Development of natural gas hydrates: A comprehensive review with focus on numerical simulation

Natural gas hydrates are a promising alternative energy resource, but their development presents complex challenges due to multi-field coupling involving thermal, hydraulic, mechanical, and chemical interactions. Numerical simulations offer critical solutions for addressing these challenges, enabling multiscale analysis and production strategy optimization. This review aims to evaluate the role and evolution of numerical simulation in natural gas hydrate development, addressing key challenges such as reservoir heterogeneity, phase complexity, and geomechanical risks. A systematic review of current simulation approaches was conducted, including custom-built, research-oriented, and commercial model-driven simulators. Traditional model-driven simulations, dependent on governing equations and parameter precision, often struggle to capture the nonlinear responses and dynamic behavior of complex reservoirs. With the accumulation of experimental observations, field trial data, and advancements in machine learning, data-driven models have emerged, offering predictive frameworks capable of modeling heterogeneity and multi-field coupling processes. While physical mechanism modeling remains the cornerstone of numerical simulation, data-driven models enhance predictive accuracy and generalizability. This review establishes a multidimensional assessment framework that encompasses phase behavior, thermodynamic versus kinetic representations, fidelity of multi-field coupling, numerical and parallelization strategies, geological representativeness, and levels of experimental or field validation. It also incorporates emerging hybrid paradigms that integrate model-driven simulators with data-driven models, and includes direct comparisons of field-scale simulation outcomes. These contributions collectively advance the systematic evaluation of natural gas hydrate simulation approaches and inform a clear pathway forward: future models must overcome current limitations by integrating data-driven models with multiscale coupled physics and by establishing open, collaborative numerical simulation frameworks to enable efficient, safe, and scalable resource development.