Articles | Volume 16, issue 1
Model description paper
11 Jan 2023
Model description paper |  | 11 Jan 2023

The Intelligent Prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration

John Mern and Jef Caers

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Cited articles

Agusdinata, D. B., Liu, W., Eakin, H., and Romero, H.: Socio-environmental impacts of lithium mineral extraction: towards a research agenda, Environ. Res. Lett., 13, 123001,, 2018. 
Bickel, J. E., Smith, J. E., and Meyer, J. L.: Modeling dependence among geologic risks in sequential exploration decisions, SPE Reserv. Eval. Eng., 11, 352–361,, 2008. 
Brechtel, S., Gindele, T., and Dillmann, R.: Probabilistic decision-making under uncertainty for autonomous driving using continuous POMDPs, in: 17th international IEEE conference on intelligent transportation systems (ITSC) IEEE, 8–11 October 2014, Qingdao, China, 392–399, 2014. 
Brus, D. J. and de Gruijter, J. J.: Random sampling or geostatistical modelling? Choosing between design-based and model-based sampling strategies for soil (with discussion), Geoderma, 80, 1–44,, 1997. 
Caers, J., Scheidt, C., Yin, Z., Mukerji, T., and House, K:. Efficacy of Information in Mineral Exploration Drilling, Nat. Resour. Res., 31, 1157–1173 (last access: 16 March 2022​​​​​​​), 2022. 
Short summary
In this work, we formulate the sequential geoscientific data acquisition problem as a problem that is similar to playing chess against nature, except the pieces are not fully observed. Solutions to these problems are given in AI and rarely used in geoscientific data planning. We illustrate our approach to a simple 2D problem of mineral exploration.