Fidelity corers play a crucial role in exploring and evaluating deep oil and gas resources. Due to the complexity of the corer parts, an improper assembly sequence can lead to inefficiencies and reduced reliability, impacting the success of obtaining oil and gas samples. This paper presents a novel assembly sequence planning method based on graph theory and multi-objective evaluation. The graph-theoretic cut set algorithm is utilized to generate all possible assembly sequences based on a directed graph which represents corer component assembly information. To address deep oil and gas corer requirements, the interpretative structural modeling method (ISM) is employed to construct a comprehensive stability-reliability-accuracy assurance-easiness-cost economy (SRAEC) indicator system. Through indicators weight assignment and multi-objective evaluation, the optimal solution of assembly sequence is identified from a global perspective. The proposed method is applied to a deep-sea gas hydrate corer, resulting in the identification of the most suitable assembly sequence for both field drilling and laboratory testing. This optimized sequence improves the assembly reliability and efficiency, contributing to the overall success and efficiency of the corer in obtaining oil and gas samples. The study provides valuable insights for designing and practically applying deep oil and gas coring tools.