Work

Research on Natural Gas Hydrate Particle Size Prediction Model Based on DCSMHyK-PBM

Year: 2026
Type: article
Abstract: Agglomeration of gas hydrate particles inside deepwater multiphase oil-and-gas flowlines can readily induce pipeline plugging, threatening the safe and efficient transportation of offshore energy resources. Accurate prediction of the dynamic evolution of hydrate particle size is crucial for assessing flow safety risks and formulating hydrate management strategies. The cohesive force in the CSMHyK model uses only subcooling as the input variable and lacks a temporal evolution mechanism, resulting in limited dynamic prediction accuracy. Addressing these limitations, this paper proposes a DCSMHyK-PBM coupling model. First, the Derjaguin microscopic liquid-bridge adhesion mechanism is introduced to replace the empirical subcooling-based cohesion formula, realizing the physical closure of inter-particle cohesion force through interfacial properties and particle radius. Second, the population balance model (PBM) with time-dependent partial differential equations is adopted to replace the original steady-state equilibrium algebraic particle-size formula, enabling dynamic output of particle size distribution and average agglomerate size over time. Finally, the model is designed to be compatible with an industrial transient multiphase flow framework through a time-stepping iteration logic. Validation against FBRM in situ measured chord length distribution data shows that the predicted CLD curves are consistent with experimental trends across six representative time points (four calibration and two independent validation), with an overall mean absolute relative deviation (MARD) of 8.68%, demonstrating that the improved model provides reasonable dynamic prediction of hydrate particle size evolution, contributing to safe and efficient offshore energy production and flow assurance in deepwater oil-and-gas transportation systems.
Source: Energies
Language: English
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W7225193453
FWCI:
Cites: 36
Cited by:
Related to: 10