European Geologist Journal 51

Deepening an old, verticalised pit: rock slope instability hazard assessment using a digitally augmented structural database (Flône limestone quarry, Belgium)

 

by E. C. Frets (1*), A. Gauffriau (1), N. Coussaert (1) and J. Vanneste (2)

1 Tractebel Engie, Boulevard Simón Bolívar 34-36, 1000 Brussels, Belgium
2 Lhoist Western Europe, Rue Granbonpré 11, 1435 Corbais, Belgium

Contact: erwin.frets@tractebel.engie.com

Abstract

We present a rock slope instability hazard study of the Flône pit (Belgium) by means of a deterministic kinematic stability analysis. The specificity of this study resides in the “digital augmentation” of the field mapping structural database (x 5) by semi-automatic point cloud analysis. Results show that the main instability hazards in the actual pit are flexural toppling and, to a lesser extent, wedge sliding. Planar sliding, although minor, will constitute a significant hazard for interbench rupture during future excavation due to the presence of an anticline structure at depth. The augmented ― and georeferenced ― structural database has enabled us to generate a synthetic rock slope instability hazard map that constitutes the basis for the recommendation of targeted monitoring solutions during future excavation works.

Cite as: Frets, E. C., Gauffriau, A., Coussaert, N., & Vanneste, J. (2021). Deepening an old, verticalised pit: rock slope instability hazard assessment using a digitally augmented structural database (Flône limestone quarry, Belgium). European Geologist, 51. http://doi.org/10.5281/zenodo.4954423

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Introduction

With increasing environmental awareness, optimising the extraction of readily available resources ― prior to searching for new ones ― is key to ensure future sustainable extraction activities. Nonetheless, optimising resources by deepening a pit and/or verticalising its fronts goes along with increased instability hazard and may endanger the personnel working at a given site.

Lhoist Group plans to optimise the exploitation of the Hermalle site pure limestone resource. The Hermalle quarry is located in a very narrow and steep location at the border of the Meuse River in Belgium (Figure 1).

Figure 1: Context of the Flône pit (orange), object of the present instability hazard assessment study by means of a digitally augmented structural database.

It is a 2.5 km long, 300 m large elongated pit whose westernmost part (the “Flône” pit) has not been exploited since 2007. Since then, the 3 upper benches have been already set in their “final” position (i.e. 20 m vertical each, with 5 m interbench distance – Figure 2), making it inaccessible for geological-structural mapping. Although no major instability hazard has occurred since this time, it was imperative for security reasons to:

  • assess the instability hazard in such narrow and steep conditions,
  • gain a view of the resource at depth, prior to restarting extraction activities in the Flône pit.

Figure 2: Flône actual pit geometry (grey) and deepening project (orange).

Although geological interpretation of “virtual outcrops” has been successfully tested to map inaccessible areas such as cliffs (e.g. Xu et al., 2001, Trinks et al., 2005) or caves (Triantaphyllou et al., 2019) or for detailed structural mapping at outcrop scale (Martin et al., 2019), to our knowledge only few studies (Smith & Holden, 2020) have attempted to integrate a deterministic kinematic stability analysis into such mapping. In addition to this, here we also link this kinematic stability analysis with hazard mapping of the quarry.

Geological context

The Hermalle quarry exploits Visean limestones and dolomites along the Midi-Eifel thrust zone, the Belgian part of the Variscan Front Thrust that delimits the European Variscides to the south, with the Caledonian basement to the north. The exploited rocks pertain to the lower to middle Visean Terwagne, Lives and Neffe formations. Below and above these formations occur the Tournaisian dolomites of the Engihoul formation and the Namurian shales of the Chokier formation, respectively. This folded sedimentary succession crops out in the quarry as steeply S-dipping strata with normal stratigraphic polarity, or steeply N-dipping with reverse polarity in the south and the north of the pit, respectively. The northern front also shows a tight, upright fold, with an axial surface dipping towards the pit (see also cross-section of Figure 5, section 4).

Methodology

Digitally augmented structural database

The high-density point cloud has been constructed by merging a fix station laser scanning acquisition from the base of the pit with an aerial (drone) photogrammetric survey. This dual acquisition has allowed us to increase and homogenise point density, especially in scanning dead angles for geological and geotechnical study purposes.

Our structural database, based on:

  • Field mapping: 157 DGPS stations, 211 planes – S0, S1, fractures, faults – and 24 lines – slickensides, fold axes, and
  • Archive integration: Lhoist pit photographs and structural database,

has then been digitally ‘augmented’ by semi-automatic, point-cloud based picking of ~1000 plane orientations using CloudCompare software (Figure 3).

The georeferenced point cloud not only allows us to retrieve data from inaccessible areas such as each of the three 20 m high, verticalised fronts of the Flône pit, but also enables us to refine the geological model and perform targeted detailed kinematic slope stability analyses, precisely locating the subsets of problematic structures directly in GIS. Remote data measurement is reliable, efficient and a powerful methodology for both geological and geotechnical studies.

