Machine learning applied to geophysics

What is it about?

Machine Learning is growing fast in recent years as a powerful tool for interpreting geophysical data. Boundary analysis is a very common practice to identify the source edges from potential field anomalies. We propose a new method based on unsupervised machine learning algorithm for an automatic boundary analysis.

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Why is it important?

With our method we are no longer dependent on the experience and sensitivity of the operator during the interpretation. Moreover, it is a method that does not require very experienced operators as is the case with traditional boundary analysis methods.