Spectral Pattern Classification in Lidar Data for Rock Identification in Outcrops

The present study aimed to develop and implement a method for detection and classification of spectral signatures in point clouds obtained from terrestrial laser scanner in order to identify the presence of different rocks in outcrops and to generate a digital outcrop model. To achieve this objective, a software based on cluster analysis was created, named K-Clouds. This software was developed through a partnership between UNISINOS and the company V3D. This tool was designed to begin with an analysis and interpretation of a histogram from a point cloud of the outcrop and subsequently indication of a number of classes provided by the user, to process the intensity return values. This classified information can then be interpreted by geologists, to provide a better understanding and identification from the existing rocks in the outcrop. Beyond the detection of different rocks, this work was able to detect small changes in the physical-chemical characteristics of the rocks, as they were caused by weathering or compositional changes.

[1]  Jamie K. Pringle,et al.  3D high-resolution digital models of outcrop analogue study sites to constrain reservoir model uncertainty: an example from Alport Castles, Derbyshire, UK , 2004, Petroleum Geoscience.

[2]  J. I. San José Alonso,et al.  COMPARING TIME-OF-FLIGHT AND PHASE-SHIFT. THE SURVEY OF THE ROYAL PANTHEON IN THE BASILICA OF SAN ISIDORO (LEÓN) , 2012 .

[3]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[4]  David Hodgetts,et al.  Integration of digital outcrop models (DOMs) and high resolution sedimentology – workflow and implications for geological modelling: Oukaimeden Sandstone Formation, High Atlas (Morocco) , 2010 .

[5]  Mohammed Alfarhan,et al.  Laser rangefinders and ArcGIS combined with three-dimensional photorealistic modeling for mapping outcrops in the Slick Hills, Oklahoma , 2008 .

[6]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[7]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[8]  David D. Pollard,et al.  Digital mapping of three-dimensional structures of the Chimney Rock fault system, central Utah , 2001 .

[9]  X. Janson,et al.  Improving fractured carbonate-reservoir characterization with remote sensing of beds, fractures, and vugs , 2009 .

[10]  David Healy,et al.  Calibration and validation of reservoir models: the importance of high resolution, quantitative outcrop analogues , 2008 .

[11]  C. Kerans,et al.  Architectural Characterization and Three-Dimensional Modeling of a Carbonate Channel–Levee Complex: Permian San Andres Formation, Last Chance Canyon, New Mexico, U.S.A. , 2007 .

[12]  K. Verwer,et al.  Evolution of a High-Relief Carbonate Platform Slope Using 3D Digital Outcrop Models: Lower Jurassic Djebel Bou Dahar, High Atlas, Morocco , 2009 .

[13]  K. McCaffrey,et al.  Visualization of folding in marble outcrops, Connemara, western Ireland: An application of virtual outcrop technology , 2008 .

[14]  Charles Kerans,et al.  Three-dimensional geological and synthetic seismic model of Early Permian redeposited basinal carbonate deposits, Victorio Canyon, west Texas , 2007 .

[15]  Boris Mirkin,et al.  Mathematical Classification and Clustering , 1996 .

[16]  David Hunt,et al.  Virtual fieldtrips for petroleum geoscientists , 2010 .

[17]  A. Nagalli,et al.  Método para aplicação de escâner a laser terrestre ao estudo da estabilidade de taludes em rocha , 2011 .

[18]  T. Good,et al.  Photogeological and image-analysis techniques for collection of large-scale outcrop data , 1997 .

[19]  J. Howell,et al.  Impact of deltaic clinothems on reservoir performance: Dynamic studies of reservoir analogs from the Ferron Sandstone Member and Panther Tongue, Utah , 2010 .

[20]  Karl T. Bates,et al.  High-resolution LiDAR and photogrammetric survey of the Fumanya dinosaur tracksites (Catalonia): implications for the conservation and interpretation of geological heritage sites , 2008, Journal of the Geological Society.

[21]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[22]  S. Buckley,et al.  Terrestrial laser scanning in geology: data acquisition, processing and accuracy considerations , 2008, Journal of the Geological Society.

[23]  P. Hariharan.  Basics of Interferometry , 2006 .

[24]  Sanjay Ranka,et al.  An effic ient k-means clustering algorithm , 1997 .

[25]  David Hodgetts,et al.  A new approach for outcrop characterization and geostatistical analysis of a low-sinuosity fluvial-dominated succession using digital outcrop models: Upper Triassic Oukaimeden Sandstone Formation, central High Atlas, Morocco , 2009 .

[26]  Bahadir Ergun,et al.  Terrestrial Laser Scanning Data Integration in Surveying Engineering , 2011 .

[27]  Kenneth J. W. McCaffrey,et al.  Quantitative analysis and visualization of nonplanar fault surfaces using terrestrial laser scanning (LIDAR)—The Arkitsa fault, central Greece, as a case study , 2009 .

[28]  Xueming Xu,et al.  Digital Geologic Mapping of the Ferron Sandstone, Muddy Creek, Utah, with GPS and Reflectorless Laser Rangefinders , 2001, GPS Solutions.

[29]  John A. Howell,et al.  Overlapping faults and their effect on fluid flow in different reservoir types: A LIDAR-based outcrop modeling and flow simulation study , 2009 .

[30]  P. Hennings,et al.  Complex fracture development related to stratigraphic architecture: Challenges for structural deformation prediction, Tensleep Sandstone at the Alcova anticline, Wyoming , 2009 .

[31]  George A. McMechan,et al.  Creating virtual 3-D outcrop , 2000 .

[32]  Stefano Girardi,et al.  Discrimination between marls and limestones using intensity data from terrestrial laser scanner , 2009 .

[33]  John A. Howell,et al.  From outcrop to reservoir simulation model: Workflow and procedures , 2007 .

[34]  C. Kerans,et al.  Digital Outcrop Models: Applications of Terrestrial Scanning Lidar Technology in Stratigraphic Modeling , 2005 .

[35]  Richard R. Jones,et al.  A cost-efficient solution to true color terrestrial laser scanning , 2008 .

[36]  W. Marsden.  I and J , 2012 .

[37]  A. Đapo,et al.  Terrestrial laser scanners , 2007 .

[38]  John F. Ferguson,et al.  Outcrop fracture characterization using terrestrial laser scanners: Deep-water Jackfork sandstone at big rock quarry, Arkansas , 2008 .

[39]  Peter J. Fawcett,et al.  Chronotopographic analysis directly from point-cloud data: A method for detecting small, seasonal hillslope change, Black Mesa Escarpment, NE Arizona , 2007 .

[40]  Peter P. Flaig,et al.  Lidar intensity as a remote sensor of rock properties , 2011 .

[41]  Richard A. Beck,et al.  Analysis of hyperspectral and lidar data: Remote optical mineralogy and fracture identification , 2007 .

[42]  Jianhong Wu,et al.  Data clustering - theory, algorithms, and applications , 2007 .

[44]  Dimitri Lague,et al.  3D Terrestrial LiDAR data classification of complex natural scenes using a multi-scale dimensionality criterion: applications in geomorphology , 2011, ArXiv.

[45]  VISUALIZAÇÃO E INTERPRETAÇÃO DE MODELOS DIGITAIS DE AFLORAMENTOS UTILIZANDO LASER SCANNER TERRESTRE , 2012 .

[46]  H. Kessler,et al.  Reconstructing flood basalt lava flows in three dimensions using terrestrial laser scanning , 2011 .