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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

3D Regional Geological Modelling in Structurally Complex Environments: Gaining Geological Insight for the Northern Labrador Trough

Montsion, Rebecca January 2017 (has links)
3D geological modelling is becoming an effective tool for communication and development of geological understanding. This is due to increased computer performance and availability of improved geological modelling software. 3D geological modelling technology has reached the stage where it can be implemented in regionally extensive and geologically complex settings, with the ability to achieve geological insight beyond what could otherwise have been gained through 2D investigations alone. Insight includes better constrained fault and horizon topologies, refined fold geometries, improved understanding of tectonic processes, and characterization of deformational events. By integrating field observations, aeromagnetic maps, and 3D modelling techniques in the northern Labrador Trough, a regionally extensive and structurally complex geological environment, regional faults geometries and topological relationships were refined. Additionally, a new fault, the Ujaralialuk Fault, and two shear zones were interpreted. During modelling, several challenges were identified, including higher computational costs for regionally extensive models, sparse 3D constraints, algorithmic limitations related to complex geometries, and the large investment of time and effort required to produce a single model solution. A benefit of this investigation is that new insight was also gained for a greenfields region which may assist future exploration efforts. Developing 3D models in challenging environments allows for better definition of future workflow requirements, algorithm enhancements, and knowledge integration. These are needed to achieve a geologically reasonable modelling standard and gain insight for poorly constrained geological settings.

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