Assessing and managing risks in the oil and gas industry with machine learning and digital technologies

Abstract

This article aims to provide a comprehensive overview of the current use of machine learning and digital technologies for risk assessment and management in the oil and gas industry. A comprehensive methodology was used, including a literature review, data collection from academic journals, industry reports, and online sources, data analysis using machine learning algorithms, and results interpretation. The results from the study provide valuable insights into the use of machine learning and digital technologies for risk management, including the effectiveness of machine learning algorithms for modeling and predicting risks and the benefits of IoT and blockchain technology for data collection and analysis. The study highlights that the use of these technologies has the potential to significantly enhance the effectiveness of risk management in the oil and gas industry, but more research is needed to fully understand the benefits and limitations of these approaches and to identify best practices for implementation.