Mechanistic Decline Curves for Gas-Condensate Reservoirs: Model Development Conference Paper uri icon

abstract

  • Abstract This manuscript incorporates material balance, complex fluid behavior, reservoir characteristics, and well operating constraints into a mechanistic model to forecast production from gas-condensate reservoirs. Our model considers condensate banking, while running at least one order magnitude faster than commercial compositional reservoir simulators. To estimate production from gas-condensate reservoirs we used a thermodynamic cubic equation of state (EOS) to evaluate Constant Volume Depletion (CVD) coupled with radial pseudo-steady state gas flow equations. This allows a relationship between production and time for different production modes (fixed or variable drawdowns, gas rates, or flowing bottomhole pressure), while honoring material balance. As near-wellbore and reservoir pressure drops below saturation pressure, condensate banking occurs in gas-condensate reservoir causing hindrances to flow. Our model considers the reservoir as two concentric tanks. The conventional CVD is modified to begin production at pressures higher than the saturation pressure and to allow two-phase flow. The inner small CVD tank is used to model the near-wellbore saturation using alternative production rules and replenishment schemes. The saturation determined from the small tank determines the appropriate relative permeabilities in the flow equation. The forecasts developed from this mechanistic model versus conventional decline curves, constructed from a commercial numerical simulator predicted data, show very promising results and stress the danger of using empirical methods. The value of this model rests in its portability, speed and flexibility, while using rigorous mass balance, complex two-phase flow behavior, and realistic production constraints. This method provides the physical basis for reservoir engineers to predict a more reliable production behavior from gas-condensate reservoirs that can be used to plan depletion strategies and facilities.

name of conference

  • Day 2 Thu, May 18, 2017

published proceedings

  • Day 2 Thu, May 18, 2017

author list (cited authors)

  • Ariwibowo, R., & Barrufet, M. A.

citation count

  • 0

complete list of authors

  • Ariwibowo, R||Barrufet, MA

publication date

  • January 2017