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Bulletin of Chinese Academy of Sciences (Chinese Version)

Keywords

deep Earth science, multi-sphere interactions, artificial intelligence, research paradigm, resource exploration, deep underground engineering, Earth-Moon system

Abstract

Deep Earth science is central to understanding Earth’s internal architecture and the coupled evolution of its major spheres, while also underpinning energy security, the supply of critical mineral resources, and resilience to major geohazards. Nevertheless, the advancement of deep Earth science is currently hindered by insufficient in situ observations under extreme conditions, the difficulty of integrating multi-source heterogeneous data, and the limited capability to model complex multiphysics coupling processes. Recent advances in artificial intelligence offer a potential route beyond these limitations. By integrating data-driven learning with physical and geological understanding, AI is reshaping deep Earth science from empirical interpretation to intelligent discovery, and from local analysis to system-level inference. This emerging paradigm is accelerating the development of a comprehensive full-chain system spanning sensing, modelling, prediction, decision-making, and control. This study systematically examines the paradigm shift and technological foundations of AI-enabled deep Earth science, assesses global research trends, and highlights emerging opportunities in deep resource exploration and development, deep underground engineering, deep geohazard monitoring and early warning, and Earth-Moon exploration. We further outline strategic priorities for future development across deep Earth exploration data infrastructure, foundational theory, enabling technologies and instrumentation, application platforms, and implementation mechanisms. Together, these perspectives provide a framework for advancing deep Earth science in the era of AI.

First page

1193

Last Page

1205

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

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