Abstract
<jats:p>The article examines the theoretical and practical aspects of applying artificial intelligence (AI) technologies in the operation of oil and gas condensate wells. The main focus is on the concept of the “Smart Well,” which is based on the integration of intelligent sensor systems, digital twins, and machine learning algorithms to optimize hydrocarbon production . The paper analyzes global and domestic trends in the digitalization of the oil and gas industry, including such projects as Shell Smart Fields, Schlumberger Delfi, BP Field of the Future, Equinor Integrated Operations, as well as national initiatives within the framework of the “Digital Oilfield” program in Kazakhstan. Special attention is paid to the implementation of predictive analytics, edge computing technologies, SCADA-based control systems, and the development of digital twins for monitoring and modeling technological processes. The necessity of transitioning from traditional dispatch-based management to intelligent, proactive, and autonomous operational systems based on self-learning models is substantiated. The methodological basis of the study relies on a comparative analysis of international experience, synthesis of empirical data, and expert assessments of the effectiveness of AI implementation in the oil and gas sector. In conclusion, the key advantages of digitalization are highlighted — increased energy efficiency and reliability of processes, reduced operational costs, minimization of production risks, and the formation of intelligent oilfields of the future (Smart Field) capable of adaptive real-time data-driven management.</jats:p>