Nowadays the quantitative risk analysis approaches in various fields are widely used at different business case stages: geology, engineering, construction and operations. You have probably heard of the QRA, Cost and Schedule Risk Analyzes, Reliability and Availability Modeling, Reliability Centered Maintenance etc., which have shown their value, added at different stages. These methods are aimed at improving the decision quality (DQ).
However, classically these methods give recommendations to decision makers with some delay, and sometimes it even happens that the recommendations are not relevant. Given the reduction in cost of the real-time data extraction, transmission and processing infrastructure, the risk analysis toolset has received a new set of characteristics that significantly improve several stages of DQ.
Within this workshop, speaker will demonstrate theoretical and practical benefits, challenges of machine learning in real-time risk analysis. Speaker also will present the machine learning use case at the refining process allowing in real time to eliminate the HSE risk and increase operational efficiency.
This is a must watch session for anyone working in risk management and a great foundation for the whole week. Make sure you sign up!
Damir Ramazanov has practiced different quantitative analysis and risk modeling approaches for over 15 years mainly in oil & gas, power generation and mining & metal industries at different business case stages (from FEL1 to operations). He has MSc in O&G Operations (Ufa State Petroleum Institute, 2005), PhD on quantitative risk modeling of the enhanced oil recovery projects (Russian Academy of Science, 2010), MBA Big Data & Business Analytics (Amsterdam Business School, University of Amsterdam, 2019), certificates PMI-RMP and PMI-PMP. He currently holds the position of Group Project Risk Manager at ERG Group HQ and supports C-executives on risk-informed decisions on portfolio, program and project levels. Prior to joining ERG, he worked as a chief economist in Russian-Swiss JV on Oil Exploration, consulting company, a risk manager in Bashneft, a head of downstream risk management division in Gazpromneft, risk management lead in Lukoil Overseas and Lukoil International Upstream East. Interests: Data Science, Decision Analysis, Business Risk Modeling, Data-Driven Management, Project Management
Alex has created a short bootcamp designed to help companies implement quantitative risk management. Imagine saving the company so much money that investing in risk management competencies and resources becomes a no brainer for the executives. That's exactly what Alex Sidorenko did at a global $10B chemical company and he has been kind enough to share his top tips and lessons learned with you each week. Sign up now!