Deepwater oil production environments rely heavily on Supervisory Control and Data Acquisition (SCADA) and Distributed Control Systems (DCS) to monitor and control complex offshore processes. These systems are critical for ensuring operational safety, efficiency, and continuity. However, as offshore facilities become increasingly digitized and interconnected, they face escalating cybersecurity threats that can compromise control integrity, disrupt production, and pose severe environmental and safety risks. This proposes a comprehensive cyber-resilient model tailored specifically for securing SCADA and DCS systems within deepwater oil production settings. The proposed model emphasizes a multi-layered security architecture that integrates network segmentation, intrusion detection and prevention systems, robust authentication mechanisms, and encrypted communication protocols. By adopting fault-tolerant and redundant cybersecurity strategies, the model enhances the ability of SCADA and DCS platforms to detect, withstand, and recover from cyber incidents with minimal operational impact. Real-time monitoring combined with advanced anomaly detection algorithms enables proactive threat identification, while automated failover and recovery mechanisms ensure system resilience in the face of attacks or failures. Implementation challenges unique to deepwater offshore environments—such as harsh physical conditions, integration with legacy systems, and limited onsite human resources—are addressed to ensure practical applicability. Regulatory compliance and cost-effectiveness considerations are also incorporated to align with industry standards and operational constraints. A case study application on a representative deepwater platform demonstrates the model’s effectiveness in mitigating cyber threats, reducing response times, and maintaining continuous safe operations. The findings highlight the strategic importance of cyber-resilience in protecting critical offshore infrastructure against evolving cyber threats. This study advocates for industry-wide adoption of integrated cyber-resilient architectures and calls for further research into leveraging artificial intelligence and machine learning to enhance adaptive security capabilities in offshore oil and gas operations.