Prediction perspective areas for the gold mineralization using the methods of mathematical information processing and the data set of remote sensing satellite Harmonized Landsat Sentinel-2 on the Polar Urals

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For the first time, for the SW part of the Malouralskaya zone of the Polar Urals, an approach was applied. The testing of which was obtained as a result of combining (1) methods of mathematical processing of information and (2) a set of data obtained by the Earth remote sensing spacecraft Harmonized Landsat Sentinel-2. The first one is based on the analysis of search features and their functional and correlation relationships. The second is the integration of maps of the distribution of hydrothermal alterations and the lineament density scheme, created on the basis of the results of statistical processing of remote sensing data. As a result of the study, two new areas were delineated and new predictive and prospecting features of gold mineralization were identified within the study area. (1) Areas promising for the gold mineralization type in the SW part of the Malouralskaya zone are localized along transregional fault zones that intersect favorable horizons and structures and control ore mineralization, and within the volcanic-tectonic structure (large morphostructure 40 × 45 km) of the 1st order. Within this depression, the accepted systems of modern volcanic structures of the 2nd and higher order, the position of which is controlled by junctions of NE- and NW-trending faults with a length of more than 10 km. (2) Potentially ore-bearing volcanic edifices show subsidence calderas and large area of metasomatic aureoles (more than 30 km2) with elevated indices of hydroxyl-(Al-OH, Mg-OH) and carbonate-bearing minerals and iron oxides and hydroxides (limonite) and, to a lesser extent, ferrous oxides.

Sobre autores

J. Ivanova

Institute of Geology of Ore Deposits, Petrography, Mineralogy and Geochemistry of the Russian Academy of Sciences; Peoples' Friendship University of Russia

Autor responsável pela correspondência
Email: jnivanova@yandex.ru
Rússia, Moscow; Moscow

