Sampling Technique Biases and their Effect on Discrete Fracture Networks Generation for Underground Works using LiDAR Scanning

I Vazaios

In the proceedings of: GeoVancouver 2016: 69th Canadian Geotechnical Conference

Session: FUNDAMENTALS - II Engineering Geology & Geomorphology

ABSTRACT: Structural mapping is a key element that provides valuable data such as discontinuity orientation, density, persistence, fracture trace length etc. which serve as input to the geometrical modelling of a rockmass. However, in an active underground environment, traditional joint survey techniques, and more specifically, structural mapping of the tunnel walls, may become difficult. LiDAR scanning in an operational underground environment can be proven to be more efficient, as the required collection data time and impediment to the construction is minimized as processing of the structural rockmass e biases due to the inherent limitations of the sampling techniques employed. This affects the discontinuity data which is then used as input to the geometrical modelling of the fracture network (such as the use of Discrete Fracture Networks (DFNs)), which underground project. This paper will focus on the procedures associated with utilizing LiDAR data in order to aid in the characterization of the rockmasses past the face of tunnelling projects. The workflow and results will be discussed utilizing data sets obtained from a tunneling project in Norway.

RÉSUMÉ: La cartographie structurale est un élément clé qui fournit des données précieuses telles que re techniques de relevés on de la rapidité de la collecte des données qui diminue les entraves aux opérations. La collecte de données est rapide puisque le traitement des données de la masse rocheuse peut être effectué ultérieurement. De plus, semblable à la cartographie conventionnelle, la cartographie virtuelle est soumise aux mêmes inconvénients en raison des limites inhérentes aux dans la modélisation géométarticle porte sur les procédures assocr de tunnel en Norvège. KEYWORDS: DFN, LiDAR, Underground Projects, Sampling Biases

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Cite this article:
I Vazaios (2016) Sampling Technique Biases and their Effect on Discrete Fracture Networks Generation for Underground Works using LiDAR Scanning in GEO2016. Ottawa, Ontario: Canadian Geotechnical Society.

@article{3692_0717100558,author = I Vazaios,title = Sampling Technique Biases and their Effect on Discrete Fracture Networks Generation for Underground Works using LiDAR Scanning,year = 2016}