Journal of Geological Society of India (Online archive from Vol 1 to Vol 78)

Shakeel Ahmed ¹, B. C. Sarkar ², Indranil Roy ²

Affiliations
1 National Geophysical, Research Institute, Hyderabad - 500 007, IN
2 Indian School of Mines, Dhanbad, IN

Abstract

No Abstract.

Full Text

   

B. C. Sarkar ¹, Indranil Roy ²

Affiliations
1 Department of Applied Geology, Indian School of Mines, Dhanbad - 826 004, IN
2 Central Ground Water Board, Guwahati, IN

Abstract

The prime purpose of orebody modelling is to reliably estimate the distribution of in situ and recoverable tonnages and grades of a mineral deposit. Conventional methods of estimation, such as polygonal, triangular, crosssectional and distance weighting provide local estimates of an ore body. However, such estimates are not error associated. Classical statistical techniques provide error of estimation but ignore spatial relationships, A thorough geostatistical estimation with careful attention to geology of mineralization provides not only an adequate global reserve estimate but also a more reliable block-by-block mineral inventory with associated confidence in the block estimates. Such estimates are crucial for short- and long-term planning for exploration of mineral deposits to maximise net return on investment. Kalta iron ore deposit, located in the state of Orissa, has been studied for resource evaluation using geostatistical approach taking into account the geological parameters wherever necessary. Using exploratory drill hole information, a study starting from statistical distribution modelling through semi-variography to generation of ore inventory and gradetonnage relationships has been carried out to highlight the effectiveness of such modelling.

Keywords

Geostatistics, Resource evaluation, lron Ore, Grade-Tonnage, Kalta, Orissa.

Full Text

     

Indranil Roy ¹, B. C. Sarkar ¹

Affiliations
1 Department of Applied Geology, Indian School of Mines, Dhanbad - 826 004, Jharkhand, IN

Abstract

Geological knowledge of associations between field evidence and deposit types for a range of iron ore deposits have been consolidated and structured into a rule-based prototype system, MODELER that is able to assist exploration geologist for diagnosing iron ore deposit types. The system contains knowledge on eighteen deposit models represented by eighteen compound rules based on the concepts of type area and genetic type. This paper focuses on the design and development of the system and its application to five iron ore deposits from eastern India.

Keywords

Expert System, Prototype, Iron Ore Deposit Types, Eastern India.

Full Text