A. Bochneva

Peoples' Friendship University of Russia

Email: jnivanova@yandex.ru
Rússia, Moscow

Bibliografia

  1. Abdullah A., Akhir J.M., Abdullah I. Automatic Mapping of Lineaments Using Shaded Relief Images Derived from Digital Elevation Model (DEMs) in the Maran – Sungai Lembing Area, Malaysia // Electr. Jour. of Geotech. Engin. 2010. V. 15(6). P. 949–958. doi: 10.1039/CS9962500401.
  2. Aerospace methods of geological research / Ed. A.V. Pertsova. St. Petersburg: VSEGEI, 2000. 316 p. (in Russian).
  3. Ananiev Yu.S. Gold-concentrating systems of the Southern folded framing of the West Siberian plate (on the example of the Western Kalba). Dis. … dok. geol.-miner. Sciences. Tomsk, 2017, 509 p. (In Russian).
  4. Benevolsky B.I., Volchkov A.G., Protsky A.G. Prospects for creating an ore resource base for the gold mining industry in the Polar Urals region // Mineral Resources of Russia. Economics and Management. 2004. No. 2. P. 10–15. (in Russian).
  5. Bosikov I.I., Vyskrebenets А.S., Tsidaev B.S., Belukov S.V. Improving efficiency of appraisal, assaying and extraction of copper–nickel resources. MIAB. Mining Inf. Anal. Bull. 2020. (11–1). P. 40–53. (In Russian). doi: 10.25018/0236-1493-2020-111-0-40-53.
  6. Cheng Q., Jing, L., Panahi A. Principal component analysis with optimum order sample correlation coefficient for image enhancement // Intern. Jour. of Rem. Sen. 2006. V. 27(16). P. 3387–3401. doi: 10.1080/01431160600606882.
  7. Chernyaev E.V., Chernyaeva E.I., Sedelnikova A.Yu. Geology of the gold-skarn deposit Novogodnee-Monto (Polar Urals) // Skarns, their genesis and ore content (Fe, Cu, Au, W, Sn, …). Mat. conf. XI Readings A.N. Zavaritsky. Yekaterinburg: IGiG UrO RAN, 2005. P. 131–137. (in Russian).
  8. Claverie M., Jub J., Masek J.G. et al. The Harmonized Landsat and Sentinel-2 surface reflectance data set // Remote Sensing of Environment. V. 219. 2018. P. 145–161.
  9. Doxani G., Vermote E., Roger J.C. et al. Atmospheric correction inter-comparison exercise // Remote Sensing. 2018. 10(2). 352 p.
  10. Dushin V.A., Malyugin A.A., Kozmin V.S. Gold metallogeny of the Polar Urals // Bulletin of St. Petersburg State University. Ser. “Geology and Geography”. 2002. No. 2. Is. 7. P. 72–81. 2. (In Russian).
  11. Ekneligoda T.C., Henkel H. Interactive spatial analysis of lineaments // Jour. of Comp. and Geos. 2010. V. 36. № 8. P. 1081–1090.
  12. Farr T.G., Rosen P.A., Caro E. et al. The shuttle radar topography mission // the American Geophysical Union. 2007. P. 1–33. doi: 10.1029/2005RG000183.
  13. Galiullin I.Z., Remizov D.N. et al. Geological and mineralogical mapping (GMC) at a scale of 1:200,000 sheets Q-41-XYI, XYII, XXI, XXII (the Vostochno-Voykarskaya area). Geological report // OJSC Polyarno-Uralskoye GGP. city of Labytnangi. 2009. http://geolfond.3dn.ru. (In Russian).
  14. Gitis G.V., Ermakov B.V. Fundamentals of space-time forecasting in geoinformatics. M.: FIZMATLIT. 2004. 256 p. (In Russian).
  15. Gitis V.G. Method of Approximation of Functional Dependencies Based on Expert Scores // Problems of Information Transmission. 1987. Volume XXIII. Iss. 3. P. 94–100. (In Russian).
  16. Gornyy V.I., Kritsuk S.G., Latypov I.Sh. et al. Osobennosti mineralogicheskoy zonal'nosti rudno-magmaticheskikh sistem, vmeshchayushchikh kvartsevo-zhil'nyye mestorozhdeniya zolota (po materialam sputnikovoy spektrometrii) [Peculiarities of mineralogical zonality of ore-magmatic systems hosting quartz-vein gold deposits (according to satellite spectrometry data)] // Sovremennyye problemy distantsionnogo zondirovaniya Zemli iz kosmosa [Modern problems of remote sensing of the Earth from space]. 2014. V. 11. № 3. P. 140–156. (In Russian).
  17. Gray J.E., Coolbaugh M.F. Geology and geochemistry of Summitville, Colorado: An Epitermal Acid Sulfate Deposit in a Volcanic Dome // Economic Geology. 1994. V. 89. P. 1906–1923.
  18. Gupta R.P. Remote Sensing Geology, 3rd ed. Springer, Berlin, Germany, 2017. P. 180–190, 235–240, and 332–336.
  19. Hubbard B.E., Mack T.J., Thompson A.L. Lineament Analysis of Mineral Areas of Interest in Afghanistan. USGS Open. Reston, Virginia: U. S. Geological Survey. 2012. Available at: http://pubs.usgs.gov/of/2012/1048.
