Source rocks (shales) exhibit different geometric pore types and considerable anisotropy caused by the preferential orientation of the clay and kerogen layers, which is not accounted for in classical rock-physics models. Pore geometry can be effectively studied through the aspect ratio, and in this study, we use the aspect ratio to characterize different pore geometries. Then, we consider a pore connectivity index as well as a lamination index associated with these orientations. An inclusion-based theory (differential effective medium and self-consistent approximation) and the Brown-Korringa equations are used in the modeling approach. The results show that the indices as well as the aspect ratio of the connected pores significantly affect the elastic properties. We propose an inversion method to invert these three parameters simultaneously from experimental vertical P- and S-wave velocities using a global optimization algorithm. The method is applied to well log and seismic data from the Longmaxi shale reservoir in southwest China to verify its predictive ability.
A modeling-inversion methodology for source rocks based on clay-kerogen lamination and pore geometry
Carcione J.;
2025-01-01
Abstract
Source rocks (shales) exhibit different geometric pore types and considerable anisotropy caused by the preferential orientation of the clay and kerogen layers, which is not accounted for in classical rock-physics models. Pore geometry can be effectively studied through the aspect ratio, and in this study, we use the aspect ratio to characterize different pore geometries. Then, we consider a pore connectivity index as well as a lamination index associated with these orientations. An inclusion-based theory (differential effective medium and self-consistent approximation) and the Brown-Korringa equations are used in the modeling approach. The results show that the indices as well as the aspect ratio of the connected pores significantly affect the elastic properties. We propose an inversion method to invert these three parameters simultaneously from experimental vertical P- and S-wave velocities using a global optimization algorithm. The method is applied to well log and seismic data from the Longmaxi shale reservoir in southwest China to verify its predictive ability.| File | Dimensione | Formato | |
|---|---|---|---|
|
1-s2.0-S1995822625002328-main.pdf
accesso aperto
Tipologia:
Versione Editoriale (PDF)
Licenza:
Creative commons
Dimensione
8.46 MB
Formato
Adobe PDF
|
8.46 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


