AI for Mining and Exploration

Applying AI advances to model complex mining processes & accelerate exploration studies

AIforMining

Mining is a data-rich domain with decades worth of data from explorations across the globe. As economic conditions change and mining technologies evolve, valuable opportunities may be discovered if the data pointing to the opportunities is easily accessible and analyzable. While recently acquired data is maintained in modern GIS databases, a large portion of historical exploration data is still lying in scanned documents, photographs and images making information retrieval and analysis a tedious and inefficient process. AI can help change this situation without costing a fortune.

More broadly, with AI:

Accelerators and Solutions

Exploration
  • Data acquisition
  • Data modeling
  • Mineral lead generation
Mining
  • Predictive maintenance
  • Throughput prediction
  • Process modeling
 
Utility solutions
  • Identifying and segregating geological files
  • Assay data identification & Mineral tagging
  • Geo-referencing and Chronological sorting
 

Service Catalog

We take up projects with an objective to deliver business value beyond the SOW. We achieve this by applying latest advances in AI research to serve enterprise needs. Our flexible engagement models - SOW based, Outcome based, Risk/Reward based, Long-term partnership – enable clients to pick complex problems. Some examples below:

  • Building an automated system to segregate geological documents from a corpus of scanned documents
  • Geo-referencing documents to identify the location, latitude and longitude referred to in a particular document
  • Building a continuously learning AI model that scores geological documents based on relevance to user search criteria
We build specific product solutions to enhance existing tools by integrating AI modules, to connect existing tools through AI based RPA. We also develop customized solutions and integrate with existing processes. Some examples below:

  • Integration of ‘Document seggregation’ modules to existing Document management systems that seggregate and identify documents of geological importance
  • Incorporate Natural Language Generation (NLG) modules with existing Information Management Systems to generate regulatory submissions in a particular format
  • Building an automated email alert system for updates regarding competition, industry and regulations in an enterprise’s specific area of interest

We develop customized datasets by collating data from various sources such as open source datasets, patents, journal, academic papers using NLP techniques. We also set up and manage data pipelines originating from diverse data sources that feed AI models while maximizing computational efficiency. Some examples below:

  • Mining literature using NLP techniques to build a database for satellite imaging models
  • A weekly email alert summarizing the new articles, journals, patents published in relation to existing models’ infrastructure and architecture
Aganitha team has also built unique approaches of applying AI techniques in scenarios where only small datasets are available and in extracting knowledge graph for large scale modeling.

We evaluate processes and tools adopted across the enterprise value chain, identify opportunities where AI can bring in efficiencies, draft roadmaps to drive AI adoption maturity, partner with enterprise in adopting AI into operational processes.