Predictive Mapping of Industrial Minerals Using Reprocessing Data by Near-Surface Seismic Methods
A.V. Yablokov1, A.V. Mamaeva2, A.T. Semashev2, V.D. Grishko2, A.A. Kozyaev2, V.V. Lukyanov3, E.A. Buryak4
1 Trofimuk Institute of Petroleum Geology and Geophysics SB RAS, Novosibirsk, Russia
2 LLC «RN-Geology Research Development», Krasnoyarsk, Russia
3 LLC « RN-Upstream Design»,Krasnoyarsk, Russia
4 LLC «Kharampurneftegaz», Gubkinsky, Russia
Keywords: seismic exploration, refracted wave method, multichannel analysis of surface waves, cluster analysis, near-surface geological section, industrial minerals
Abstract
An approach is proposed for assessing the distribution of industrial minerals in the upper part of the geological section based on reprocessing and interpretation of archived 3D seismic data. The approach includes reconstruction of P- and S-wave velocity models using modified refraction and surface wave methods, automated extraction of dispersion curves using a neural network algorithm, as well as calculation and integration of a set of seismic and morphometric attributes. Based on the combined feature space, clustering is performed to delineate facies associated with deposits of different genesis. The approach was tested on the Kharampur license area located in the Arctic zone of West Siberia, characterized by the presence of permafrost. For this site (area ~60 km²), it is shown that the proposed workflow enables the construction of detailed predictive maps consistent with drilling data and active quarries. Clustering based on combined seismic and terrain-related features allowed identification of facies and the construction of physico-geological models of sand and peat bodies with economically significant thicknesses. This approach enables the generation of high-resolution predictive maps without additional field surveys, with a resolution comparable to engineering-scale drilling data.
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