Abstract

The one of the factors limiting production of gas-water is affected by sediments' permeability. Evaluating the normalized permeability (Kn) of sediments containing hydrates is necessary for analyzing the saturation (decomposition level) and flow capacity. The mistakes in Kn prediction are frequently brought about by the assumption such as homogenous particles distribution and ignoring microscopic pore structure. To address the issue, a fractal-based nonempirical prediction model of Kn was developed by modeling, parameter acquisition using SEM and Analyzer, experiment validation, error comparison with published data, and sensitivity analysis for evolution, respectively. Assuming that sediment skeleton particles were misaligned spherical particles of equal diameter. The heterogeneity of sediments was described by the vertical and horizontal distance ratio (m) and offset angle (θ) of the particles. This led to a novel approach for determining average tortuosity (τav,0) and tortuosity fractal dimension (Dτ,0). The viability of the model was confirmed by permeability measurement experiments. Additionally, using the measuring function of SEM, the maximum pore diameter of sediments was obtained. Furthermore, a comparison with earlier data demonstrated the effect. Considering heterogeneity, the average accuracy of Geometric Mean Variance in Kn has increased to 9.66%. Finally, each parameter's impact on prediction was examined. At m = 1.357, Dτ,0 grows symmetrically. Kn,GC varies 15 times more with an increase in Dτ,0 than Kn,PF. All findings indicate that the new model is more likely to be forecasted Kn for a variety of systems, including clayey-silt, sand, and silty-sand system, and especially in reflecting the heterogeneity.

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