logo


Diamond Exploration Database

The CPRM data was organized into a Postgis database and interfaces were created to access the information using a geospatial framework.

Since the data is stored into a database, it can be extracted in any format you wish to be read by your favorite toll (GIS software, web apps, Google Earth, etc).

Here you can see a basic data analysis with the goal to identify new prospects. It is basic but effective.

The goal was to demonstrate how to integrate spatial data and target selection based on existing data. Much more can be achieved.

It is easy to extract the data and present them as graphics too.

See some results extracted from the database:



Interactive Map

The map, created using Leaflet, will be the portal to the geospatial information.
When started we will see at the top-right we have the layer selector. They are divided into the following categories:
- Kimberlites Classified by the presence of specific indicator mineral (in green).
- KIM samples Classified by the sampling environment (in purple).
- Diamond occurences All diamond occurences in Brazil (in orange).
- Mineral geochemistry Mineral Geochemistry data from DIM (in light purple).
Clicking on any element will bring each individual information in a popup window.
Mineral chemistry and KIM sample will have a link to more detailed information about that location.
Thus, in a practical way, we have access to the database.





Integrating results

Based on our data we can make the following initial assumptions:
Spatial distribution of DIM within the diamond stability filed.
Spatial distribution of diamond occurences from primary sources.
Spatial distribution of diamond occurences from unknown sources.
Diamond occurrences associated with positive DIM within the pipes nearby.
Evaluation of the other diamond occurences not directly associated with pipes within the diamond stability field nearby.
Prospecting of pipes within the diamond stability field to explain the presence of diamonds not associated with primary sources.

The graphics show the distribution of G10 from the mineral geochemistry data within the diamond stability field. On the map we can see the spatial distribution of G10 samples in red (full dataset in blue).


The graphics show the distribution of Cr Spinel from the mineral geochemistry data within the diamond stability field. On the map we can see the spatial distribution of Cr Spinel samples in red. (full dataset in blue).


Spacial distribution of diamonds from known and unknown sources.


Spatial correlation between diamond occurences and DIM bearing pipes (G10 and Cr spinel).


Spatial correlation between diamond and pipes bearing diamonds nearby.


Potential for the discovery of new diamond bearing pipes.

Based on the information gathered above, we have potential for the discovery of new diamond bearing pipes in Roraima, central Mato grosso, Mato Grosso and Goiás border, Tocantins northeast/Piaui southwest, Espinhaço in Minas Gerais and Chapada Diamantina in Bahia.

Also, the Tapajós, Carajás and Mato Grosso do Sul central north shows some potential for new discoveries.

The regions with proven diamond occurrences associated with pipes have also potential to be expanded with the discovery of new pipes.



Kimberlite Locations and Diamond Occurences on Google Earth

Use the procedure below to load the KML directly from the database into Google Earth:

Open the menu Add>Network Link and the following window will appear.


Enter the field name and link http://amazeone.com.br/prods/diamante/ocorrencias.php into their respective fields as shown below.



Repeat the same for kimberlites and diamond bearing Kimberlites using: http://amazeone.com.br/prods/diamante/kimberlitos.php and http://amazeone.com.br/prods/diamante/kimberdia.php and you are ready.



.