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Elementary Pore Network Models Based on Complex Analysis Methods (CAM): Fundamental Insights for Shale Field Development

Author

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  • Ruud Weijermars

    (Harold Vance Department of Petroleum Engineering, Texas A&M University, 3116 TAMU, College Station, TX 77843-3116, USA)

  • Aadi Khanal

    (Harold Vance Department of Petroleum Engineering, Texas A&M University, 3116 TAMU, College Station, TX 77843-3116, USA)

Abstract

This paper presents insights on flow in porous media from a model tool based on complex analysis methods (CAM) that is grid-less and therefore can visualize fluid flow through pores at high resolution. Elementary pore network models were constructed to visualize flow and the corresponding dynamic bottomhole pressure (BHP) profiles in a well at reservoir outflow points. The pore networks provide the flow paths in shale for transferring hydrocarbons to the wellbore. For the base case model, we constructed a single flow path made up of an array of pores and throats of variable diameter. A passive ganglion (tracer) of an incompressible fluid was introduced to demonstrate the deformation of such ganglions when moving through the pores. The simplified micro-flow channel model was then expanded by stacking flow elements vertically and horizontally to create complex flow paths representing a small section of a porous reservoir. With these model elements in place, the flow transition from the porous reservoir fluid to the wellbore was modeled for typical stages in a well life. The dynamic component of the bottomhole pressure (BHP) was modeled not only during production but also during the drilling of a formation (with either balanced, underbalanced or overbalanced wellbore pressure). In a final set of simulations, the movement of an active ganglion (with surface tension) through the pore space was simulated by introducing a dipole element (which resisted deformation during the movement through the pores). Such movement is of special interest in shale, because of the possible delay in the onset of bubble point pressure due to capillarity. Capillary forces may delay the reservoir to reach the bubble point pressure, which postpones the pressure-drop trigger that would lead to an increase of the gas–oil ratio. The calculation of the estimated ultimate recovery (EUR) with an erroneous assumption of an early increase in the gas–oil ratio will result in a lower volume than when the bubble point delay is considered.

Suggested Citation

  • Ruud Weijermars & Aadi Khanal, 2019. "Elementary Pore Network Models Based on Complex Analysis Methods (CAM): Fundamental Insights for Shale Field Development," Energies, MDPI, vol. 12(7), pages 1-39, April.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1243-:d:218938
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    References listed on IDEAS

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    1. Ruud Weijermars & Arnaud Van Harmelen, 2018. "Shale Reservoir Drainage Visualized for a Wolfcamp Well (Midland Basin, West Texas, USA)," Energies, MDPI, vol. 11(7), pages 1-21, June.
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