Predictive Vehicle Dump Location Planning for Copper Heap Leaching
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Solution Overview
Problem
Existing mining operations face challenges in optimizing heap leaching processes due to complex interactions between mineralogy, chemical, and physical factors, leading to inefficiencies in copper recovery and increased costs, as current systems lack the ability to dynamically adjust to changing variables and optimize ore routing and processing.
Innovation Solution
A system that utilizes predictive models trained on historical data, including mineralogy, irrigation, and environmental data, to forecast copper recovery and adjust parameters in real-time, optimizing heap leaching operations by improving ore placement and processing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional ore routing based on mineralogy is used, then processing simplicity is maintained, but copper recovery optimization is limited
Solution Approach 1:
The system changes multiple parameters simultaneously including ore placement location, leach solution flow rate, aeration rates, and chemical additives based on real-time sensor data and predictive models, moving beyond traditional fixed mineralogy-based routing to dynamic parameter optimization
Solution Approach 2:
The patent replaces traditional mechanical/mineralogy-based ore routing with a data-driven system using sensors, predictive analytics, and automated control to determine optimal processing parameters and ore placement strategies
2Productivity
If more acid is provided to release all contained copper, then copper recovery is improved, but acid cost increases
Solution Approach 1:
The system uses real-time sensor feedback on acid consumption, copper dissolution rates, and solution chemistry to dynamically adjust acid addition rates, ensuring acid is provided only when and where needed for optimal recovery without excessive consumption
Solution Approach 2:
The system applies partial acidification strategies, providing just sufficient acid to achieve economically viable copper recovery rather than attempting to extract all contained copper, optimizing the balance between recovery rate and acid cost
3Productivity
If atmospheric oxygen is used for leaching sulfides, then oxidation potential is sufficient, but interior oxygen starvation reduces copper recovery
Solution Approach 1:
The system introduces intermediate oxygen delivery mechanisms including subsurface aeration systems, oxygen-permeable leach pads, and controlled air injection points within the heap interior to bridge the gap between atmospheric oxygen and oxygen-starved interior zones
Solution Approach 2:
The patent transitions from surface-only atmospheric oxygen exposure to three-dimensional oxygen distribution throughout the heap interior using vertical aeration pipes, layered oxygen injection, and depth-dependent leach pad design
4Productivity
If chalcopyrite is sent to froth flotation and smelting, then copper recovery is reliable, but processing cost increases
Solution Approach 1:
The system changes key parameters including particle size distribution through selective crushing, leach solution chemistry composition, temperature, and aeration rates to optimize chalcopyrite leaching performance and make it economically competitive with flotation-smelting routes
Solution Approach 2:
The patent applies preliminary size reduction and ore preparation steps specifically tailored for leaching, including selective crushing to liberate chalcopyrite particles and pre-conditioning of ore before leaching to enhance recovery efficiency
5Productivity
If ore is placed on leach dump without precise location tracking, then operation simplicity is maintained, but ore placement optimization is reduced
Solution Approach 1:
The patent replaces manual or simple mechanical tracking of ore placement with automated GPS/satellite-based location systems integrated with predictive models that automatically determine optimal dump locations based on real-time heap characteristics and forecasted performance
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances copper recovery rates and reduces operational costs by providing real-time adjustments to optimize chemical and physical forces in leaching processes, leading to more accurate predictions and improved mining efficiency.
Implementation Method 1
copper oxide and carbonate ores (e.g., cuprite, chrysocolla, malachite, and azurite) may be very amenable to leaching. Exposure to dilute sulfuric acid carries sufficient chemical energy to put the copper into solution
Implementation Method 2
When ferric iron oxidizes copper sulfide minerals, the ferric iron is converted to ferrous iron. The ferrous iron is converted back to ferric iron to further oxidize copper sulfide minerals
Implementation Method 3
Air or oxygen may either be introduced by physically piping or blowing it into the ore structure
Implementation Method 4
The system may include a sensor on the haul truck, GPS, a beacon, or a dispatch system that provides data about the location of the haul truck and/or that the haul truck has completed a dump
Data Source
AI summary
The method may comprise receiving historical data (e.g., mineralogy data, irrigation data, raffinate data, heat data, lift height data, geographic data on ore placement and/or blower data); training a predictive model using the historical data to create a trained predictive model; adding future assumption data to the trained predictive model; running the forecast engine for a plurality of parameters to obtain forecast data for a mining production target; comparing the forecast data for the mining production target to the actual data for the mining production target; determining deviations between the forecast data and the actual data, based on the comparing; and changing each of the plurality of parameters from the forecast data to the actual data to determine a contribution to the deviations for each of the plurality of parameters.