Mehrdad Darijani

Office: ER-4038Dr. Mehrdad Darijani

B.Sc. in Physics, Shahid Bahonar University of Kerman, Iran.

M.Sc. in Geophysics, University of Tehran, Iran.
Thesis Title: Investigating electrical resistivity and geological structures of hot springs using Magnetotelluric method in Markazi province, Iran.

Ph.D. in Geophysics, Memorial University of Newfoundland, Canada.
Thesis Title: Investigating modelling and inversion techniques for overburden stripping for uranium exploration in the Athabasca Basin, Canada

Post-Doctoral Project Title: Investigation and development of strategies for performing constrained inversions of geophysical data for mineral exploration
Supervisor: Dr. Colin G. Farquharson
Research Abstract: Inversion has become the standard tool for interpreting geophysical data. There are several different ways of incorporating geological information or ideas into a geophysical inversion, including reference models, bounds, weights, the type of measure used in the penalty function being minimized, and physical-property-based clustering. Each has advantages and disadvantages in terms of their capabilities and their effects on how easy, or not, the resulting minimization problem is to solve. This research aims to formulate a coherent framework for the most effective way to perform constrained inversion in real-life mineral exploration scenarios, and to analyze the implications, advantages, and drawbacks of the various available approaches. The focus will be on magnetic data and induced polarization (IP) data, both of which the industrial partner feels could provide more information for their particular exploration and delineation projects than they currently do. The work on magnetic data will include data-sets for which magnetic susceptibility models are sufficient to explain the data, and data-sets for which remanent magnetization cannot be ignored. In addition, further magnetization and chargeability measurements on samples will be performed to increase the amount of physical property information available for the examples being considered.

Research Interests:
Forward modelling and inversion (joint and constrained) of geophysical data (seismic, electromagnetic, magnetic and gravity data); Artificial intelligence

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