Traditional techniques to evaluate well's integrity employed for assessing mechanical integrity often come with high operational costs and logistical expenses, as they require the interruption of production or injection processes (1). Consequently, these conventional methods can be impractical and hinder overall efficiency.

However, the emergence of autonomous and intelligent intervention systems has paved the way for a significant advancement in this field. These innovative systems possess the capability to make real-time decisions in dynamic and unstructured environments. By using artificial intelligence technologies, it can autonomously evaluate mechanical integrity without human intervention.

One of the primary benefits of maintaining mechanical integrity is the assurance of safety and operational efficiency. The integrity of well structures prevents the occurrence of leaks, ruptures, or collapses, which can lead to catastrophic incidents and environmental damage. By employing autonomous and intelligent intervention systems, companies can proactively monitor the mechanical of wells, mitigating potential risks and avoiding costly operational disruptions.

These advanced systems are designed to monitor and assess critical parameters such as pressure, temperature, and flow. The real-time decision-making capability of autonomous intervention systems significantly reduces response times to potential integrity threats. By identifying issues, operators can prevent the escalation of problems and minimize associated costs. In addition to improving operational efficiency and safety, autonomous and intelligent intervention systems also offer long-term cost savings. By implementing proactive monitoring strategies, companies can optimize their resource allocation and extend the lifespan of wells. This, in turn, reduces the frequency of costly interventions and enhances overall operational profitability representing a significant leap forward in evaluating well's integrity. By reducing the need for traditional, costly techniques and enabling real-time decision-making equipment, these systems enhance safety, efficiency, and cost-effectiveness.

Studies (2, 3) demonstrates that the utilization of RLWI (Rigless Well Intervention) systems can significantly reduce the costs associated with well intervention. Also, the utilization of robotic solutions, as example, wireline tractors have been proved as an excellent solution to improve the efficiency and reliability of well integrity (4, 5, 6).

The paper will describe the progress made in developing a modular, autonomous mobile robotic platform for through-tubing operation. We outline the stages of prototype development, current project status, and tests. We also provide details on the artificial intelligence control and autonomous decision-making systems. Finally, we plan to present simulation and field test results in the final section of the paper.

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