Oil and gas is also a high-risk industry, given its sophisticated technologies, widespread environmental effects, and regulatory challenges. This study is intended to provide an image that bridges the gap between existing risk management processes and digital technologies in line with the UN SDGs. The framework promises better risk management for the industry and allows for sustainability. It adopts a qualitative Descriptive Deductive Approach (DDA) using grey literature, stakeholder interviews, and technology to identify and understand the gaps in existing risk management practices. With (DDA), this study presents an emerging conceptual framework that combines Enterprise Risk Management (ERM), Hazard and Operability Studies (HAZOP), and Digital Twin methodologies into a model of risk management to meet global sustainability objectives and goals. The research findings show that ERM, HAZOP, and other models offer a basic risk management framework, they do not have the real-time flexibility and sustainability convergence needed in today’s operating environment. With Digital Twin and predictive analytics, the framework proposes a consolidated solution to operational resilience, regulatory compliance, and environmental accountability that supports SDGs with clean and affordable energy (SDG 7), responsible consumption and production (SDG 12), and climate action (SDG 13). This research adds value to the literature on traditional risk management theories with digital technology. Tying the model to SDGs, it delivers a new multi-level model for optimization of operation, compliance, and sustainability in oil and gas for the benefit of industry stakeholders, policymakers, and researchers.