The remanent magnetization may contain information about the formation process, mineralogy, and possibly geological history of different units. The magnitude of magnetization helps define the spatial configuration and structure of magnetic causative bodies, while the magnetization directions could distinguish between different causative bodies. Consequently, 3D magnetization inversion enables the complete utilization of information content in magnetic anomaly in the presence of remanent magnetization and, thereby, assist in geology differentiation. In this presentation, we apply a magnetization inversion algorithm based on fuzzy c-means clustering to investigate the utility of recovered magnetization directions in geology differentiation. We use both synthetic and field data sets to illustrate the algorithm, demonstrate the feasibility, and propose a means to quantify the confidence of differentiation results.

Presentation Date: Tuesday, October 18, 2016

Start Time: 11:10:00 AM

Location: 168

Presentation Type: ORAL

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