Point-Based Approaches for Automated Detection of Facies, Strata and Fractures from DOM (Digital Outcrop Models).
Sophie Viseur. ( 2009 )
in: Proc. 29th Gocad Meeting, Nancy
Abstract
Due to its high flexibility and precision, the LIDAR technology is increasingly used for acquiring numerous outcrop geometries that can have very large lateral and vertical extensions. Once acquired, these data collections must be processed in order to allow the interpretation of facies, fractures or stratigraphic limits. The manual interpretation onto the DOMs is the most used approach. However, it can easily become a time consuming process because of the huge size of the numerical data set and the plausible multi-scaled information to extract. It is then of paramount importance to develop efficient automated interpretation methods in order to deeply explore the acquired LIDAR data. In this context, we propose algorithms to help geologists to interpret in a semi-automated way sedimentary structures and fractures directly from LIDAR data points. Working directly on the data points have the benefit to avoid the building of triangulated surfaces which may be time consuming and often leads to point decimation. The presented point-based algorithms use techniques stemming from image processing. They locally or globally extract geological features from the outcrop geometry but also from other attributes such as colours and intensity. These approaches have been tested on real case studies and results will be shown.
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BibTeX Reference
@inproceedings{ViseurGM2009, abstract = { Due to its high flexibility and precision, the LIDAR technology is increasingly used for acquiring numerous outcrop geometries that can have very large lateral and vertical extensions. Once acquired, these data collections must be processed in order to allow the interpretation of facies, fractures or stratigraphic limits. The manual interpretation onto the DOMs is the most used approach. However, it can easily become a time consuming process because of the huge size of the numerical data set and the plausible multi-scaled information to extract. It is then of paramount importance to develop efficient automated interpretation methods in order to deeply explore the acquired LIDAR data. In this context, we propose algorithms to help geologists to interpret in a semi-automated way sedimentary structures and fractures directly from LIDAR data points. Working directly on the data points have the benefit to avoid the building of triangulated surfaces which may be time consuming and often leads to point decimation. The presented point-based algorithms use techniques stemming from image processing. They locally or globally extract geological features from the outcrop geometry but also from other attributes such as colours and intensity. These approaches have been tested on real case studies and results will be shown. }, author = { Viseur, Sophie }, booktitle = { Proc. 29th Gocad Meeting, Nancy }, title = { Point-Based Approaches for Automated Detection of Facies, Strata and Fractures from DOM (Digital Outcrop Models). }, year = { 2009 } }