As we progress towards the energy transition we face a shortfall in the metals required to meet decarbonisation targets. S&P Global Market Intelligence predicts annual global copper demand will nearly double to 50 million tonnes by 2035, yet global exploration spend and discovery rates remain well below historical peaks and the average time from discovery to mine production has ballooned to 15.7 years (S&P Global Market Intelligence).
2022 global exploration spend was a mere US$11.24 billion, barely 50% of the 2012 peak (US$20.52 billion) with US$2.9 billion (26%) directed to grass roots exploration, well short of 41% in 2007. Unsurprisingly, discovery rates have faltered, as just 65 initial resources were announced in 2022, compared with 175 in 2012 (S&P Global World Exploration Trends 2022).
Given this investment scenario, explorers must adapt and find cost-effective, innovative ways to efficiently and effectively make discoveries. We must seek improvements in data collection and develop effective methods for the timely communication of findings to key stakeholders and decision makers.
One important area that has been a focus for developing more innovative and better methods of data collection and analysis is at the drill site. Various lab-at-the-rig type solutions (discussed elsewhere in this edition) can be paired to innovative workflows for field data collection, allowing a seamless flow of ‘live’ data to inform exploration decisions in near real time.
One such example is the implementation of near real time modelling to influence drilling decisions. Key downhole data can be modelled as it is logged using implicit modelling software. By implicitly modelling logged estimates of sulphide species, sulphide abundance, vein abundance, alteration mineralogy and intensity alongside existing data we can better inform decisions in real time on navigational drilling, end of hole depth, design of the next drill hole and/or broader programme strategies.
Given turnaround times for assays can be longer than the length of a drilling programme, it is possible to utilise well-calibrated core scanning, pXRF or spectrometer data as interim inputs to the near real time model. Data derived from these can overprint the visually estimated data to increase the confidence of models, in turn being overprinted as assay data is received.
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This thought leadership piece is in partnership with the Mining Journal's Future of Exploration.
