Solving the tasks of subsurface resources management based on the created GIS RAPID geoinformation technology
B. Busygin1, S. Nikulin1, K. Sergieieva1
1Dnipro University of Technology, Dnipro, Ukraine
Min. miner. depos. 2019, 13(3):49-57
https://doi.org/10.33271/mining13.03.049
Full text (PDF)
      ABSTRACT
      Purpose. Solving the tasks of subsurface resources management based on the created GIS RAPID geoinformation technology.
      Methods. Close spatial relationships of lineament network characteristics and earthquake epicenters were detected in 3 seismically active areas located in the mountainous regions of Central Europe. Digital elevation models (DEM) based on ASTER satellite surveys and earthquake epicenter data were used. The nature of spatial relationship of lineament network and vein ore objects was studied in the territory of Congo DR, in the Lake Kivu area using space imagery. Gold ore objects were searched and forecasted in Uzbekistan in the site of Jamansai Mountains. High-resolution imagery from QuickBird 2 satellite, geophysical field surveys, geological and geochemical data were used.
      Findings. It was found that a significant number of epicenters are located in areas of high concentration of “non-standard” azimuths lineaments – from 27 to 34% of the total number of lineaments. It was revealed that 59.6% of the epicenters are located within 10% of sites with the highest values of complex deformation maps; 50% of the areas with the highest values of these maps contain, on average, 89% of all earthquake epicenters. It was found that satellite image lineament concentration maps with “non-standard” azimuths reflect the spatial relationship with known deposits much better than the concentration map of all lineaments. It was detected that the total area of gold ore objects perspective sites is about 20 km2.
      Originality.The use of GIS RAPID in a number of earth’s crust areas has allowed to establish new regularities linking the networks of physical field and landscape lineament characteristics with ore bodies and earthquake epicenters localization.
      Practical implications. A new technology has been developed for solving geological forecasting and prospecting problems. The technology can be used to solve a wide range of practical problems, especially in difficult geological conditions when searching for deep objects weakly presented in external fields and landscape.
      Keywords: geoinformation system, Data Mining, mineral deposits, earthquakes, lineament analysis
      REFERENCES
Borg, I., & Groenen, P.J.F. (2005). Modern multidimensional scaling: theory and applications. Berlin, Germany: Springer.
https://doi.org/10.18637/jss.v014.b04
Busygin, B.S., & Nikulin, S.L. (2015). Specialized geoinformation system RAPID: features, structure, tasks. In 14th EAGE International Conference on Geoinformatics – Theoretical and Applied Aspects, Geoinformatics 2015 (pp. 1-4). Kyiv, Ukraine: EarthDoc.
https://doi.org/10.3997/2214-4609.201412353
Busygin, B.S., & Nikulin, S.L. (2016). The relationships between the lineaments in satellite images and earthquake epicenters within the Baikal Rift Zone. Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 13(4), 219-230.
https://doi.org/10.21046/2070-7401-2016-13-15-219-230
Florinsky, I.V. (2008). Global lineaments: application of digital terrain modelling. Advances in Digital Terrain Analysis (Lecture Notes in Geoinformation and Cartography), 365-382.
https://doi.org/10.1007/978-3-540-77800-4_20
Kuttykadamov, M.E., Rysbekov, K.B., Milev, I., Ystykul, K.A., & Bektur, B.K. (2016). Geodetic monitoring methods of high-rise constructions deformations with modern techno-logies application. Journal of Theoretical and Applied Information Technology, 93(1), 24-31.
Masoud, A., & Koike, K. (2017). Applicability of computeraided comprehensive tool (LINDA: LINeament Detection and Analysis) and shaded digital elevation model for characterizing and interpreting morphotectonic features from lineaments. Computers & Geosciences, (106), 89-100.
https://doi.org/10.1016/j.cageo.2017.06.006
Pivnyak, G.G., Busygin, B.S., & Garkusha, I.N. (2010). Conceptual approach to the creation of the state system of monitoring and prediction of coal fires in the data space survey. Geoinformatics 2010 – 9th International Conference on Geoinformatics: Theoretical and Applied Aspects, A020.
Wit, M.J., Guillocheau, F., & Wit, M.C.J. (2015). Geology and resource potential of the Congo Basin. Heidelberg, Germany: Springer-Verlag Berlin Heidelberg.
https://doi.org/10.1007/978-3-642-29482-2
Witten, I., Frank, E., Hall, M., & Pal, C. (2017). Data Mining: practical machine learning tools and techniques. Amsterdam, Netherlands: Morgan Kaufmann Publishing.
Zakharov, V.N., Zverev, A.V., Zverev, A.T., Malinnikov, V.A., & Malinnikova, O.N. (2017). Application of automated lineament analysis of satellite images in modern geodynamics research: a case study. Russian Journal of Earth Sciences, 17(3), 1-14.
https://doi.org/10.2205/2017ES000599