Union Ministry of Mines secretary VL Kantha Rao stressed upon the need for the use of new age technology especially Artificial Intelligence (AI) and Machine Learning (ML) in accelerating  mineral exploration activities in our country. 

The Geological Survey of India (GSI) hosted a workshop on “Emerging Technologies in Mineral Exploration” at GSI Training Institute, Hyderabad, today.

The workshop was inaugurated by the Ministry of Mines secretary Rao.

He said that the conventional ways to process the geoscientific data are time consuming, expensive and sometimes limited in their accuracy.

With the advent of new technologies like AI and ML, geological data are gradually characterized by elements of big data involving quantity, value, diversity, and timeliness.

In the arena of big-data technologies, Artificial Intelligence (AI) and Machine Learning (ML) methods, along with the development of high-performance computing have proven to be effective in finding good prospective mineral models.

He urged the Govt. PSUs and private stakeholders to make the best use of vast geoscientific data from National Geoscience Data Repository (NGDR) platform of GSI.

Rao also directed to arrange 20 such workshops in different parts of the country to promote the ecosystem of exploration using AI and ML.

Rao advised  to take  advantage of Drone survey for mapping to save time and appealed to all notified exploration agencies and start-ups working in the field of exploration to put special focus on critical minerals, potash and concealed deposits.

He urged the State Governments to work in tandem with GSI and continue to organize such workshops as follow up action.

Addressing the gathering, GSI director general Janardan Prasad,emphasized the vital role of mineral exploration in fostering the economic development of the country. 

GSI plans to deploy advanced technologies like drones, AI, and ML for more efficient and accurate mineral prospecting, saving valuable time and resources while uncovering concealed deposits.

He said that with the advent of AI and ML technology in the field of mineral exploration, integration of various datasets using time-tested Machine learning algorithms are gaining popularity because of their accuracy in delineating potential areas for mineralization.

Especially AI has assisted the users for generation of 4D modelling by adding time component which allows reproducing the dynamic evolution of geological structures and reconstructing the past deformation history of geological formations.