مهدی محمدعلیپور
Acidizing is a critical stimulation technique in the oil and gas industry, employed to enhance
hydrocarbon production from wells. This process involves injecting acid, typically hydrochloric
acid (HCl) or other acid mixtures, into the wellbore and surrounding rock formations to dissolve
minerals such as limestone, dolomite, or calcite. By improving reservoir rock permeability and
creating flow channels, acidizing significantly boosts well productivity, particularly in carbonate
reservoirs prone to scale buildup or formation damage. The technique not only increases
recovery but also extends well life and reduces operational costs.
The integration of AI in acidizing simulations and scale-up processes presents transformative
opportunities. AI models can analyze complex cases, predict acid-rock interactions, and
optimize treatment designs for field-scale applications. By coupling machine learning with
advanced simulation tools, operators can better model heterogeneous reservoir conditions,
enhance the accuracy of performance forecasts, and minimize uncertainties in upscaling from
core samples to field implementations. This fusion of AI with traditional techniques ensures
more efficient, cost-effective, and sustainable acidizing operations.
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