Analyzing the Impact of COVID-19 on Gas Demand Markets: A Process Analytics Perspective

COVID-19 profoundly disrupted the global economy, underscoring the need for sustainable and resilient energy systems. In addition to traditional time-series approaches, incorporating process analytics provides a deeper understanding of energy consumption patterns during a disruptive event. This paper analyzes the behavioral interrelationships of various natural gas demand markets— residential, commercial, industrial, electric power, and transportation—across short-, medium-, and long-term planning horizons. Using monthly gas consumption data from January 2001 to May 2024, we apply Complete Ensemble Empirical Mode Decomposition (CEEMD) to extract intrinsic demand cycles and explore their co-movements. To enhance interpretability, we introduce a process mining perspective that treats demand data as event logs, uncovering structural shifts in market behavior due to COVID-19. Our findings reveal significant post-pandemic changes in inter-market dynamics, particularly in the strategic horizon, and highlight the value of integrating event-driven process insights with empirical forecasting. The results provide actionable guidance for sustainable production and integrated energy planning in the face of such future disruptions.