A single multi-scale and multi-sourced semi-automated lineament detection technique for detailed structural mapping with applications to geothermal energy exploration

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1144/qjegh2022-051. This is version 1 of this Preprint.

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Authors

Christopher Mark Yeomans , Hester Claridge, Alexander Hudson, Robin K Shail , Cees Willems , Matthew Eyre , Chris Harker

Abstract

A multitude of semi-automated algorithms, many incorporating multi-sourced datasets into a single analysis, now exist. However, these operate at a fixed pixel resolution resulting in multi-sourced methods being limited by the largest input pixel size. Multi-scale lineament detection circumvents this issue and allows increased levels of detail to be captured. In this study we present a semi-automated method using bottom-up Object-Based Image Analysis approach to map regional lineaments to a high level of detail. The method is applied to onshore LiDAR data and offshore bathymetry around the Land's End Granite (Cornwall, UK). The method uses three different pixel resolutions to extract detailed lineaments across a 700 km2 area. The granite displays large-scale NW-SE structures that are considered to be an analogue to fault-hosted geothermal systems in southwest England. Investigation of the lineaments derived from this study show along-strike variations from NW-SE orientations within granite to NNW-SSE within mudstone and reflect structural inheritance of early Variscan structures within Devonian mudstones. This is furthered by analysing these major structures for reservoir potential. Lineaments proximal to these broadly NW-SE features indicate a damage zone approximately 100 m wide is present. These observations provide a preliminary understanding of reservoir characteristics for fault-hosted geothermal systems.

DOI

https://doi.org/10.31223/X5R59C

Subjects

Geology, Geomorphology, Tectonics and Structure

Keywords

bathymetry, lineament detection, LiDAR

Dates

Published: 2020-10-23 05:06

Last Updated: 2020-10-23 12:06

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
Nothing to declare

Data Availability (Reason not available):
Data available once published by request to the author