Dynamic Risk Assessment of the Overseas Oil and Gas Investment Environment in the Big Data Era

• Main Authors: Xuqiang Duan, Xu Zhao, Jianye Liu, Shuquan Zhang, Dongkun Luo
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-03-01
• Series: Frontiers in Energy Research
• Subjects: overseas oil and gas investment; dynamic; risk assessment; CPBN; big data
• Online Access: https://www.frontiersin.org/articles/10.3389/fenrg.2021.638437/full

Our research aims to analyze how the uncertainties and risks of the overseas oil & gas investment environment change over time and reveal the specific occurrence probabilities of risk on different levels. In the process of long-drawn overseas oil & gas investment that can last for 30 years or longer, it is difficult for investment decision-makers to grasp the occurrence probabilities and trends of some specific risks accurately and in a timely manner. The overseas risk assessment system has made great progress; however, it has remained elusive due to the challenge of too many complex and interweaved factors. With the advent of big data and artificial intelligence, more precise and specific risk evaluations can be conducted. Our research selects 25 indicators from six dimensions and applies a Cloud parameter Bayesian network algorithm to dynamically assess the oil and gas overseas investment risk of 10 countries. The results reveal how risk dynamics have changed over the past two decades. Our research may serve as a reference in future overseas oil & gas investment risk decision-making, and is also significant to outbound investing, engineering, and service projects. The proper use of risk assessment results can be conducive to potential investors who may invest in potential countries in the future.