  20. Ivanova J.N., Nafigin I.O. Development of an approach for constructing a predictive map of the probabilistic distribution of high-permeability rocks zones for polymetallic mineralization type to data spacecraft Landsat-8 // Research of the Earth from space. 2023. No. 1. doi: 10.31857/S0205961423010062. (In Russian).
  21. Ivanova J.N., Vyhristenko R.I., Vikentiev I.V. Structural control of gold mineralization in the central part of the Malouralskiy volcano-plutonic belt (Polar Urals) based on the analysis of multispectral images of the Landsat 8 spacecraft // Issledovanie Zemli iz Kosmosa, 2020. No. 4. P. 51–62.
  22. Ivanova Yu.N., Bochneva A.A. Prediction perspective areas for the gold-copper-porphyry type of mineralization based on the analysis of prospecting features and their functional and correlation relationships // Geoinformatics. 2016. No. 2. P. 41–50. (In Russian).
  23. Jensen J.R. Introductory Digital Image Processing: A remote sensing perspective // Pearson Prentice Hall, Upper Saddle River NJ 07458, 3-rd ed., 2005. P. 276–287 and 296–301.
  24. Jolliffe I.T. Principal component analysis. Department of Mathematical Sciences King’s College University of Aberdeen, Uk, 2-d edition., 2002. 487 p.
  25. Kenig V.V., Butakov K.V. Deposits of ore gold Novogodnee-Monto and Petropavlovskoye – a new gold ore region in the Polar Urals // Exploration and protection of mineral resources. 2013. No. 11. P. 22–24. (In Russian).
  26. Krivko T.N., Zoloev K.K., Koroteev V.A. New data on ore occurrences in the Rudnogornensky district and the probability of discovering industrial facilities of the “Novogodnensky type” (Polar Urals) // Gold and Technologies. 2014. No. 3(25). P. 14–17. (In Russian).
  27. Krivoguzova A.S., Vasyutenko D.M. Analysis of the application of mathematical modeling in geology // Bulletin of the Baltic Federal University. I. Kant. Ser. Physico-mathematical and technical sciences. 2022. № 1. P. 101–107. (In Russian).
  28. Kucherina P.M. et al. Report of the Haramatalou party on the objects: Production of a geological additional study on a scale of 1:50,000 of the area of the Rai-Iz massif and its framing. Sheets Q-41–46-B c, d, Q-41–47-A-a-3.4, c, d, C, D; Q-41–48-A and group geological survey of scale 1: 50,000 sheets Q-41–56-V-b, c, d, D; Q-41–57-A, B, C-a and geological additional study of sheets Q-41–56-A, B, C-a; Q-41–57-V-b, c, d, D-a, c, d within the northwestern region of the Voikar synclinorium, carried out in 1982–1991, pos. Polar, 1991. (In Russian).
  29. Lesnyak D.V., Ananiev Yu.S., Gavrilov R.Yu. Structural, geophysical and geochemical criteria for epithermal acid-sulfate gold mineralization on the example of the Svetloe ore field (Khabarovsk Territory) // Bulletin of the Tomsk Polytechnic University. Engineering of georesources. 2022. V. 333. No. 8. P. 60–72. (In Russian).
  30. Levochskaya D.V., Yakich T.Yu., Lesnyak D.V., Ananiev Yu.S. Hydrothermal-metasomatic zoning, fluid regime and types of gold mineralization in the Emi and Elena sites of the Svetloe epithermal ore field (Khabarovsk Territory) // Proceedings of the Tomsk Polytechnic University. Engineering of georesources. 2021. V. 333. No. 10. P. 17–34. (In Russian).
  31. Li Z., Zhang H.K., Roy D.P. Investigation of Sentinel-2 bidirectional reflectance hot-spot sensing conditions // IEEE Transactions on Geoscience and Remote Sensing. 2018. 10.1109/TGRS.2018.2885967 (https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8594675).
  32. Loughlin W.P. Principal Component Analysis for Alteration Mapping // Photogramm. Eng. Remote Sens. 1991. V. 57. P. 1163–1169.
  33. Mansurov R.Kh. Geological and structural conditions for the localization of Petropavlovsk gold deposit (the Polar Urals). Abstract dis. … cand. geol.-miner. Sciences. Moscow, 2013. 22 p. (In Russian).
  34. Masek J.G., Claverie J., Ju M. et al. Harmonized Landsat Sentinel-2 (HLS) Product User Guide. Product Version 2.0. 2018.
