This chapter presents an innovative method for the mathematical modeling of acid treatments in carbonate reservoirs, focusing on the complex and evolving structure of near-wellbore zones. Recognizing the unique challenges posed by carbonate formations, the authors introduce an improved model for calculating the skin factor, which integrates essential parameters, including the formation of wormholes resulting from previous acid treatments. By considering these factors, the model enhances precision in predicting treatment outcomes and understanding reservoir behavior, establishing itself as a valuable tool for optimizing stimulation processes. The study delineates the model’s primary components, underscoring its capability to handle multivariate calculations. This advanced feature allows operators to simulate a range of scenarios, facilitating more accurate planning and effective execution of acid treatments. By enabling such comprehensive modeling, the approach aims to improve treatment efficiency, reduce the risk of formation damage, and ultimately increase hydrocarbon recovery rates from carbonate reservoirs. The proposed method thus represents a significant leap forward in the field of well stimulation, addressing real-world challenges associated with acidizing carbonate formations. With its focus on improving both accuracy and operational outcomes, this model provides practical solutions that benefit engineers and operators working to maximize productivity in complex carbonate environments.

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Mathematical Modeling of Acid Treatments of Carbonate Reservoirs

  • Arslan Geldimuradov,
  • Bayrammyrat Atamanov,
  • Guvanch Ishangulyyev,
  • Gadam Garayev

摘要

This chapter presents an innovative method for the mathematical modeling of acid treatments in carbonate reservoirs, focusing on the complex and evolving structure of near-wellbore zones. Recognizing the unique challenges posed by carbonate formations, the authors introduce an improved model for calculating the skin factor, which integrates essential parameters, including the formation of wormholes resulting from previous acid treatments. By considering these factors, the model enhances precision in predicting treatment outcomes and understanding reservoir behavior, establishing itself as a valuable tool for optimizing stimulation processes. The study delineates the model’s primary components, underscoring its capability to handle multivariate calculations. This advanced feature allows operators to simulate a range of scenarios, facilitating more accurate planning and effective execution of acid treatments. By enabling such comprehensive modeling, the approach aims to improve treatment efficiency, reduce the risk of formation damage, and ultimately increase hydrocarbon recovery rates from carbonate reservoirs. The proposed method thus represents a significant leap forward in the field of well stimulation, addressing real-world challenges associated with acidizing carbonate formations. With its focus on improving both accuracy and operational outcomes, this model provides practical solutions that benefit engineers and operators working to maximize productivity in complex carbonate environments.