Herrington, R, Alonzo, D, Armstrong, R, Pocaan, J, Beltran, A, Brito-Parada, P, Cording, H, Dalona, IM, Dybowska, A, Graham, A, Guihawan, J, Jungblut, A, Madamba, RS, Magliulo, M, Maulas, K, Mondejar, A, Orbecido, A, Paglinawan, F, Plancherel, Y, Prasow-Emond, M, Promentilla, M, Rasheed, S, Resabal, V, Santos, A, Schofield, P, Stretton, A, Suelto, M, Sumaya, NH, Tabelin, C, Villacorte-Tabelin, M & Yuen, A 2026, 'A Bio+Mine Digital Twin approach to mine closure monitoring', in AB Fourie, G Boggs, J Heyes & M Tibbett (eds), Mine Closure 2026: Proceedings of the 19th International Conference on Mine Closure, Australian Centre for Geomechanics, Perth, pp. 1-13, https://doi.org/10.36487/ACG_repo/2615_120
(https://papers.acg.uwa.edu.au/p/2615_120_Herrington/)
Abstract: Mine closure demands multidomain, temporally resolved data, yet conventional workflows leave these datasets fragmented and underused when decisions must be made. The Bio+Mine Digital Twin project, based on work carried out at the Sto. Niño legacy mine site in the Philippines, will address this by integrating data from 4 domains into an interrogable data cube from which artificial intelligence (AI) and machine-learning tools can identify cross-domain relationships and model site trajectories through time. A central aim is to establish where cheaper proxies can substitute for intensive sampling. Because the method and learned relationships will be recalibrated to each new site, the outcome will be a modular, transferable workflow template that supports consistent, evidence-based closure practice.