In the evolving landscape of the oil and gas industry, Digital Twin has emerged as a transformative technology, offering a virtual representation of physical assets to enhance operational efficiency and environmental monitoring. These models, powered by real-time data acquisition, are unique in simulating, predicting, and optimizing the performance of oil and gas operations. This paper aims to map the monitoring variables utilized in Digital Twins in the oil and gas industry, focusing on identifying the variables directly related to operations and those concerning the surrounding environment. By employing a Systematic Literature Review, the study analyzed 1300 articles, from 2018 to 2023, to select 73 publications relevant to the integration of Digital Twins in oil and gas operations. As main results, we identified pressure, temperature, and equipment performance as the most frequently monitored variables, underscoring their critical role in operational safety and efficiency. Furthermore, the study releveled a predominant focus on “Efficiency and Optimization” and “Safety and Maintenance” among the thematic clusters, with these areas receiving significant attention in the selected publications. By identifying prevalent trends and gaps, particularly the underrepresentation of environmental variables, this work contributes to the academic and practical knowledge on optimizing Digital Twin models for oil and gas.