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Geowebinars’21. Machine learning methods in the interpretation of potential-field and seismic survey data.
Topic: Machine learning methods in the interpretation of potential-field and seismic survey data.
Speaker: Aleksandr Viktorovich Kolmakov
Machine learning methods in the interpretation of potential-field and seismic survey data
Abstract:
The high resolution of modern airborne geophysical methods, combined with the relatively low cost of airborne geophysical fieldwork (with the possibility of combining available measuring instruments on a single aircraft), makes non-seismic methods highly effective at the hydrocarbon exploration stage. Integrating non-seismic methods, particularly gravimetry and magnetometry, with seismic survey data produces a consistent model of geophysical data, thereby substantially reducing uncertainties in geological structure associated with lateral variations in the density, acoustic and geometric properties of the sedimentary cover deposits and basement.