GEOSCAN Search Results: Fastlink

GEOSCAN Menu


TitleAI-enabled remote sensing data interpretation for geothermal resource evaluation as applied to the Mount Meager geothermal prospective area
DownloadDownloads
 
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorChen, ZORCID logo; Grasby, S EORCID logo; Deblonde, C; Liu, XORCID logo
SourceGeological Survey of Canada, Open File 8882, 2022, 1 sheet, https://doi.org/10.4095/330008 Open Access logo Open Access
Image
Year2022
PublisherNatural Resources Canada
Documentopen file
Lang.English
Mediaon-line; digital
File formatreadme
File formatpdf
ProvinceBritish Columbia
NTS92J/05; 92J/06; 92J/11; 92J/12; 92J/13; 92J/14
AreaMount Meager; Lillooet River; Meager Creek
Lat/Long WENS-123.7442 -123.2817 50.7517 50.4839
Subjectsgeophysics; hydrogeology; regional geology; structural geology; surficial geology/geomorphology; Science and Technology; Nature and Environment; geothermal energy; geothermal resources; geothermal potential; remote sensing; satellite imagery; LANDSAT; volcanology; volcanic features; volcanoes; volcanism; magmatism; intrusions; thermal analyses; heat flow; ground temperatures; anomalies; bedrock geology; structural features; fractures; faults; groundwater; groundwater circulation; flow regimes; flow structures; structural analyses; lineaments; deformation; slope failures; models; field work; field relations; structural analyses; structural trends; Garibaldi Volcanic Belt; Mount Meager Volcanic Complex; Landsat 8; Artificial intelligence; Methodology; Phanerozoic; Cenozoic; Quaternary; Tertiary
Illustrationslocation maps; tables; flow diagrams; satellite images; plots
ProgramEnergy Geoscience Geothermal Assessments
Released2022 12 06
AbstractThe objective of this study is to search for features and indicators from the identified geothermal resource sweet spot in the south Mount Meager area that are applicable to other volcanic complexes in the Garibaldi Volcanic Belt. A Landsat 8 multi-spectral band dataset, for a total of 57 images ranging from visible through infrared to thermal infrared frequency channels and covering different years and seasons, were selected. Specific features that are indicative of high geothermal heat flux, fractured permeable zones, and groundwater circulation, the three key elements in exploring for geothermal resource, were extracted. The thermal infrared images from different seasons show occurrence of high temperature anomalies and their association with volcanic and intrusive bodies, and reveal the variation in location and intensity of the anomalies with time over four seasons, allowing inference of specific heat transform mechanisms. Automatically extracted linear features using AI/ML algorithms developed for computer vision from various frequency bands show various linear segment groups that are likely surface expression associated with local volcanic activities, regional deformation and slope failure. In conjunction with regional structural models and field observations, the anomalies and features from remotely sensed images were interpreted to provide new insights for improving our understanding of the Mount Meager geothermal system and its characteristics. After validation, the methods developed and indicators identified in this study can be applied to other volcanic complexes in the Garibaldi, or other volcanic belts for geothermal resource reconnaissance.
Summary(Plain Language Summary, not published)
A Landsat 8 multi-spectral band dataset, for a total of 57 images ranging from visible through infrared to thermal infrared frequency channels and covering different years and seasons, were collected. Features that could be indicative of high geothermal heat flux, fractured permeable zones, and groundwater circulation were extracted using AI/ML algorithms. Based on regional structural models and field observations, the anomalies and features from remotely sensed images were interpreted to provide new insights for improving our understanding of the Mount Meager geothermal system and its characteristics.
GEOSCAN ID330008

 
Date modified: