multiphase flow. [1]

in which k is the absolute Permeability, kr is the Relative permeability, φ is the Porosity, and μ is the fluid Viscosity. Rocks with better fluid dynamics (i.e., experiencing a lower pressure drop in conducting a fluid phase) have higher TEM versus saturation curves. Rocks with lower TEM versus saturation curves resemble low quality systems.[1]

TEM-function in analyzing Relative permeability data is analogous with Leverett J-function in analyzing Capillary pressure data. Furthermore, TEM-function in two-phase flow systems is extension of RQI (Rock Quality Index) for single-phase systems. [1]

Also, TEM-function can be used for averaging relative permeability curves (for each fluid phase, separately (i.e., water, oil, gas, CO2)).[1]

References
  1. Mirzaei-Paiaman, A.; Saboorian-Jooybari, H.; Chen, Z.; Ostadhassan, M. (2019). "New technique of True Effective Mobility (TEM-Function) in dynamic rock typing: Reduction of uncertainties in relative permeability data for reservoir simulation". Article Published in Journal of Petroleum Science and Engineering - JPSE - by Elsevier B.V., August, 2019. doi:10.1016/j.ptlrs.2020.06.003. Retrieved 6 August 2020.
  2. Mirzaei-Paiaman, A.; Asadolahpour, S.R.; Saboorian-Jooybari, H.; Chen, Z.; Ostadhassan, M. (2020). "A new framework for selection of representative samples for special core analysis". Article Published in Petroleum Research by Elsevier B.V., 2020. doi:10.1016/j.ptlrs.2020.06.003. Retrieved 6 August 2020.]
  3. Mirzaei-Paiaman, A. (2019). "New Concept of Dynamic Rock Typing and Necessity of Modifying Current Reservoir Simulators" (PDF). Technical Feature Article Published in SPE Review London e-Magazine by Society of Petroleum Engineers' London Branch, June, 2019: 7–10. Retrieved 6 August 2020.
  4. Wang, R. (2019). "Grid density overlapping hierarchical algorithm for clustering of carbonate reservoir rock types: A case from Mishrif Formation of West Qurna-1 oilfield, Iraq". Article Published in Journal of Petroleum Science and Engineering by Elsevier: -. Retrieved 6 August 2020.
  5. Noorbakhsh, A. (2020). "Field Production Optimization Using Sequential Quadratic Programming (SQP) Algorithm in ESP-Implemented Wells, A Comparison Approach". Article Published in Journal of Petroleum Science and Technology by RIPI: -. Retrieved 6 August 2020.
  6. Nazari, M.H. (2019). "Investigation of factors influencing geological heterogeneity in tight gas carbonates, Permian reservoir of the Persian Gulf". Article Published in Journal of Petroleum Science and Engineering by Elsevier: -. Retrieved 6 August 2020.
  7. Liu, Y. (2019). "Petrophysical static rock typing for carbonate reservoirs based on mercury injection capillary pressure curves using principal component analysis". Article Published in Journal of Petroleum Science and Engineering by Elsevier: -. Retrieved 6 August 2020.
  8. Shakiba, M. (2020). "An experimental investigation of the proportion of mortar components on physical and geomechanical characteristics of unconsolidated artificial reservoir sandstones". Article Published in Journal of Petroleum Science and Engineering by Elsevier: -. Retrieved 6 August 2020.


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