1887

Abstract

Summary

While the influence of clay smear on the sealing properties of fault zones in siliciclastic rocks can be predicted by validated concepts such as the SGR or CSP reliable models for predicting the structural and hydraulic properties of faults in layered limestone-marl sequences do not yet exist.

The main goal of our study is to analyse the development of fault sealing as a result of marl smearing in interaction with mechanical mixing as well as fracturing and cementation processes in dependence of mechanically alternating bedding and fault geometry. Oriented transfer samples of fault cores from different normal fault systems destabilised by the fault process with adjacent damage zone were successfully extracted from outcrops with Jurassic limestone in a quarry Northern Bavaria, Germany. Microanalytical tools and multiscale (m-nm) analyses workflows were developed to provide ground truth for the training of machine learning algorithms for the efficient interpretation of 2D microstructural image data. The systematic macroscopic and microstructural examination of the transfer specimens has shown that the fault zones are built up by recurrent building blocks, whose variation and expression are strongly influenced by the presence and nature of interbedded marly layers.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202210764
2022-06-06
2024-04-27
Loading full text...

Full text loading...

References

  1. Aubert, I, Léonide, P, Lamarche, J. and Salardon, R. [2020] Diagenetic evolution of fault zones in Urgonian microporous carbonates, impact on reservoir properties (Provence – southeast France). Solid Earth11, 4, 1163–1186.
    [Google Scholar]
  2. Jiang, M., Rößler, C, Wellmann, E., Klaver, J., Kleiner, F. and Schmatz, J. [2021] Workflow for high-resolution phase segmentation of cement clinker from combined BSE image and EDX spectral data. Journal of Microscopy, 1–7.
    [Google Scholar]
  3. Klaver, J., Hemes, S., Houben, M., Desbois, G., Radi, Z. and Urai, J.L. [2015] The connectivity of pore space in mudstones: insights from high pressure Wood’s Metal Injection, BIB-SEM imaging and Mercury Intrusion Porosimetry. Geofluids15, 4, 577–591.
    [Google Scholar]
  4. Klaver, J., Schmatz, J., Wang, R, Jiang, M., Kleipool, L.M., Cilona, A., and Urai, J.L. [2021] Automated Carbonate Reservoir Pore and Fracture Classification by Multiscale Imaging and Deep Learning.” In, 2021:1–5. European Association of Geoscientists & Engineers.
    [Google Scholar]
  5. Kottwitz, M. O., Popov, A. A., Abe, S. and Kaus, B. J. P. [2021] Investigating the effects of intersection flow localization in equivalent-continuum-based upscaling of flow in discrete fracture networks. Solid Earth, 12, 2235–2254.
    [Google Scholar]
  6. Schmatz, J, Klaver, J, Virgo, S, Jiang, M, von Hagke, C., Desbois, G. and Urai, J.L. [2017] Standardized Automated Multiscale Imaging Technologies to Quantify Microstructure and Petrophysical Properties in a Range of Rock Types. 79th EAGE Conference and Exhibition 2017, 2017, 1 – 5.
    [Google Scholar]
  7. Yielding, G., Freeman, B., NeedhamT. [1997] Quantitative fault seal prediction. AAPG Bulletin81, 897–917.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.202210764
Loading
/content/papers/10.3997/2214-4609.202210764
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error