TRIM4Post-Mining is a H2020/RFCS-funded project that brings together a consortium of European experts from industry and academia to develop an integrated information modelling system. This is designed to support decision making and planning during the transition from coal exploitation to a revitalized post-mining landscape, enabling infrastructure development for agricultural and industrial utilization, and contributing to the recovery of energy and materials from coal mining dumps. The smart system will be founded upon a high-resolution spatiotemporal database, utilizing state-of-the-art multi-scale and multi-sensor monitoring technologies that characterize dynamic processes in coal waste dumps related to timely, dependent deformation and geochemical processes. It will integrate efficient methods for operational and post-mining monitoring, comprehensive spatiotemporal data analytics, feature extraction, and predictive modelling; this will allow for the identification of potential contamination areas and the forecasting of geotechnical risks and ground conditions. For the interactive exploration of alternative land-use planning scenarios—in terms of residual risks, technical feasibility, environmental and social impact, and affordability—up-to-date data and models will be embedded in an interactive planning system based on Virtual Reality and Augmented Reality technology, forming a TRIM—a Transition Information Modelling System. This contribution presents the conceptual approach and main constituents, and describes the state-of-the-art and detailed anticipated methodological approach for each of the constituents. This is supported by the presentation of the first results and a discussion of future work. An anticipated second contribution will focus on the main findings, technology readiness and a discussion of future work.

The field tests of the SOLSA expert system at the bauxite mine (SODICAPEI-VICAT, South France, 15th to 30th September 2018) aimed to evaluate the workflow and individual instrumental parameters, mechanics of the drill rig, the core scanner (RGB, profilometer, VNIR-SWIR (final with XRF)), the benchtop system XRD-XRF, data architecture, data transfer, software and interaction with the (open-) databases. The focus was on iron oxyhydroxide and clay mineral rich lithologies, that is also present in Ni-laterite profiles. In total 65 m were drilled at two boreholes with a 90-100% core recovery on 52 m (80%). Core scanning recorded 40m/10h. The results on the undestroyed core surface are representative of the core. The XRD-XRF benchtop system is fast (5-7 min/sample) for validating and quantifying analyses on the regions of interest, defined by the core scanner. It will be installed at the drill site for immediate environmental analyses. Data connection was successful from drill to core-scanner. The hyperspectral database is performant for the lithologies present at this bauxite deposits. The sample database is operational based on international standards. Data superposition and fusion, and GUIs are under development.

On-line, real-time chemical and mineralogical analyses on drill cores are highly demanded by mining companies. However, they are a challenge because of drill core surface state and sample heterogeneities. We selected four rock samples: highly porous, siliceous breccia and serpentinized harzburgite coming from the base of a nickel laterite profile in New Caledonia which were sonic drilled, and fine grained, homogeneous sandstone and coarse grained granite which were diamond drilled and provided by Eijkelkamp Sonic Drill with unknown origin. The samples were analysed at five surface states (diamond or sonic drilled, cut as squares, polished at 6 and 0.25 mu m, powdered < 80 mu m) by portable XRF spectroscopy (pXRF) in mining and soil modes and portable infrared spectroscopy (pIR, Visible and Near Infrared-Short Wave Infrared range (VNIR-SWIR)). A total of 52 pXRF and 200 pIR analyses were performed per sample at each surface state. This study shows that the surface state has minor influence on the results of the portable instruments. By comparing pIR and pXRF results with laboratory devices (Raman spectroscopy, XRD with Rietveld refinement, XRF spectroscopy and ICP-AES), we evidence the lower and less accurate information obtained from handheld instruments in terms of chemistry and mineralogy. The porosity and grain size effect on the measurement need to be taken into consideration for on-line drill core analyses. We show that the combination of complementary analytical techniques helps to overcome the drawbacks of the core texture and of the precision of portable instruments in order to define the regions of interest (ROI) for mining companies. We also demonstrate that a precise pXRF calibration is mandatory and that the concentration of light elements (Si, Mg), even if not accurate, shows sufficient contrast along the lateritic profile for ROI definition.

In order to evaluate the instrumental parameters for the combined on-line-on-mine-real-time expert system SOLSA (http://www.solsa-mining.eu), portable and laboratory analyses were carried out on coarse granite, sandstone, serpentinized harzburgite and siliceous breccia. Each sample was studied at 5 different surface roughnesses (sonic or diamond drilled, cut, polished at 6 mu m and 0.25 mu m, sample powders). X-ray diffraction (XRD), portable Infra-Red (pIR) and X-ray-fluorescence (pXRF), and laboratory micro-Raman spectroscopy gave complementary and corroborating results. No major effect on the analyses was noted for the selected surface states. pXRF gave variable results except for the homogeneously serpentinized harzburgite, related to coarse or contrasting grain sizes or pores, small spot size (3 mm) and needs close-to-surface analyses. Portable IR (spot size 1.76 cm(2)) is carried out close to surfaces while Raman spectroscopy (1-2 mu m) is performed at distance. Sampling strategies have to be defined for each lithology. Major challenges for a combined on-line analysis are to adapt the specificities of the techniques to (1) analyse similar surface areas (from 2 cm(2) (pIR) to < mu m (Raman)), (2) smartly combine all the techniques into a single instrument, and (3) develop appropriate databases to reach a reliable "real-time" outcome results, which can be used for more precise geomodeling, and to rapidly define exploration and beneficiation parameters.