Applied Geology

Dr. Satyabrata Behera

Room No. - NA,

+91 7008718304 +91 9439199983

satyabratabehera [at] ravenshawuniversity [dot] ac [dot] in geo.beherasatyabrata [at] gmail [dot] com

Dr. Satyabrata Behera holds the post of Assistant Professor in the Department of Geology, Ravenshaw University. He has done his doctoral research in the Department of Geology and Geophysics, IIT Kharagpur and obtained his PhD degree in 2022. During his doctoral program, Dr. Behera worked on a challenging area of mineral exploration, taking two important gold localities (Sonakhan and Hutti) in India as case studies. He has acquired state-of-the-art expertise in computerized mineral exploration that involved a strong command over the Geographic Information System on which many of the soft computing tools are routinely implemented. In addition, he has acquired state-of-the-art skills in spatial data analysis, satellite image processing and integration of multidisciplinary geoscience data (geological, geochemical, geophysical & remote sensing) in his gold prospectivity modelling work. Dr. Behera has published the results of his research in reputed international journals in the field of mineral exploration, an area in which there is a rare contribution from academia. Furthermore, he has served as a Teaching Assistant in two MHRD sponsored MOOC projects for the NPTEL (SWAYAM) courses “Mineral Resources: Geology, Exploration, Economics and Environment” and “Fluid Inclusion in Mineral Principles, Methodology, Practice and Application” at IIT Kharagpur. Essentially, Dr. Behera is a trained Economic Geologist and Exploration Geoscientist with adequate knowledge on economic aspects of ore deposits, methodologies and practices of ore deposit evaluation with a good knowledge on Geostatistics that he routinely applies in his work. His research mainly focuses on developing effective approaches to improve the exploration effort for precious, essential, critical and strategic minerals in our country.

Selected Publications

  1. Behera, S. and Panigrahi, M.K., 2022. Gold prospectivity mapping and exploration targeting in Hutti-Maski schist belt, India: Synergistic application of Weights-of-Evidence (WOE), Fuzzy Logic (FL) and hybrid (WOE-FL) models. Journal of Geochemical Exploration, 235, p.106963.
  2. Behera, S. and Panigrahi, M.K., 2021. Gold Prospectivity Mapping in the Sonakhan Greenstone Belt, Central India: A Knowledge-Driven Guide for Target Delineation in a Region of Low Exploration Maturity. Natural Resources Research, 30(6), pp.4009-4045.
  3. Behera, S. and Panigrahi, M.K., 2021. Mineral prospectivity modelling using singularity mapping and multifractal analysis of stream sediment geochemical data from the auriferous Hutti-Maski schist belt, S. India. Ore Geology Reviews, 131, p.104029.
  4. Behera, S., 2019. Remote Mapping of Clay Alteration Zones in moderately vegetated Terrane using Landsat ETM + Data: A Case Study from Sonakhan Greenstone Belt, Central India. GEOS Annual Edition, 17, pp.50-55.
  5. Behera, S., Panigrahi, M. K., & Pradhan, A. (2019). Identification of geochemical anomaly and gold potential mapping in the Sonakhan Greenstone belt, Central India: An integrated concentration-area fractal and fuzzy AHP approach. Applied Geochemistry, 107, pp.45-57.
  • Group
  • Research
  • Publications
  • Teaching