  35. Masek J.G., Vermote E.F., Saleous N.E. et al. A Landsat surface reflectance dataset for North America, 1990–2000 // IEEE Geoscience and Remote Sensing Letters. 2006. V. 3(1). P. 68–72.
  36. Masoud A.A., Koike K. Morphotectonics inferred from the analysis of topographic lineaments auto-detected from DEMs: application and validation for the Sinai Peninsula, Egypt // Tectonophysics. 2011. 510(3). P. 291–308. doi: 10.1016/j.tecto.2011.07.010.
  37. Mather P.M. Computer Processing of Remotely Sensed Images: An Introduction. Chichester, UK: John Wiley and Sons. 1999. 460 p.
  38. Maurer T. How to pan-sharpen images using the gram-Schmidt pan-sharpen method – a recipe. In: International archives of the photogrammetry, remote sensing and spatial information sciences, volume XL-1/W1. ISPRS Hannover workshop, Hannover, pp 21–2. Environmental Earth Sciences. 2013. 79:101. doi.org/10.1007/s12665-020-8845-4.
  39. Melgunov A.N. et al. Geological report “Prognostic assessment of the resource potential of the Northern, Subpolar and Polar Urals based on modern geological and geophysical, mineragenic, geochemical and isotope research methods”. FSUE VSEGEI, St. Petersburg. 2008. Electronic version. (In Russian).
  40. Milovskii G.A., Rudakov V.V., Lebedev V.V. et al. Application of satellite imagery to forecast gold mineralization in deep fault zones in the Northeast of Russia // Issledovanie Zemli iz kosmos. 2010. No. 3. P. 30–34. (In Russian).
  41. Milovsky G.A., Denisova E.A., Ezhov A.A., Kalenkovich N.S. Prediction of mineralization in the Sob-Kharbeiskaya area (Polar Urals) based on cosmic geological data // Issled. Earth from space. 2007. No. 6. P. 29–36.
  42. Nezampour M.H., Rassa I. Using remote sensing technology for the determination of mineralization in the Kal-e-Kafi porphyritic deposit, Anarak, Iran // Min. Depos. Res.: Meeting the Global Challenge. 2005. Р. 565–567. doi.org/10.1007/3-540-27946-6_145.
  43. Ovechkin A.M. Prospecting for chromites in the northern part of the Voikaro-Syn'inskii hypermafic massif. Report for 1985–1999, settlement. Polar, 1999. (In Russian).
  44. Remizov D.N., Shishkin M.A., Grigoriev S.I. et al. State geological map of the Russian Federation. Scale 1:200,000 (2nd edition, digital). The Polar-Ural series. Sheet Q-41-XVI (Khordyus). Explanatory letter. Saint Petersburg: Cartographic factory VSEGEI. 2014. 256 p. (In Russian).
  45. Roy D.P., Li J., Zhang H.K. et al. Examination of Sentinel-2A multispectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance // Remote Sensing of Environment. 2017. V. 199. P. 25–38.
  46. Roy D.P., Zhang H.K., Ju J. et al. A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance // Remote Sensing of Environment. 2016. V. 176. P. 255–271.
  47. Seravkin I.B. Endogenous metallogeny of gold in the Urals (review, article 1 – Polar, Subpolar, Northern and Middle Urals) // Geological collection. Information materials. Geol Institute Ufa department of the Russian Academy of Sciences. 2009. P. 164–176. (In Russian).
  48. Serokurov, Yu.N., Kalmykov V.D., Gromtsev K.V. Remote assessment of the gold-bearing potential // Ores and metals. 2008. No. 1. P. 45–51. (In Russian).
  49. Shaporev V.A., Kapitanov A.D., Shaporeva R.M. et al. Geological report “Analysis, generalization and development of a methodology for interpreting electrical data for mapping reservoirs and solving other oil and gas prospecting problems in the southwestern part of the Siberian Platform”. PGO “Yeniseigeophysics”. 1986, p. Geofizikov. 374 p. (In Russian).
  50. Sharpenok L.N. Magmatogenic-ore systems of continental volcano-plutonic belts of mobile areas // Regional geology and metallogeny. 2014. No. 58. P. 84–90. (In Russian).
  51. Sharpenok L.N. Magmatogenic ring structures. Leningrad, Nedra, 1979, 231 p. (In Russian).
  52. Shishkin M.A., Astapov A.P., Kabatov N.V. et al. State geological map of the Russian Federation. Scale 1: 1000000 (3rd gen.). The Ural series. Q41 – Vorkuta sheet: Explanatory note. St. Petersburg: VSEGEI. 2007. 541 p. (In Russian).
  53. Sobolev I.D., Soboleva A.A., Udoratina O.V. et al. Devonian island-arc magmatism of the Voikar zone in the Polar Urals // Geotectonics. 2018. V. 52. No 5. P. 531–563.
