Preprints
https://doi.org/10.5194/egusphere-2024-2483
https://doi.org/10.5194/egusphere-2024-2483
16 Oct 2024
 | 16 Oct 2024

Elastic anisotropy differentiation of thin shale beds and fractures using a novel hybrid rock physics model

Haoyuan Li, Xuri Huang, Limin Sa, Lei Li, Fang Li, and Tiansheng Chen

Abstract. Elastic anisotropy is frequently used to characterize fracture distribution. However, sets of parallel fractures and thin shale beds in tight sand both can cause elastic anisotropy. Here, we are not referring to shale layers on the logging scale but rather to very thin shale beds, a few centimeters thick, within tight sand. To accurately differentiate the anisotropy caused by fractures or thin shale beds, we propose a hybrid rock physics model. This new model combines the Hudson model and the shale compacting Orientation Distribution Function (ODF) model, based on the anisotropic Self-Consistent Approximation and Differential Effective Medium (SCA&DEM) theory. The new model’s reliability is demonstrated by comparing to the well logs. The proposed model can characterize the elastic properties of both thin shale beds and fractures. Based on this model, the rock physical analysis reveals that thin shale beds and fractures exhibit distinct elastic anisotropy characteristics. Furthermore, we analyse the seismic response differences between fractures and thin shale beds using the anisotropic Ruger’s approximation formula. The analysis indicates that tight sand containing thin shale beds interfere with the identification of some fractured tight sand. On the other hand, there are identifiable differences between the fractured tight sand that can form fractured reservoirs and the tight sand containing thin shale beds. Based on this difference, we develop a new seismic attribute to characterize the fracture distribution. These difference-based attributes can effectively eliminate the interference from thin shale beds, making the distribution of fractures more apparent.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Haoyuan Li, Xuri Huang, Limin Sa, Lei Li, Fang Li, and Tiansheng Chen

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-2483', Anonymous Referee #1, 17 Nov 2024
    • AC1: 'Reply on RC1', Li Haoyuan, 20 Nov 2024
      • RC2: 'Reply on AC1', Anonymous Referee #1, 22 Nov 2024
        • AC3: 'Reply on RC2', Li Haoyuan, 27 Nov 2024
          • RC3: 'Reply on AC3', Anonymous Referee #1, 01 Dec 2024
            • AC4: 'Reply on RC3', Li Haoyuan, 10 Dec 2024
    • AC2: 'Reply on RC1', Li Haoyuan, 20 Nov 2024
      • RC4: 'Reply on AC2', Anonymous Referee #1, 12 Dec 2024
        • AC5: 'Reply on RC4', Li Haoyuan, 12 Dec 2024
          • RC5: 'Reply on AC5', Anonymous Referee #1, 15 Dec 2024
            • AC7: 'Reply on RC5', Li Haoyuan, 15 Dec 2024
        • AC6: 'Reply on RC4', Li Haoyuan, 12 Dec 2024
  • RC6: 'Comment on egusphere-2024-2483', Anonymous Referee #2, 17 Dec 2024
    • AC8: 'Reply on RC6', Li Haoyuan, 17 Dec 2024
Haoyuan Li, Xuri Huang, Limin Sa, Lei Li, Fang Li, and Tiansheng Chen
Haoyuan Li, Xuri Huang, Limin Sa, Lei Li, Fang Li, and Tiansheng Chen

Viewed

Total article views: 375 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
237 118 20 375 3 6
  • HTML: 237
  • PDF: 118
  • XML: 20
  • Total: 375
  • BibTeX: 3
  • EndNote: 6
Views and downloads (calculated since 16 Oct 2024)
Cumulative views and downloads (calculated since 16 Oct 2024)

Viewed (geographical distribution)

Total article views: 364 (including HTML, PDF, and XML) Thereof 364 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 Dec 2024
Download
Short summary
Our research aims to accurately differentiate the elastic properties of tight sands with thin shale beds and fractures. Traditional models struggle to distinguish between these two features. We developed a hybrid rock physics model. Our model's reliability is validated against well log data, revealing distinct anisotropic characteristics for thin shale beds and fractures. This model helps identify fractures more accurately, improving geophysical exploration.