Developing efficient computational simulationtools for geophysical applications

Quantitative interpretation of magnetic data through inversion for general distributions of magnetic susceptibility has played an increasingly important role in mineral exploration in recent years. The goal of the proposed project is to develop efficient and robust computational simulation tools for the inversion of magnetization at a specified depth using ground/airborne magnetic data. A numerical algorithm based on the preconditioned conjugate gradient method with Teoplitz matrix, which is well studied in the field of image processing, is extended to construct a fast and robust method for geophysical applications. The method provides a more accurate and detailed magnetic mapping, so that the geologist will have a better understanding for subsurface geology environment. Preliminary research has demonstrated that significant improvement compared to the existing method using the re-weighted regularized conjugate gradient algorithm can be achieved by the proposed method. Working together with TerraNotes, we plan to refine and promote this new technique to geophysical community.

Intern: 
Jian Deng
Faculty Supervisor: 
Dr. Yau Shu Wong
Project Year: 
2014
Province: 
Alberta
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