  54. Space information in geology / Ed. A.V. Peive. Moscow: Nauka, 1983. 536 p. (In Russian).
  55. Thannoun R.G. Automatic Extraction and Geospatial Analysis of Lineaments and their Tectonic Significance in some areas of Northern Iraq using Remote Sensing Techniques and GIS // Intern. Jour. of enhanced Res. in Scien. Techn. & Engin. 2013. 2, 2. ISSN NO: 2319–7463.
  56. Thomson I.N., Kravtsov V.S., Kochneva N.T., Seredin V.V., Seliverstov V. A. Metallogeny of hidden lineaments and concentric structures. Moscow: Nedra, 1984. 272 p. (In Russian).
  57. Tommaso I., Rubinstein N. Hydrothermal alteration mapping using ASTER data in the Infiernillo porphyry deposit, Argentina // Ore Geol. Rev. 2007. V. 32. P. 275–290.
  58. Vaganov V.I., Ivankin P.F., Kropotkin P.N. Explosive ring structures of shields and platforms. M.: Nauka, 1985. 200 p. (In Russian).
  59. Verdiansyah O. A Desktop Study to Determine Mineralization Using Lineament Density Analysis at Kulon Progo Mountains, Yogyakarta and Central Java Province. Indonesia // Indonesian Journ. of Geography. 2019. V. 51. No. 1. P. 31–41. doi.org/10.22146/ijg.37442
  60. Verdiansyah O. Aplikasi Lineament Density Analysis Untuk Membatasi Pola Kaldera Purba Godean // Jour. Teknologi Technoscienti. 2017. V. 9(2).
  61. Vermote E., Justice C., Claverie M., Franch B. Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product // Remote Sensing of Environment. 2016. V. 185. P. 46–56.
  62. Vermote E.F., Kotchenova S. Atmospheric correction for the monitoring of land surfaces // Journal of Geophysical Research: Atmospheres. 2008. V. 113(D23).
  63. Vikentiev I.V., Mansurov R.Kh., Ivanova Yu.N. et al. Gold-porphyry Petropavlovskoye deposit (Polyarny Ural): geological position, mineralogy and conditions of formation Geology of Ruds. deposits // Geology of ore deposits. 2017. V. 59. No. 6. P. 501–541.
  64. Volchkov A.G., Girfanov M.M., Novikov V.P. Prospects for the development of the mineral resource base of gold in the Polar Urals (YaNAO) // Problems of development of SMEs of solid fields. isp. in the Polar Urals. Salekhard. 2007. P. 188–190. (In Russian).
  65. Vural A., Corumluoglu Ö., Asri I. Remote sensing technique for capturing and exploration of mineral deposit sites in Gumushane metallogenic province, NE Turkey // J. Geol. Soc. India. 2017. V. 90. Is. 5. Р. 628–633. doi.org/10.1007/s12594-017-0762-0
  66. Wilson J.P., Gallant J.C. Terrain analysis: principles and applications // John Wiley & Sons. 2000. 520 р.
  67. Yakovlev G.F. Geological structures of ore fields and deposits. M.: Moscow University, 1982. 270 p.
  68. Yousefi T., Aliyari F., Abedini A., Calagari A.A. Integrating geologic and Landsat-8 and ASTER remote sensing data for gold exploration: a case study from Zarshuran Carlin-type gold deposit, NW Iran // Arabian J. Geoscien. 2018. 11:482. doi.org/10.1007/s12517-018-3822-x
  69. Zhang X., Panzer M., Duke N. Lithologic and mineral information extraction for gold exploration using ASTER data in the south Chocolate Mountains (California) // J. Photogramm. Remote Sens. 2007. V. 62. P. 271–282.
  70. Zhu Z., Wang S., Woodcock C.E. Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4–7, 8, and Sentinel 2 images // Remote Sensing of Environment. 2015. V. 159. P. 269–277.
  71. Zverev A.T., Gavrilova V.V. Development of the theory and methods for assessing and forecasting the state of natural resources using space images. Izv. universities. Geodesy and aerial photography. 2012. No. 5. P. 44–47. (In Russian).
  72. Zverev A.T., Malinnikov V.A., Arellano-Baeza A. Prediction of ore mineral deposits in Chile based on lineament analysis of space images // Izv. universities. Geodesy and aerial photography. 2005. No. 6. P. 62–69. (In Russian).
  73. Zylova L.I., Kazak A.P. et al. State geological map of the Russian Federation. Scale 1:1000000 (third generation). Series West Siberian. Sheet Q-42 – Salekhard: Explanatory note. St. Petersburg: VSEGEI, 2014. 396 p. (In Russian).

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