A multidimensional analysis of artificial intelligence perceptions as a tool for enhancing sustainable quality in petroleum operations: An analytical study in the East Baghdad oil field

Abstract

The study aimed to analyze the perceptions of oil sector workers about artificial intelligence and its use as a tool to enhance sustainable quality in oil operations. The study applied the quantitative approach. The study population consisted of the East Baghdad oil field. The study sample amounted to 200 individuals working in the maintenance and engineering departments and the safety and environment department. The data collection tool was a questionnaire in addition to personal interviews. 200 questionnaires were distributed to the study sample in the field, and 187 questionnaires were returned, representing 93% of the total. After conducting statistical processing of the study sample's opinions, the study revealed a set of results, the most important of which was that the application of artificial intelligence tools (such as predictive data analysis and predictive maintenance) contributed to increasing the efficiency of operations such as production and maintenance. It also enhanced the Safety and Environment Department's ability to monitor pollutants and reduce emissions using smart methods, in addition to encouraging employees to adopt more sustainable solutions, especially in planning and development. Based on the study results, recommendations were formulated, such as developing ongoing training programs for all departments on the use of artificial intelligence tools in quality and sustainability, improving communication systems, providing smart sensors, linking data between departments, and deploying artificial intelligence systems to monitor emissions and assess the environmental impact in real time.