An comprehensive approach to implementing digital technologies in oil and gas industry workforce training

Abstract

The article substantiates the need for a systematic transition from disparate digital initiatives to an integrated educational ecosystem in the oil and gas industry in order to reduce the risks associated with the human factor and increase the effectiveness of personnel training in the context of the increasing complexity of Industry 4.0 technologies. The scientific novelty lies in the development of a comprehensive methodology that combines VR/AR environments, digital counterparts of technological installations, adaptive AI-based algorithms and mobile AR prompts combined with a single platform with methodological, organizational and economic modules for evaluating effectiveness. The methodological base includes a systematic analysis of more than 300 sources, a three-year multicenter pedagogical experiment (a consortium of companies and a university, N = 1850), stratification of the sample by position and length of service, control and experimental groups, standardized knowledge tests and practice-oriented metrics (operation time, critical/non-critical errors, compliance with regulations), expert assessments and focus groups, as well as statistical apparatus (ANOVA, correlation and regression analysis, t criterion p 0.001). It is shown that the integrated digital platform reduces the average training time by 40,5% relative to traditional methods and by 16,3% compared to isolated VR solutions, reduces the probability of critical error from 18,6% to 2,5% and increases the knowledge retention index to 81,9% versus 45,8% for classical training (p 0.001). A strong relationship was found between the depth of assimilation and long-term retention (r = 0,82), as well as the advantage of adaptive trajectories for specialists with up to 3 years of experience (an additional reduction in time by 9.2 percentage points). and a decrease in non-critical errors by 23.2 percentage points) with the effect being inversely related to seniority. The economic analysis records the total cost of ownership of 191,1 thousand rubles and the cumulative effect of 344 thousand rubles per specialist for 5 years, the net effect of 153,3 thousand rubles, an ROI of 80,2% and a payback period of ≈ 1,8 years with project sustainability under adverse scenarios (92%). Factor analysis shows the contribution of technological, methodological and organizational units (45/35/20%) and 15-20% synergy with simultaneous improvement, which confirms the feasibility of an integrated approach and the prospects for standardization, as well as deep integration of training systems with production data to support real-time solutions.