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https://hdl.handle.net/2440/78269
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Type: | Journal article |
Title: | The RANSAC method for generating fracture networks from micro-seismic event data |
Author: | Fadakar Alghalandis, Y. Dowd, P. Xu, C. |
Citation: | Mathematical Geosciences, 2013; 45(2):207-224 |
Publisher: | Kluwer Academic/Plenum Publ |
Issue Date: | 2013 |
ISSN: | 1874-8961 1874-8953 |
Statement of Responsibility: | Younes Fadakar Alghalandis, Peter A. Dowd, Chaoshui Xu |
Abstract: | Fracture network modeling is an essential part of the design, development and performance assessment of Enhanced Geothermal Systems. These systems are created from geothermal resources, usually located several kilometers below the surface of the Earth, by establishing a network of connected fractures through which fluid can flow. The depth of the reservoir makes it impossible to make direct measurements of fractures and data are collected from indirect measurements such as geophysical surveys. An important source of indirect data is the seismic event point cloud generated by the fracture stimulation process. Locations of these points are estimated from recorded micro-seismic signals generated by fracture initiation, propagation and slip. This point cloud can be expressed as a set of three-dimensional coordinates with attributes, for example Seijk={(x,y,z); a{pipe}x,y,z∈R, a∈I}. We describe two methods for reconstructing realistic fracture trace lines and planes given the point cloud of seismic events data: Enhanced Brute-Force Search and RANSAC. The methods have been tested on a synthetic data set and on the Habanero data set of Geodynamics' geothermal project in the Cooper Basin of South Australia. Our results show that the RANSAC method is an efficient and suitable method for the conditional simulation of fracture networks. © 2013 International Association for Mathematical Geosciences. |
Keywords: | Fracture network modeling Line/plane detection Point cloud RANSAC Conditional modeling |
Rights: | © International Association for Mathematical Geosciences 2013 |
DOI: | 10.1007/s11004-012-9439-9 |
Grant ID: | http://purl.org/au-research/grants/arc/DP110104766 |
Published version: | http://dx.doi.org/10.1007/s11004-012-9439-9 |
Appears in Collections: | Aurora harvest 4 Civil and Environmental Engineering publications |
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