Figure 3: 3D point cloud geological limits picking and results of field & remote structural database.

Interpretative geological cross-sections

In order to evaluate simultaneously the evolution of the limestone resource at depth and the instability hazard during excavation of the future pit, four interpretative cross-sections (see Figure 4 for their location) have been produced, of which two are presented in Figures 5 and 6. These sections allowed discussion of the instability hazard to be integrated with the future design of the pit and hence served as a basis for making recommendations for monitoring and additional investigations, as well as general recommendations regarding future excavation works.

Figure 4: Structural map showing Tectonic Units UT-1 to UT-4, and location of the cross-sections presented in Figures 5 and 6.

Rock slope kinematic stability analysis

Three rock slope instability hazards have been investigated by means of rock kinematic stability analysis using the Rocscience software suite (Dips 5.0): planar sliding, wedge sliding and flexural toppling. Investigation of general failure mode was not part of this study, considering the overall strong character of the exploited limestones and dolomites as deduced from our field mapping.

For each actual front (south, north, west and east) of the Flône pit, we have computed plane, wedge and flexural toppling kinematic stability analysis based on >1000 planes covering the 4 mapped tectonic units. To perform the kinematic stability analyses based on Markland’s test (Hoek & Bray, 1981), we have considered an average slope dip of the quarry fronts of 75°, a friction angle of 30°, and the georeferenced structural database that enabled detailed instability hazard maps to be produced.

Results

Geological – Structural mapping and cross-sections

Based on our new field structural mapping and augmented structural database, we were able to distinguish four tectonic units in the Flône pit (Figure 4), each characterised by a different degree of deformation: UT-1 is composed by dominant S0/1 planes,  UT-2 is in addition crosscut by one family of high angle (back-)thrust faults, UT-3 shows complex (recumbent) fold geometries and is cut by two or more fracture/fault orientations, and UT-4 corresponds to decameter scale, steeply dipping deformation zones (e.g. inverted flower structures) where S0/1 is no longer visible.

The presence of high angle thrusts and backthrusts crosscutting the S0/1  and recumbent folds and intense shearing affecting the westernmost and easternmost part of the pit was previously unrecognised (Lhoist, 2008), and this new information allowed us to draw a more consistent tectonic interpretation of the Flône pit. The cross-section shown in Figure 5 draws a representative view of the structure across the pit.

Figure 5: Digitally augmented structural cross section with remote structural data (see Figure 4 for cross-section location).

Instability hazard assessment

Rock slope instability hazard of the future pit based on our interpretative cross-sections (Figure 6) and rock kinematic stability analysis (deterministic approach) based on a near comprehensive georeferenced structural database (see Figure 7 for the case of the south front) have shown that the main rock instability hazard in the Flône pit concerns flexural toppling on the north and south fronts (46% and 47% respectively). The east and west fronts, which are dominated by UT-2 and UT-3, only show moderate wedge failure hazard (11%), mainly where S0/1 intersects (back-)thrusts. Planar sliding hazard is generally low (2% to 10%) on all fronts, but our interpretative cross-sections have highlighted that this hazard may significantly increase during future excavations. In particular, on the northern front, deepening of the pit could generate significant inter-bench failure due to the presence of the anticline flank dipping moderately downwards through the future pit (see example cross-section).

Figure 6: Planar sliding hazard along the main anticline flank (see Figure 4 for cross-section location).

Figure 7: Rock kinematic deterministic analysis of the south front: results and GIS mapping of the involved planes.

Discussion

Point cloud based structural data acquisition has enabled augmenting our field mapping database by a factor of 5 in the Flône quarry to re-assess the geological model and support our rock instability hazard assessment. The virtually augmented structural database makes it possible to largely reduce the uncertainty related to the usually poor representativity of structural data at the scale of a quarry where the majority of the outcrop surface is inaccessible. Similar structural data acquisition based on point clouds has been successfully conducted in other inaccessible environments, such as rock slopes (Tiruneh et al. 2013; Bordehore et al., 2017; Tung et al., 2018), caves (Triantaphyllou et al., 2019), road cuttings (Riquelme et al., 2016) or for geological model development (Cawood et al., 2017). However, these works did not integrate deterministic kinematic stability analysis in their assessment. Only very recently, Smith & Holden (2020) provided a similar analysis, but these authors looked at the different mechanisms one by one, without finally integrating or mapping the hazard results. For our study, the georeferenced structural database then enabled us to extract and map the subsets of planes that were prone to failure, providing an integrated instability hazard map necessary for safe extraction activities of the pit.

