This paper used 1526 works from the literature on disaster risk perception from 2000 to 2020 in the Web of Science core collection database as the research subject. The CiteSpace knowledge graph analysis tool was used to visual analyze the country, author, institution, discipline distribution, keywords, and keyword clustering mapping. The paper drew the following conclusions. Firstly, disaster risk perception research has experienced three stages of steady development, undulating growth, and rapid growth. Secondly, the field of disaster risk perception was mainly concentrated in the disciplines of engineering, natural science, and management science. Thirdly, meteorological disasters, earthquakes, nuclear radiation, and epidemics were the main disasters in the field of disaster risk perception. Residents and adolescents were the main subjects of research in the field of disaster risk perception. Fourthly, research on human risk behavior and risk psychology and research on disaster risk control and emergency management were two major research hotspots in the field of disaster risk perception. Finally, the research field of disaster risk perception is constantly expanding. There is a trend from theory to application and multi-perspective combination, and future research on disaster risk perception will be presented more systematically. The conclusion can provide a reference for disaster risk perception research, as well as directions for future research.

CO₂ Geological Storage Leakage (CGSL) poses significant risks to environmental safety and the sustainability of Carbon Capture, Utilization, and Storage (CCUS) projects. While Fault Tree Analysis (FTA) and the Risk Matrix are established risk assessment tools, their combined application to CGSL remains underexplored, particularly in providing a structured, semi-quantitative framework for risk prioritization. This study addresses this gap by developing an integrated FTA-Risk Matrix methodology specifically tailored for CGSL. Firstly, an Analytic Hierarchy Process (AHP) was employed to establish and optimize a comprehensive risk assessment index system, resulting in 17 key indicators derived from expert questionnaires. Subsequently, a fault tree model for CGSL was constructed, identifying 14 basic risk events. By integrating the risk matrix, these factors were quantitatively assessed based on their probability and severity, enabling clear risk classification and the identification of critical vulnerable points. The practical application of this framework to the Jingbian CCUS project in the Ordos Basin demonstrates its efficacy, revealing legacy wells and fault activation as high-risk factors. This research provides a systematic and transferable tool for enterprises to conduct hierarchical risk management and offers a critical reference for enhancing the safety protocols of CCUS projects.