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  • Mineral resources are among the most important natural resources that determine the socioeconomic growth and prosperity of a nation and its people, supporting a significant part of GDP through the manufacturing sectors by supplying raw materials for the primary, secondary and tertiary industries. Thus, exploring avenues for new mineral horizons is an ever-lasting challenge faced by exploration geoscientists throughout the globe to achieve a dynamic balance between demand and supply of minerals. However, mineral exploration is a high-risk enterprise in which failure is the norm and success is elusive with a significant factor of ‘chance’, which also involves huge costs. Therefore, precise delineation of mineral prospects by effectively narrowing down the search space is the need of the hour for the discovery of new deposits.
  • A great deal of metallogenetically relevant exploration datasets have been collected by various survey agencies in India, and the acquisition process is still ongoing. In the era of digital platforms and soft computing, the situation calls for creative, out-of-the-box thinking to push the frontiers of metallogenic data visualization, optimization and integration that will inevitably open up new vistas in mineral exploration. Consequently, I have focused my research on the use of soft computing tools for synthesis and effective interpretation of multi-source geoscience data (geological, geochemical, geophysical, Satellite & remote sensing), which makes it an interdisciplinary field, i.e. “geo-data science” or, “digital geology” that lie in the frontier areas of research between mathematical geology, computational geology and data-science.
  • My primary research interests are in Mineral Exploration with a holistic approach and applying state-of-the-art techniques of spatial data modelling, Prospectivity Mapping, Mineral Systems Analysis, Fractal Analysis, Geologic Remote Sensing and GIS. Over the past couple of years, I have been enthusiastic about working on machine learning approaches such as neural networks, support vector machines, random forests, etc. and applying them to mineral exploration.

  • Behera, S. and Panigrahi, M.K., 2022. Gold prospectivity mapping and exploration targeting in Hutti-Maski schist belt, India: Synergistic application of Weights-of-Evidence (WOE), Fuzzy Logic (FL) and hybrid (WOE-FL) models. Journal of Geochemical Exploration, 235, p.106963.
  • Behera, S. and Panigrahi, M.K., 2021. Gold Prospectivity Mapping in the Sonakhan Greenstone Belt, Central India: A Knowledge-Driven Guide for Target Delineation in a Region of Low Exploration Maturity. Natural Resources Research, 30(6), pp.4009-4045.
  • . Behera, S. and Panigrahi, M.K., 2021. Mineral prospectivity modelling using singularity mapping and multifractal analysis of stream sediment geochemical data from the auriferous Hutti-Maski schist belt, S. India. Ore Geology Reviews, 131, p.104029.
  • Behera, S. and Panigrahi, M.K., 2020, May. Application of various fuzzy inference networks to integrate mineral exploration datasets: Implication for gold prospectivity mapping in Sonakhan greenstone belt, India. In EGU General Assembly Conference Abstracts (p. 7576).
  • Behera, S., & Panigrahi, M. K., 2019, August. Exploration targeting for gold in Sonakhan, India using ArcGIS. In ESRI India User Conference, Kolkata. (Awarded as Best Poster)
  • Behera, S., 2019. Remote Mapping of Clay Alteration Zones in moderately vegetated Terrane using Landsat ETM + Data: A Case Study from Sonakhan Greenstone Belt, Central India. GEOS Annual Edition, Vol. 17, pp.50-55.
  • Behera, S., & Panigrahi, M. K., 2019, June. ASTER spectral characterisation for mapping alteration minerals in Sonakhan Greenstone Belt, India: An approach to regional scale reconnaissance survey of gold in a moderately vegetated terrane. In National Geo-Research Scholar Meet, Wadia Institute of Himalayan Geology, Dehradun.
  •  Behera, S., Panigrahi, M. K., & Pradhan, A., 2019. Identification of geochemical anomaly and gold potential mapping in the Sonakhan Greenstone belt, Central India: An integrated concentration-area fractal and fuzzy AHP approach. Applied Geochemistry, 107, pp.45-57.
  • Behera, S., & Panigrahi, M. K., 2018, December. Gold Favorability Modeling from Stream Sediment Geochemical Data using Fractal-Geospatial Approach: An Example from Sonakhan Greenstone Belt, India. In AGU Fall Meeting Abstracts (Vol. 2018, pp. V23I-0161).
  • Behera, S., & Panigrahi, M. K., 2018, September. Predictive modelling of stream sediment geochemical data for mapping gold prospects in a part of Sonakhan Greenstone Belt, Chhattisgarh, India. In Annual General Body Meeting of Indian Society of Applied Geochemists.
  • Ore-Forming Processes
  • Mineral Exploration
  • Mineral Economics
  • Mineral Engineering
  • Fuel Geology
  • Mining Geology
  • Environmental Geology
  • Structural Geology
  • GIS and Remote Sensing
  • Earth and Climate Science