Blockchain technology, characterized by its immutability and decentralization, enables the creation of permanent and tamper-resistant records once data are uploaded, making it widely applicable in scenarios requiring data authenticity and reliability. However, the immutability of on-chain data poses significant security risks, as erroneous or illegal data become difficult to correct or remove once recorded. Editable blockchain technology offers a potential solution for on-chain data modification. Nevertheless, existing approaches face several challenges, including the impact of malicious nodes on the security and efficiency of data modification, excessive centralization in the management of modification rights and trapdoor keys, and cumulative issues in reputation-based traditional node grouping methods. To address these challenges, this study proposes an RE-TNG (Reputation Evaluation-Twice Node Grouping) node selection method and an editable blockchain scheme based on it. The RE-TNG method employs a two-stage grouping process following reputation-based node ranking. The first grouping stage uses a Fibonacci sequence-based rule to mitigate the issue of cumulative reputation values over time. The second grouping stage selects high-reputation nodes within groups to ensure the trustworthiness of selected nodes. Trapdoor keys are collaboratively generated by the high-reputation node group, achieving decentralized trapdoor management. Modification nodes are randomly chosen from the high-reputation group, ensuring both integrity and decentralization in modification authority. Comparative analyses and experimental evaluations against traditional random node selection and grouping methods demonstrate the feasibility of the proposed scheme, showcasing a superior performance in terms of security and modification efficiency.