Method for Water and Moisture Management for a Mining Operation

Abstract

Wet conditions pose a plurality of hazards for mining operations. For example, mining of wet ore is more costly from a variety of perspectives. Furthermore, available water quantity and quality can impact mining operations. Described herein are methods for measuring or determining “wetness” of various sections, locations and/or segments of a mining operation as well as methods for predicting not only future wetness but also the impact of both current and future wetness on mining operations. This information is used to direct specific interventions and outcomes, for example, decisions regarding vehicle routing, areas to be mined and interventions taken regarding water reservoirs. Also described are methods where algae growth data is measured and subjected to multivariate analysis for predicting future algal bloom. Finally, a method for predicting tailings dam failures comparing results from a tailing pond spectrophotometer and a seepage spectrophotometer is described.

1 . A method for determining sections of a mining operation impacted by wetness comprising:
 positioning a plurality of moisture sensors within the mining operation, each respective one moisture sensor arranged to measure moisture at a specific location within the mining operation;   positioning a plurality of groundwater level sensors within the mining operation, each respective one groundwater level sensor arranged to measure groundwater levels at a specific location within the mining operation;   positioning a plurality of water flow sensors along one or more water flow routes impacting the mining operation, each respective one water flow sensor being positioned at a location along a water flow route and measuring flow rate and volume of water at said location;   said sensors reporting moisture, groundwater level and water flow data from the mining operation to a control system,   said control system analyzing said moisture, groundwater level and water flow data and determining when wetness at a given location within the mining operation is outside of an acceptable range.   
     
     
         2 . The method according to  claim 1  wherein the control system determines a wetness map of the mining operation. 
     
     
         3 . The method according to  claim 2  wherein the wetness map indicates optimal areas for ore extraction and blasting during wet mining conditions. 
     
     
         4 . The method according to  claim 1 , further comprises positioning a plurality of water level sensors in one or more water sources of the mining operation. 
     
     
         5 . The method according to  claim 1 , further comprising providing mine dewatering pump data to the control system for projecting water volumes within specific reservoirs as well as wetness of specific locations. 
     
     
         6 . The method according to  claim 1 , wherein the control unit generates a functional map of the mining operation which indicates which locations are currently suitable for transport and which locations are suitable for ore extraction. 
     
     
         7 . The method according to  claim 1 , wherein the control unit receives weather forecast data. 
     
     
         8 . The method according to  claim 7 , wherein the control unit generates a predicted functional map further comprising projected weather forecast data and/or historical trends. 
     
     
         9 . The method according to  claim 1 , further comprising seismic sensors and/or geotechnical sensors reporting ground and/or slope stability information to the control unit for routing mine vehicle traffic. 
     
     
         10 . The method according to  claim 1 , wherein the control unit is arranged to collect GPS data from mine vehicles. 
     
     
         11 . A method for mining operation water management comprising:
 providing a plurality of water level sensors and positioning each respective one water level sensor in a water source associated with a mining operation;   
       providing a plurality of water flow sensors and positioning each respective one water flow sensor at a location along a water flow route and measuring flow rate and volume of water at said location;
 said sensors reporting water volume and water flow data from the mining operation to a control system, 
 said control system forecasting wetness within the mining operation by projecting water volumes within specific water sources and selecting locations for water pumping and adjusting water pumping rates based on said forecasted wetness. 
 
     
     
         12 . The method according to  claim 11  wherein the control unit receives weather forecast data, historical data and local trends. 
     
     
         13 . A method for training a machine learning algorithm to predict tailings dam failure comprising:
 (a) providing a tailings pond spectrophotometer in a tailings pond, said tailing pond spectrophotometer recording a first tailing pond spectrum of water in the tailings pond at a first time point and reporting said first tailings spectrum to a control unit;   (b) providing a seepage spectrophotometer in an associated water source, said seepage spectrophotometer recording a first seepage spectrum of water in the associated water source at said first time point and reporting said first seepage spectrum to a control unit;   (c) said control unit storing said first tailing pond spectrum and said first seepage spectrum;   (d) repeating steps (a)-(c) until tailing pond spillage occurs;   (e) said control unit performing a multivariate comparison of collected tailing pond spectra and seepage spectra over time for spectral regions of dissimilarity, said regions of dissimilarity being predictive of tailing pond spillage.   
     
     
         14 . A method for preventing tailings dam failure comprising:
 (a) providing a tailings pond spectrophotometer in a tailings pond, said tailing pond spectrophotometer recording a tailing pond spectrum of water in the tailings pond at a first time point and reporting said spectrum to a control unit;   (b) providing a seepage pond spectrophotometer in a seepage pond, said seepage pond spectrophotometer recording a seepage pond spectrum of water in the seepage pond at said first time point and reporting said spectrum to a control unit;   (c) said control unit receiving said tailing pond spectrum and said seepage pond spectrum, said control unit performing a multivariate comparison of the tailing pond spectrum and seepage pond spectrum for regions of dissimilarity, and if said regions of dissimilarity are found, performing tailing dam repair.