Outotec OreMet Optimizer

Transcription

1 Outotec OreMet Optimizer , Luleå, Sweden Outotec Minerals Processing, Antti Remes Vesa-Pekka Takalo Matti Talikka OreMet Optimizer for mining value chain analysis ore to metal Geometallurgical modelling of concentrator plant for each ore types and plant operating scenarios The main discrete events, starting from extraction and ending up with concentrate storage are evaluated separately Their throughputs and stream compositions are simulated with the digital plant model corresponding operating expenses (OPEX) in $/ton of each stage are used for the calculation model The value of the final concentrate is calculated using the Net Smelter Return (NSR) formula 2 1

2 Determination of Value VPTakalo EXPLOITABLE BLOCK ORE CONCENTRATE Volumetric capacity Properties of the rock Rock mineralogy Official authorization Social license to operate CapEx OpEx Dry metric tonnes Metal and other valuable contents Deleterious and disturbing element contents Moisture Treatment charge Freight 3 Example: average orebody vs. domains Average orebody % Cu, 0.3 ppm Au Recovery 83 % Cu, 60 % Au BWi 20 Domain tonnes. Similar to average ore body. Domain % Cu Amenable to ore sorting: 30 % mass recovery 95 % Cu Flotation recovery 80 % Cu 30 % shorter milling time or smaller milling capacity Domain % Cu, 0.6 ppm Au Recovery 84 % Cu, 65 % Au Gravity circuit / flash flotation increases the overall gold recovery by 5 % Additional domain % Cu Not feasible to process without sensor-based sorting Amenable to ore sorting: 60 % mass recovery 70 % Cu BWi 14 (hard waste rock removed) Flotation recovery 80 % Cu 60 % shorter milling time or smaller milling capacity 4 2

3 Challenging the traditional mine value chain with geometallurgy An average ore body does not exist! Traditional approach: Single value/point does not represent the average ore boby. Does not recognize variations in operational circumstances. Information silos. Poor communication between disciplines and systems. Geometallurgical approach: A holistic approach, which intergrates geological, mining, metallurgical, environmental, economic and other relevant information with an aim to optimize the efficiency of utitization of an ore body. Aim to optimize the mining value chain. - Economic return, CO 2 emissions, energy and water consumption, - Supports risk management. Communication with different disciplines is essential. Recovery % Head grade, Ni% 5 Simulation of the processing scenarios and value chain analysis 6 3

4 Example: Average orebody vs. domains Recovery Average ore body, 83% Domains 1-3, 81.5% Domain 1: No changes Domain 2: Add ore sorting Domain 3: Add gravity circuit and flash flotation Domains 4, 79% Domain 4: Add ore sorting Value (NSR, non-discounted) Average ore body, 115 MUSD Domains 1-3, 143 MUSD Value increases 28 MUSD Domain 4, 145 MUSD Value increases 2 MUSD. Extends LOM Aim to maximize the value over the mining cycle. 7 Outotec OreMet Optimizer A unique ability to simulate the full processing cycle from ore to metal Ore characterization Based on HSC Chemistry software including OreMet Optimizer module Optimization can be based on e.g. economics, flowsheet performance, CO 2 emissions, water and energy consumption, LCA, and enables the selection of most sustainable process route Digital concentrator plant Enables time reduction in greenfield projects e.g. for scoping level and preliminary economic studies Quick and transparent way to compare potential development scenarios including high level opex and capex estimations with main equipment list Simulation, optimization and modifications of existing brownfield operations 8 4

5 Process economical viability study Value of the concentrate is calculated using the Net Smelter Return formula Operating expenses (OPEX, $/ton) for each processing stage are utilized VALUE ADDING CHAIN: Total operating cost Total operating profit (non-discounted) 9 Simulation from ore to concentrate 10 5

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8 Case example Greenfield case example: Cu sulphide concentrator 15 Internal Presentation name, Author Two processing options Bench scale flotation test for two grind sizes Regrind in 20 or 10 microns Simulation models for two processing options different concentrates different OPEX / CAPEX 16 8

9 Cu sulphide plant OreMet optimization study: phase I EUR/ton INCREASE IN OPEX % INCREASE IN RECOVERY 15.7 MEUR/year INCREASE IN OPERATING PROFIT 17 Cu sulphide plant OreMet optimization study: phase II The preliminary results were good Next the process optimization is continued with intermediate regrinding size (15 microns) more detailed flotation and dewatering CAPEX / OPEX studies different ore types 18 9

10 SUMMARY Discrete event based approach OreMet Optimizer incorporating a digital plant, provides a tool to assess the significance of individual events and their response to the optimization throughout the mining value chain Fast comparison between different processing sequences becomes transparent An example how this platform is used to define the most economical and sustainable process route for the project, with a fast turnaround time, was shown 19 10