Whilst this geometric approach is very powerful, it should nevertheless always be complementary to – and not be replaced by – geological/geotechnical field expertise, as instability hazard not only relies on geometric parameters, but also on mechanical parameters that can be estimated directly in the field (e.g. Marinos & Hoek, 2000; Marinos et al., 2005). Our combined geological and geotechnical surface analysis has enabled us to anticipate future hazards in defining a targeted monitoring programme depending on the locations of the instability hazards identified across the pit.

Conclusion

Digitally augmented structural databases based on georeferenced point cloud analyses now enable deterministic rock kinematic stability analysis to be performed even at the scale of a pit with a high degree of confidence due to the enormous amount of robust structural data that can be gathered in an efficient way, but field geological mapping and rock mass characterisation should be integrated to make a consistent stability assessment.

Acknowledgements

We thank two anonymous reviewers for their constructive comments that contributed to improving the manuscript.

References

Bordehore, L., Riquelme, A., Cano, M., & Tomas, R. 2017. Comparing manual and remote sensing field discontinuity collection using in kinematic stability assessment of failed rock slopes. International Journal of Rock Mechanics and Mining Sciences, 97. 24–32

Cawood, A.J., Bond, C.E., Howell, J.A., Butler, R.W.H. & Totake, Y. 2017. LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models. Journal of Structural Geology, 98. 67–82. DOI: 10.1016/j.jsg.2017.04.004

CloudCompare (version 2.11) [GPL software]. (2019). Retrieved from http://www.cloudcompare.org/

Dips 5.0 Rocscience Inc. 1998, Dips Version 5.0 – Graphical and Statistical Analysis of Orientation Data. www.rocscience.com, Toronto, Ontario, Canada.

Hoek, E. & Bray, J.W. 1981. Rock Slope Engineering. The Institute of Mining and Metallurgy, London, England.

Lhoist (2008). Flône quarry revision and extension of the geomodel. Limelette, April 4th 2008 (by Pirotte, N.)

Marinos, P. & Hoek, E. 2000. GSI: a geologically friendly tool for rock mass strength. In: Proceedings GeoEng 2000, International conference on geotechnical and geological engineering, p. 1422-40. Melbourne, Australia, Lancaster, PA: Technomic Publishing Co.

Marinos, V., Marinos, P. & Hoek, E. 2005. The geological strength index: applications and limitations. Bulletin of Engineering Geology and the Environment, 64(1):55-65. DOI: 10.1007/s10064-004-0270-5

Martín, S., Uzkeda, H., Poblet, J. & Bulnes, M.. (2019). Geological interpretation of two virtual outcrops of deformed Palaeozoic rocks (NW Iberian Peninsula) using 3D stereo VDT in a computer assisted virtual environment (CAVE™). Journal of Iberian Geology, 45. 565–584. DOI: 10.1007/s41513-019-00110-2.

Riquelme, A.J., Tomás, R. & Abellán, A. (2016). Characterization of rock slopes through slope mass rating using 3D point clouds. Int J Rock Mech Min Sci 84:165–176

Smith, J. & Holden, L. 2020. Rock slope kinematic instability controlled by large-scale variation of basalt column orientation. Bulletin of Engineering Geology and the Environment, 80. 239–250. DOI: 10.1007/s10064-020-01917-5. 

Tiruneh, H.W., Stetler, L.D, Oberling, Z.A., Morrison, D.R., Connolly, J.L. & Ryan, T.M. 2013. Discontinuity mapping using ground-based LiDAR: case study from an open pit mine. American Rock Mechanics Association, ARMA-2013-663

Triantafyllou, A.,  Watlet, A.,  Le Mouélic, S., Camelbeeck, T., Civet, F., Kaufmann, O., Quinif, Y. & Vandycke, S. 2019. 3-D digital outcrop model for analysis of brittle deformation and lithological mapping (Lorette cave, Belgium). Journal of Structural Geology, 120. 55–66. DOI: 10.1016/j.jsg.2019.01.001.

Trinks, I., Clegg, P., McCaffrey, K., Jones, R., Hobbs, R., Holdsworth, B., Holliman, N., Imber, J., Waggott, S. & Wilson, R. 2005. Mapping and analysing virtual outcrops. Visual Geosciences, 10. 13–19 DOI: 10.1007/s10069-005-0026-9.

Tung, W., Nagendran, S., Mohamad, I. & Mohd, A.. 2018. 3D rock slope data acquisition by photogrammetry approach and extraction of geological planes using FACET plugin in CloudCompare. IOP Conference Series: Earth and Environmental Science. 169. 012051. DOI: 10.1088/1755-1315/169/1/012051. 

Xu, X., Bhattacharya, J., Davies, R. & Aiken, C. 2001. Digital geologic mapping of the Ferron Sandstone, Muddy Creek, Utah, with GPS and reflectorless laser rangefinders. GPS Solutions, 5. 15–23. DOI: 10.1007/PL00012872.

This article has been published in European Geologist Journal 51 – Geotechnics – Building sustainable foundations

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