Mineral potential map by a knowledge driven GIS modelling: An example from Singhbhum copper belt, Jharkhand
Table 1
| Lithology-id |
Score |
lithological units |
| 1000 |
9 |
Soda Granite |
| 1950 |
9 |
Chlorite Schist ( Singhbhum Group) |
| 3075 |
9 |
Chlorite Schist ( Dhanjori Group) |
| 3100 |
9 |
Talc chlorite schist |
| 2000 |
8 |
Hornblende schist and Epidiorite (Singhbhum Group) |
| 3200 |
8 |
Hornblende schist and Epidiorite (Dhanjori group) |
| 1900 |
6 |
Younger ultrabasics (Singhbhum Group) |
| 3050 |
6 |
Ultrabasics ( Dhanjori Group) |
| 2100 |
6 |
Mica schist with Hornblende schist |
300/500/600
/2200/2300/
2600/3300/
3400/3500/
3600/4100/
4150/4200
/4300/4400
/4500/4700
/5000/5100 |
2 |
Rest of the rocktype |
GIS data processing
Compilation of the spatial data was followed by processing of data for extraction of evidences critical to the prognostication of copper deposits, through the guidelines imposed by the exploration model. The principal approaches to process the data, prior to data combination are illustrated below:
- Map reclassification, to simplify the complex geological map to small number of simplified units suitable for modelling.
- Generation of proximity maps showing distance to linear or polygonal features such as formation contacts, lineaments, shear zone, aeromagnetic and ground geophysical anomalies, etc (buffering).
- Extraction of bed rock geochemical anomalies of copper
- Generation of anomaly maps for the wall rock alteration elements
- Combining the relevant layers of
evidences to generate the intermediate Factor Maps namely,
Lithological Factor, Geochemical Factor, Structural Factor,
Alteration Factor and Geophysical Factor.
Lithological Factor
Analysis of host lithology
The sulphide mineralisation in the Singhbhum belt is broadly considered to be confined within the Dhanjori Group of rocks south of the Shear Zone and Singhbhum Group of rocks north of the shear zone. Both overlie the Singhbhum granite unconformably. The Dhanjori Group consists of volcanics, volcanoclastics and lithic tuffs those underwent a low grade metamorphism. The Singhbhum Group consist of high grade mica schist, hornblende schist and quartz granulite at the bottom and comparatively less metamorphosed. The phyllites are considered to be derivative of volcanic tuffs.
The sulphide mineralisation is considered to be associated mainly with the meta-volcanics and meta-tuffs of Singhbhum and Dhanjori Groups, which has been remobilised and concentrated during the later metamorphic processes. Though mineralisation occurs in almost all the rock types of these stratigraphic horizons, the borehole data reveals that soda granite, chlorite and sericite schist and altered basic volcanics are the most favourable host of copper mineralisation.
The geological map, originally containing 28 lithounits, was reclassified into the following units with a new attribute lithology-id added to the polygon attribute table (PAT). A new attribute score signifying relative importance of the mapunits on a relative scale of 1 to 10 is also added. The classified units and associated scores are illustrated below (Table 1).
The coverage is rasterised on the basis of the attribute score.
Analysis of favourable contacts
The detailed exploration in this terrain reveals that the contact between metasediments and metavolcanics are generally mineralized to a varied extent. The favourable contacts were buffered at an interval of 250m and two new attributes contact-id and score added to the PAT (Table 2). The coverage is rasterised on the basis of the score.
Table 2
| Contact-id |
Score |
Contact between |
| 1 |
9 |
Soda granite, chlorite scist and talc chlorite schist |
| 2 |
8 |
Hornblende schist and epidiorite |
| 3 |
6 |
Ultrabasics and mica schist |
| 4 |
2 |
Contacts with rest of the rocktype |
These two layers representing the simplified geological map and proximity to favourable contacts are spatially combined by additive union after giving map score 8 and 6 respectively to produce intermediate map. The intermediate map divided by the total score (8+6 = 14) to produce the Lithological Factor Map (Fig 2).