Petroleum Engineering and Data Management: Best Practices for Integration and Optimizing Seismic Data for Enhanced Exploration and Production

Effective integration of petroleum engineering workflows with robust data management practices is essential for maximizing the value of seismic data in both exploration and production phases. This review synthesizes current best practices for data governance, storage architectures, and collaborative platforms that enable seamless access to high-fidelity seismic volumes. We examine advanced techniques for optimizing seismic acquisition parameters, processing algorithms, and attribute extraction to enhance reservoir characterization and drill planning. Emphasis is placed on scalable data pipelines, cloud-native infrastructures, and machine-learning–driven analytics that accelerate decision-making while ensuring data integrity and reproducibility. Through a series of industry case studies, we highlight how integrated engineering–data ecosystems have improved exploration success rates, reduced nonproductive time, and boosted hydrocarbon recovery. Finally, we discuss emerging trends—such as digital twins, real-time data streaming, and AI-augmented interpretation—and propose a roadmap for future research that bridges the gap between unconventional reservoir challenges and next-generation data management solutions.