MOVING TOWARDS CONTINUOUS PROCESS MANAGEMENT IN MINERAL RESOURCE EXTRACTION

Transcription

1 REAL-TIME MINING MOVING TOWARDS CONTINUOUS PROCESS MANAGEMENT IN MINERAL RESOURCE EXTRACTION FUTURE MINING CONFERENCE SYDNEY, 5 TH OF NOVEMBER 2015 JÖRG BENNDORF, DELFT UNIVERSITY OF TECHNOLOGY ON BEHALF OF THE REAL- TIME MINING CONSORTIUM

2 PARTNERS 2

3 BACKGROUND Potential of critical raw materials in Europe classified by deposit sizes (PROMINE) 3

4 BACKGROUND The main barriers to overcome for the successful economic exploitation: o effective grade control, which will maximize resource potential along the whole value chain o minimization of handling zero-value material introduced by dilution, thus reducing unnecessary expenditure of energy and financial resources and o management and control of the geological uncertainty due to limited information available. 4

5 Main Source of Risk: Geological Uncertainty Limited Information 1: Complex Geology Tight product specifications 5 Foto: Neves Corvo Mine

6 THE TRADITIONAL APPROACH SILO 1 SILO 2 SILO 3 SILO 4 SILO 5 Exploration and Data Collection Resource Modelling Mine Design Equipment Selection Reserve Estimation Production Scheduling and Operation Processing and Sale 6

7 NEW INFORMATION POTENTIAL Increasing Availability of Sensor Based Online Data: Material characterization (geo-chemical, textural and physical properties) Equipment performance, upstream and downstream (e.g. efficiency, down-time) Equipment location and material tracking (e.g. GPS, UPS) 7 Foto: MIBRAG

8 THE REAL-TIME MINING APPROACH 8

9 THE REAL-TIME MINING PROJECT OBJECTIVE Overall objective: to develop an innovative technical solution for resourceefficient and optimal high precision/selective mining in geologically complex settings using online data. Hypothesis: recovery can be significantly increased by changing mineral resource management from a batch-type to a near-continuous model-based controlled activity 9

10 REAL-TIME MINING BUILDING BLOCKS 10

11 EXTRACTION METHODS RTM CYCLIC EXTRACTION Core Sample Drill Hole Control decision points Sensors for material characterization Sensors for machine performance Sensors for geo-referencing (positioning and material tracking) Ore zone Muckpile Selective Loading Scheduling LHD Orepass Ore Transfer BIN Crusher Dispatching BIN A B C 11

12 REAL-TIME MINING REAL-TIME DATA Lead: TU Delft (Lead: RWTH Aachen) Lead: SonicSampDrill 12

13 TEST CASE 1 Reiche Zeche Research Mine Freiberg, Germany Source: Description Test Site Mine Reiche Zeche, Freiberg, Saxony, Germany provided by TU Bergakademie Freiberg

14 TEST CASE 2 Neves Corvo Copper Mine Portugal (Massive sulphide ore and associated stockwork zone) Source: lundin mining

15 CASE STUDY UPDATING Grade Control (GC) Model 1. Reconcile Extracted Blocks GC Model 2. Update Scheduled Blocks Predict Extraction Performance 1. Improve production forecasts Reconcile Sensor 2. Optimize control decisions (proact) Measure 15

16 CASE STUDY UPDATING Updated Block Model Reconciliation Software replace Prior Block Model Measurement File Forward Prediction Predicted Measurements Actual Measurements Material Tracking/ Material Flow Simulation in the Mine Sensor Source: Wambeke, T & Benndorf, J (2015). Data assimilation of sensor measurements to improve production forecast in resource extraction. In s.n. (Ed.), Proceedings of the 17th annual conference of the international association for mathematical geosciences, IAMG2015 (pp ). Houston: IAMG.

17 CASE STUDY UPDATING Mean Field x SMU scale x Simulations 17

18 CASE STUDY UPDATING Mean Field x SMU scale x Simulations 18

19 CASE STUDY OPTIMIZATION Forecast of process KPI s for a given extraction schedule Optimal value Daily production in kt Penalty applied Acceptable range Optimal value Grade in % Acceptable range

20 CASE STUDY OPTIMIZATION Simulation based optimization of extraction schedule to improve extraction performance

21 ADVANCE WITHIN RTM 21

22 THREE TAKEAWAYS 1. Real-Time Mining is an exciting European Union funded H2020 project and integrates multiple disciplines 2. Making best use of online production information can lead to a shift in paradigm from a batch-type to a continuous process monitoring and control and can create significant value 3. Real-Time Mining will demonstrate this hypothesis in full industrial scale case studies (TRL 6/7). 22

23 Thank you for your attention and Glückauf 23