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Single-Well Simulation for Horizontal Wells in Fractured Gas Condensate Reservoirs
Fuguo Yin1, Shiqing Cheng1, Wenpeng Bai1
1State Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum Beijing, Beijing 102249, China.
Abstract:
Fractured gas condensate reservoirs (FGCR) are a complex, special, and highly valuable type of gas reservoir, accounting for a significant proportion of gas reservoir development. In recent years, with the continuous advancement of horizontal well technology, it has become the main approach for the development of FGCR. The current model is unable to accurately represent the fluid distribution in the near-well area of horizontal wells due to the unique retrograde condensation phenomenon in GCR. Additionally, the presence of fractures complicates the solution of traditional analytical models. In response to this issue, this paper proposes a novel semianalytical model for horizontal wells in FGCR, which incorporates natural fractures, multiphase flow, and the influence of stress sensitivity on pressure response. A dual-porosity model is employed to simulate fractured reservoirs, and a four-region radial composite model is developed to characterize multiphase flow resulting from retrograde condensation in GCR. The pseudopressure transform, Pedrosa transform, Laplace transform, and Finite Cosine transform are utilized to address the nonlinear partial differential equation. A systematic verification of the semianalytical solution is confirmed through a comparison with the numerical solution from computer modeling group (CMG). We thoroughly explain the physical significance of the various features by identifying the 12 flow regimes of the typical curve. Furthermore, we offer a method for assessing the extent of retrograde condensation and the size of the retrograde condensate region based on the curve's characteristics. Finally, the pressure measurements recorded from the Bohai field are carried out to validate the accuracy of the proposed model. The results show that the predictions of the new model are in good agreement with the actual production data, demonstrating the proposed solution's applicability.
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