A Semianalytical Method To Predict Well Deliverability in Gas-Condensate Reservoirs
- Nitin S. Chowdhury (Shell) | Ravi Sharma (PetroTel) | Gary A. Pope (U. of Texas at Austin) | Kamy Sepehrnoori (U. of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2008
- Document Type
- Journal Paper
- 175 - 185
- 2008. Society of Petroleum Engineers
- 5.2.1 Phase Behavior and PVT Measurements, 5.6.4 Drillstem/Well Testing, 1.8 Formation Damage, 4.3.3 Aspaltenes, 4.1.2 Separation and Treating, 5.2 Reservoir Fluid Dynamics, 5.2.2 Fluid Modeling, Equations of State, 5.8.8 Gas-condensate reservoirs, 4.6 Natural Gas, 5.5 Reservoir Simulation
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A fine-grid simulation is needed to capture the buildup of a condensate bank near wells operating below the dewpoint pressure. However, full-field simulations with a sufficiently fine grid will often not be feasible or will require very long computational times. A semianalytical method has been developed that can be used to predict the gas- and condensate-production rates from such wells accurately and that has some advantages over the pseudopressure approach. The semianalytical method includes the effects of capillary number (high velocity) and non-Darcy flow. The new method has been implemented in a compositional-reservoir simulator and verified with fine-grid compositional simulation results for both lean and rich gas-condensate fluids. Pressures, saturations, relative permeabilities, viscosities, and densities calculated with the semianalytical method are in excellent agreement with the results of fine-grid compositional simulations. Coarse-grid simulations with gridblock sizes on the order of 200 ft, coupled with the semianalytical method in gridblocks with wells, yielded production rates as accurate as fine-grid simulations with gridblock sizes on the order of 2 ft. The method was tested for single-layer, multilayer, and multiwell gas-condensate reservoirs and was found to give accurate results.
The prediction of well deliverability in gas-condensate reservoirs is a complex problem. Once the pressure falls below the dewpoint, a condensate bank builds up near the wellbore, which reduces the relative permeability to gas. This may cause a significant decline in the well productivity and dominate the pressure- and production-rate behavior. The difficulty arises in capturing this near-wellbore phenomenon accurately because it is a two-phase flow problem with large changes in relative permeability, and hence the equations are highly nonlinear and do not lend themselves to analytical solutions.
The high velocity of the gas near the wellbore results in a high capillary number, which may increase the relative permeability of the gas significantly, and add to the complexity and nonlinearity of the problem. Also, near very-high-rate gas-production wells, non-Darcy flow further increases the complexity and nonlinearity. The combined effects of relative permeability, capillary number, and non-Darcy flow need to be accurately modeled to estimate the gas-condensate-well deliverability accurately. The changes in the gas and condensate viscosity and density near the well may also be important in some cases. Coarse-grid simulations do not capture these effects accurately near the wells where they matter the most and dominate the production rates.
Fine-grid compositional simulations or simulations using local grid refinement (LGR) near the wells can be used to obtain an accurate estimate of the well deliverability. However, these methods have the disadvantage of large run times, especially for full-field problems with many producing zones and other complexities. There are numerical errors associated with LGR, and these are difficult to assess in general. No comparisons to LGR were made in this work.
Several investigators have used pseudopressure functions to estimate well deliverability. These methods are simple and have been shown to yield useful predictions.
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