This review evaluates data storage solutions for seismic data, focusing on optimization, security, and scalability.
The growing volume, velocity, and complexity of seismic data generated during global exploration projects have intensified the demand for efficient, scalable, and secure data storage solutions. This review investigates the evolution of seismic data storage technologies, including traditional hardware systems, cloud-based architectures, and distributed storage frameworks. It evaluates state-of-the-art optimization techniques such as AI-driven metadata indexing, compression, and automated workflow management that ensure real-time data access and cost-efficiency. Furthermore, the study explores critical security measures such as encryption, blockchain traceability, and zero-trust frameworks, as well as challenges surrounding regulatory compliance and cross-border data governance. Special attention is given to scalability strategies that accommodate the expanding data requirements of multinational exploration projects, including hybrid storage models, edge integration, and energy-efficient infrastructure. This paper concludes with a synthesis of key findings and recommendations for adopting future-proof storage architectures to enhance seismic data accessibility, integrity, and sustainability.
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Umoren et al. (2024) studied this question.
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