Course Content (Syllabus)
• Course objectives- introduction, different types of geological data, geological data analysis process.
• Filtering procedures. Smoothing filters – differential filters. Filter class, application of moving filters, effect of filtering. Examples of application to noisy data, application to highlight changes.
• Polynomial fitting of geological data. Selection of the polynomial, fitting evaluation. Data isodistribution.
The laboratory cources include application of the methods taught in theory by writing code in the Matlab programing language. Students are asked to write a Matlab code that actually analyzes geodata based on techniques taught in theory and also are asked to interpret the results.
In particular, laboratories include the application of the following methods: Smoothing filters, differential filters, polynomial regression and data isodistribution, calculation of covariance and correlation, interpolation in one dimension, interpolation in two dimensions and map construction, spectral analysis (FFT) of data and application of spectral filters.
• Geostatistical data analysis. Basic statistical concepts. Spatial covariance and correlation. Interpolation in 1D. Interpolation techniques (nearest neighbor, linear, polynomial, spline etc.). Advantages and disadvantages, examples of application.
• Interpolation in two dimensions. Interpolation techniques, pros and cons. Using of covariance matrix to construct maps. Examples of application.
• Spectral analysis. Basic concepts, sampling frequency, power spectra. Application to geological. Design and application of spectral filters.