Semi-automatic mapping of fracture networks on Digital Outcrop Models of fractured reservoirs field analogues NEXT – Natural and Experimental Tectonics group , Universit{\`{a}} di Parma , Dipartimento di Scienze The DOMStudio workflow

Silvia Mittempergher and Andrea Bistacchi and Mattia Martinelli and Andrea Succo and Marco Meda and Luca Clemenzi. ( 2017 )
in: 2017 Ring Meeting, ASGA

Abstract

Fractures control the transport and storage properties of buried hydrocarbon and water reservoirs, and can be only partially imaged from the earth surface. Outcrop analogues of buried reservoir are commonly used for a quantitative characterization of natural fracture systems and to extract predictive laws for integrating the limited subsurface data. In the last decades, Digital Outcrop Models (DOMs) based on LIDAR or photogrammetry have been successfully applied to obtain large datasets of 3D fracture orientation and spacing from field surveys. However, extracting fracture traces from DOMs is still largely a manual, time consuming process, limiting the effective usage of potentially very large datasets. Here we present a workflow for speeding up the detection of lineaments on DOMs, by applying image analysis techniques on DOMs based on photogrammetry. The DOMs are reconstructed using a large number of high resolution digital photographs processed with VisualSFM (Surface From Motion) software. The SFM algorithm links each pixel in the images (in 2D image coordinates) to the corresponding point on the DOM (in 3D real space coordinates). The biunivocal relation between images and DOM allows to process a selection of high resolution images using image analysis techniques, and to project the extracted features (expressed in image coordinates) on the 3D DOM surface without losing resolution. The complete process, from lineament extraction to the conversion to 3D lines, is embedded in the MATLB{\textregistered} toolbox DOMStudioImage. The main steps embedded in the toolbox are: (1) from image to lineament map: after preprocessing, lineaments are extracted using an edge/ridge detection algorithm. DOMStudioImage embeds three edge-ridge detection methods, namely the ICM segmentation, the phase symmetry line detection and the complex shearlet line detection; (2) lineament traces to vector lines: the lineament map is converted to an array of segments defined by vertices coordinates; (3) manual validation of the vector lines; (4) creation of 3D polylines in GOCAD format. Once projected on the DOM, faults and fractures can be used for further 3D analysis. The toolbox has been tested on DOMs of fractured and faulted limestone, used as an analogue for buried carbonate reservoirs.

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BibTeX Reference

@INPROCEEDINGS{Mittempergher2017,
    author = { Mittempergher, Silvia and Bistacchi, Andrea and Martinelli, Mattia and Succo, Andrea and Meda, Marco and Clemenzi, Luca },
     title = { Semi-automatic mapping of fracture networks on Digital Outcrop Models of fractured reservoirs field analogues NEXT – Natural and Experimental Tectonics group , Universit{\`{a}} di Parma , Dipartimento di Scienze The DOMStudio workflow },
 booktitle = { 2017 Ring Meeting },
      year = { 2017 },
 publisher = { ASGA },
  abstract = { Fractures control the transport and storage properties of buried hydrocarbon and water reservoirs, and can be only partially imaged from the earth surface. Outcrop analogues of buried reservoir are commonly used for a quantitative characterization of natural fracture systems and to extract predictive laws for integrating the limited subsurface data. In the last decades, Digital Outcrop Models (DOMs) based on LIDAR or photogrammetry have been successfully applied to obtain large datasets of 3D fracture orientation and spacing from field surveys. However, extracting fracture traces from DOMs is still largely a manual, time consuming process, limiting the effective usage of potentially very large datasets. Here we present a workflow for speeding up the detection of lineaments on DOMs, by applying image analysis techniques on DOMs based on photogrammetry. The DOMs are reconstructed using a large number of high resolution digital photographs processed with VisualSFM (Surface From Motion) software. The SFM algorithm links each pixel in the images (in 2D image coordinates) to the corresponding point on the DOM (in 3D real space coordinates). The biunivocal relation between images and DOM allows to process a selection of high resolution images using image analysis techniques, and to project the extracted features (expressed in image coordinates) on the 3D DOM surface without losing resolution. The complete process, from lineament extraction to the conversion to 3D lines, is embedded in the MATLB{\textregistered} toolbox DOMStudioImage. The main steps embedded in the toolbox are: (1) from image to lineament map: after preprocessing, lineaments are extracted using an edge/ridge detection algorithm. DOMStudioImage embeds three edge-ridge detection methods, namely the ICM segmentation, the phase symmetry line detection and the complex shearlet line detection; (2) lineament traces to vector lines: the lineament map is converted to an array of segments defined by vertices coordinates; (3) manual validation of the vector lines; (4) creation of 3D polylines in GOCAD format. Once projected on the DOM, faults and fractures can be used for further 3D analysis. The toolbox has been tested on DOMs of fractured and faulted limestone, used as an analogue for buried carbonate reservoirs. }
}