Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-289-2023
© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
Model description paper
| 
11 Jan 2023
Model description paper |
| 11 Jan 2023
| 11 Jan 2023
The Intelligent Prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration
Related authors
Geosci. Model Dev., 15, 1477–1497, 2022
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, https://doi.org/10.1088/1748-9326/aae9b1, 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, https://doi.org/10.2118/102369-PA, 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, https://doi.org/10.1016/s0016-7061(97)00072-4, 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
https://doi-org.stanford.idm.oclc.org/10.1007/s11053-022-10030-1 (last access: 16 March 2022), 2022.
