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Blockchain technology has experienced significant growth across various industries. However, challenges such as scalability, high transaction fees, and resource inefficiencies continue to limit its full potential. This paper presents a novel approach using a multilayer graph to model and analyze blockchain transactions, with a focus on resource consumption—specifically opcode execution and gas usage. By categorizing accounts into distinct layers—Externally Owned Accounts (EOAs), smart contracts, oracles, and cross-chain bridges—the graph-based model captures interactions across these account types. Through transaction trace analysis, we extract opcode usage and gas consumption, applying graph-theoretical metrics such as node scoring and edge weighting to identify critical nodes and resource-intensive transactions. Our findings provide new insights into resource-heavy behaviors, revealing optimization opportunities to reduce transaction costs and improve scalability. Additionally, the approach aids in anomaly detection and smart contract optimization, enhancing the cost-effectiveness and performance of blockchain systems.