Empowering Industries with AI and BI for Continuous Data Science Advancement

Abstract

The progression of industrial advancements has steadily incorporated data and intelligence to enhance effectiveness and productivity. Industry 4.0 innovations facilitated seamless data integration and communication across industrial setups, leading to intelligent factories characterized by self-management and continuous learning. Looking ahead, Industry 5.0 aims to foster AI integration and human-robot collaboration, promoting sustainable and personalized industrial frameworks. This paper explores the strategy of complementing existing Business Intelligence (BI) processes with Artificial Intelligence (AI) to enhance gas production in an oil field in southern Oman. Current challenges include managing an undersaturated reservoir with limited data, leading to reactive approaches and suboptimal oil recovery. Our methodology leverages AI and BI tools like Microsoft Power BI and Python to automate gas detection using machine learning algorithms based on surface readings. Results demonstrate an accuracy rate of approximately 50% in predicting gas increases, with higher precision for wells with extended breakthrough times. This approach enhances operational efficiency, reduces human error, and supports proactive decision-making. Despite its simplicity, the model's potential for further research and refinement is significant, advocating for the widespread adoption of AI-driven solutions to optimize production and minimize environmental impact across various industries.