EGU2020-18665, updated on 19 Jan 2021
https://doi.org/10.5194/egusphere-egu2020-18665
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Guiding Naturally Occurring Asbestos rock sampling using digital outcrops and geological reasoning

Thomas J.B. Dewez1, Didier Lahondère1, Tobias H. Kurz2, Marcel Naumann, Nicole Naumann3, Laure Capar1, Florence Cagnard1, and Simon J. Buckley3
Thomas J.B. Dewez et al.
  • 1BRGM, Orleans, France (t.dewez@brgm.fr)
  • 2NGU, Trondheim, Norway
  • 3NORCE Norwegian Research Centre, Bergen, Norway

Retrograde metamorphism corresponds to the metamorphic processes that occur during orogenic uplift (diminishing temperatures) and cooling (lowering temperatures). These pressure and temperature conditions induce fracturing and fluids circulation which may prompt the crystallization of fibrous actinolite and tremolite within magnesium-iron rich rocks. Such fibrous amphiboles may result from the destabilization of earlier minerals (magmatic or metamorphic pyroxenes and/or amphiboles). In all cases, fibrous occurrences concern discrete locations and limited extents in space. These Naturally Occurring Asbestos minerals only form along fracture planes (in slip-vein mode) or within open veins (cross-vein mode). That is in the space where fluids circulated. Actinolite and tremolite minerals also crystalize inside mafic rock matrix, though not under their asbestiform habitus. Altering fluids diffuse from vein walls into the rock and actinolite and tremolite substitute themselves to destabilized pyroxenes and amphiboles of the matrix. This deliberately simplified geological logic may be used  to predict the location of Naturally Occurring Asbestos (NOA) on different rock outcrops.

We contend that 3D digital outcrop models commonly acquired by photogrammetry (ground- or UAV-based) alone or together with lidar, are efficient supports to map NOA presence susceptibility using this conceptual model. The rock assemblage architecture is best interpreted either in 3D, on a photorealistic textured meshed model itself, or on 2D orthophotos projected on a vertical plane. Geometric processing of dense (centimeter-resolution) 3D point clouds enables identifying host structures (fractures, faults and layer contacts) in the outcrop relief. Already, with these information supported by field observations, a first model may be produced for most likely NOA sites on the outcrop. If hyperspectral imaging in the shortwave infra-red (1300-2500 nm) spectral range, constrained by point-based field spectrometer acquisition, is added to the pool of available data sets, diffuse alteration rings of the mafic rock matrix may be imaged and included to the presence susceptibility model. Amphibole mineralogy provides diagnostic spectral properties due to hydroxyl absorption and can be therefore identified and mapped by hyperspectral imaging in the outcrop.

This theoretical approach to mapping NOA presence susceptibility is demonstrated on examples from Norway and France. Ground-based photogrammetric survey replicates the geometry and colour of the outcrop with a dense point cloud spacing of 1pt/15-20 mm and a photorealistic textured meshed model. Lithological architecture and structural interpretation were performed manually using LIME software (virtualoutcrop.com). Geometric fracture mapping was undertaken using CloudCompare (cloudcompare.org) with the Compass and Facets plugins. Both lithological and structural information were brought together on a 2D NOA presence susceptibility map using Geographic Information System. This output, validated in the field, guides rock sample collection for laboratory analysis and objectivates their spatial representatitivity for NOA presence susceptibility reports.

How to cite: Dewez, T. J. B., Lahondère, D., Kurz, T. H., Naumann, M., Naumann, N., Capar, L., Cagnard, F., and Buckley, S. J.: Guiding Naturally Occurring Asbestos rock sampling using digital outcrops and geological reasoning , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18665, https://doi.org/10.5194/egusphere-egu2020-18665, 2020