1887

Abstract

Summary

Rock permeability is an essential factor controlling hydrocarbon production and traditionally estimated from empirical porosity-permeability relation. However, because of the complexity of pore geometry, permeability may not be adequately captured with sole porosity. This study presents a new methodology for predicting rock permeability from 2D thin sections. Without 3D reconstruction, our method extracts parameters related to pore geometry and pore network from thin sections using Watershed Segmentation. The extracted parameters are specific surface area, pore size, pore throat width, pore throat length, and pore coordination number. Then, five permeability models are regressed from 48 sandstone samples using different input parameter sets. The results show that combining all parameters into the model could significantly improve permeability prediction from 65.2% to 89.0% R2, compared to the conventional method. Our finding asserts that the arrangement of pore space could be practically quantified from thin sections, and such pore-geometry insight plays a significant role in permeability prediction.

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.202310308
2023-06-05
2026-02-10

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References

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/content/papers/10.3997/2214-4609.202310308
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Permeability prediction using specific surface area and pore network parameters extracted from thin sections
Conference Proceedings 2023, 1 (2023); https://doi.org/10.3997/2214-4609.202310308
/content/papers/10.3997/2214-4609.202310308
/content/papers/10.3997/2214-4609.202310308
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