Digital Twin-Driven Environmental Compliance Models for Sustainable Procurement in Oil, Gas, and Utilities

Abstract

This review investigates the role of digital twin technology in enhancing environmental compliance within sustainable procurement systems across the oil, gas, and utilities sectors. As industries face increasing regulatory scrutiny and the need to align operations with environmental, social, and governance (ESG) goals, digital twins offer a promising approach to simulate, monitor, and optimize procurement practices in real time. This paper explores how virtual replicas of physical assets and processes can enable real-time tracking of environmental performance, automate compliance with regulatory thresholds, and facilitate lifecycle analysis of supplier operations. By integrating data analytics, IoT sensors, and AI algorithms within a digital twin ecosystem, organizations can proactively identify non-compliance risks, reduce resource wastage, and enhance transparency across the procurement lifecycle. Furthermore, the paper examines implementation frameworks, adoption challenges, and the strategic value of these systems in driving sustainability-led procurement decisions. Through a structured synthesis of current innovations and future research trajectories, this study provides a roadmap for operationalizing digital twins in environmental compliance across resource-intensive industries.