Risk management has become of the utmost importance in the industrial world as it provides a common ground between opportunities and risks by addressing project uncertainties. In addition, inadequate risk quantification and management have a significant impact on the decision-making outcome and the success of the project. The aim of this research is to review existing literature on risk management, evaluate and rank selected resource-related risks, and propose a framework for the Kazakh oil and gas industry.

Traditional risk assessment considers risks from two perspectives: the probability of occurrence and possible consequences of a risk event. These two indicators are further multiplied to estimate the risk index. This research followed the same method, but took into account the preliminary qualitative step of correctly evaluating likelihood and effect of risks. We designed a questionnaire of 15 factors, divided into equipment, labor, materials and exogenous categories. The survey was then distributed to project engineers and management professionals working in the local oil and gas industry.

Price fluctuations, delays in delivery of materials, change orders, slow mobilization of equipment and its failures are identified as the most serious risks. These factors are also indicated the greatest in separate probability and impact rankings. Moreover, research findings demonstrate that the likelihood of occurrence of incompetent labor and equipment shortage is closely correlated with their possible consequences at statistically significant level using the Pearson test. Change orders and price volatility have once confirmed their importance. Finally, respondents described the amount of contingency as an indicator of a risk mitigation strategy.

The suggested framework is practical for the industry and increases the chances of success of oil and gas projects in Kazakhstan and the entire region. Complex projects have a high level of technological, organizational, and informational challenges and uncertainties and are heavily resource-dependent. The combination of experts, decision-makers, and stakeholders’ judgments and statistical interpretation tools provides additional insights into the nature of risks. This study sheds light on such an important topic and improves current risk management practices.

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