Interpreting regional 3D fault networks from integrated geological and geophysical data sets: An example from the Guichon Creek batholith, British Columbia

• Published in: Journal of structural geology 2019-02, Vol.119, p.93-106
• Main Authors: Lesage, Guillaume, Byrne, Kevin, Morris, William A., Enkin, Randolph J., Lee, Robert G., Mir, Reza, Hart, Craig J.R.
• Format: Article
• Language: English
• Subjects: Dip modeling; Fault network; Lineament mapping; Magnetic anomaly
• ISSN: 0191-8141; 1873-1201
• DOI: 10.1016/j.jsg.2018.12.007

The effects of fault processes on rocks commonly include a lowered magnetic susceptibility and an increased predisposition to erosion. We present a workflow that uses these characteristics of faults and geological observations to interpret a 3D fault network. The location of faults on the topographic surface is first interpreted by a multi-layer lineament mapping method that includes geological and geophysical data sets. We then demonstrate how magnetic intensity data can be used to estimate the dip of fault-related magnetic anomalies by performing 2D inverse modeling along profiles extracted from a magnetic intensity grid. The accuracy of the method is assessed by modeling the dip of low magnetic anomalies of known geometry created in a synthetic 3D magnetic susceptibility model. Modeled dips are consistently accurate to better than 5° for input dips >60°. A requirement of the method, however, is that the magnetic susceptibility contrast between the background field and the magnetic anomaly must be >75% for the anomaly to be accurately modeled. Comparison between fault orientations modeled from magnetic data and measured in the field in the Guichon Creek batholith confirms that the methodology can be successfully applied to brittle faults in real, albeit relatively simple geological environments. •Fault network at surface identified by lineament mapping using multiple data sets.•Magnetite oxidation in faults reduces magnetic susceptibility to form linear features.•Fault dips modeled along 2D profiles extracted from magnetic intensity grid.•Dip modeling accuracy better than 5° at input dip >60°.•3D fault network built using lineament mapping, modeled dips and measured strike/dips.