Methods for reducing risks and errors in the operation of oil and gas industry intellectual automated systems

Modern intelligent automated systems (IAS) provide a high level of automation and im-prove the efficiency of production processes in the oil and gas industry. At the same time, the operation of such systems is accompanied by risks and the probability of errors, which can lead to financial losses and emergencies. The article considers the main methods for reducing risks and errors in the operation of IAS in the oil and gas industry, in particular, improving approaches to verification and testing. The application of formal and informal verification methods and modular, integration, and property-based testing in specific IAS systems is in-vestigated. Approaches for measuring structural coverage and optimizing the testing process are identified. The results obtained are aimed at reducing the probability of errors and ensur-ing the system's compliance with industry standards. The study's results confirm the impor-tance of integrating formal methods and testing to ensure the reliability and functionality of the IAS. Formal methods allow you to detect critical errors at the modeling stage, while test-ing, in particular modular and integration, ensures the correctness of the system's operation in real conditions. The application of the proposed approaches helps minimize the risks of accidents and ensures the smooth functioning of the IAS.