New Hybrid Method for Gas-Hydrate Digital Rock Reconstruction and Its Accuracy Evaluation
Publication: Journal of Energy Engineering
Volume 147, Issue 6
Abstract
Analyzing the petrophysical properties of gas hydrate reservoirs under different conditions by experimental methods is time-consuming, costly, and very difficult. Therefore, it is of great practical significance to accurately reconstruct gas hydrate digital rocks using numerical simulation methods. In this study, based on in situ observations of gas hydrate pore habits and variation laws in the laboratory, a hybrid method was adopted to simulate pore-scale spatial distribution characteristics of gas hydrate using a digital rock model. The hybrid method combined classical nucleation theory, the diffusion-limited aggregation model, and the cluster-cluster aggregation model. Then, the pore size distribution, local porosity distribution, and average seepage probability distribution of gas hydrate digital rock and gas hydrate–bearing sediments were calculated and compared. In addition, the finite-element method was used to simulate and compare the reconstructed digital rock’s resistivity index and elastic modulus. The results showed that the hybrid method can effectively simulate the spatial distribution characteristics and variation laws of gas hydrate on the pore scale. In addition, the resistivity index and elastic modulus of the reconstructed gas hydrate digital rock were relatively close to those of gas hydrate–bearing sediments. However, compared with gas hydrate–bearing sediments, the average pore size of the reconstructed gas hydrate digital rock was smaller, and the pore connectivity showed a slight amount of difference. In summary, this investigation was of great significance in systematically studying the petrophysical properties of gas hydrate reservoirs.
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Data Availability Statement
All data that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 41874138).
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Received: Mar 30, 2021
Accepted: Jul 13, 2021
Published online: Sep 28, 2021
Published in print: Dec 1, 2021
Discussion open until: Feb 28, 2022
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