Patent Application
20240084702
In most cases, is a convention accepted practice in the engineering exercise to plan and design infrastructure based on historic climate data records. The road design will consider the presence of snowmelt and floods during wintertime in the area of construction, as well as the water level in the near streams. The construction of bridges over rivers will take in consideration, among different technical information, discharge flows, soil moisture, extreme high and low temperature. In the dam designs, the hypothetical storms are defined with the Probable Maximum Precipitation event. Under the scenario of climate change, the historic data may no longer be appropriate to predict futures climate events, as it does not capture trends that climate change can pose.
The climate of mountain regions plays an important role in numerous environmental systems; for example, fluctuations in the quantity and quality of water determine the behavior of aquatic life and the socioeconomic benefits along the watershed, including downstream areas beyond the mountains. However, there is a growing awareness that mountain water supplies are under pressure because of increased climatic variability and snowpack reduction, hydrological impacts due to land use changes, and the need to maintain sufficient water for ecosystem services that support the natural livelihoods.
Mountain watersheds are highly complex, extremely variable, and sensitive to both climate change and human land use. Changes in precipitation and snowmelt affected by temperature increment and referred as rain-on-snow (large amount of liquid precipitation falling in the snowpack) are altering flow of water in rivers and streams all over the world, with potentially large impacts on habitat and their species, surpassing the hydrological systems capacity. These events could be materialized in short periods of time, with consequently high volumes of water running, triggering intensive floods and debris flows in a catchment zone. Mountain livelihoods and infrastructure are predicted to be at increased risk from natural hazards and extreme events, which are set to increase in both magnitude and frequency. In disturbed lands, like the mining areas, the soil structure changes may reduce the maximum water holding capacity. These situations would increase the risk of additional hazards as landslides, slope instability, avalanches, mudflows, mudslides and other negative effects to life and property.
Water is a critical pathway through which climate impacts are experienced. Climate change can alter four aspects of the water cycle: overall water availability, including amounts of surface and groundwater; patterns and predictability of precipitation, glacier melt, and groundwater recharge; water quality; and the frequency and severity of extreme events such as droughts and floods.
Wet mining conditions are a known contributor to increased operational cost, reduced safety, and reduced operational efficiency on mine sites. Water saturated ore reduces the effective ore content per truckload, thus increasing the number of trips required to haul the same amount of ore, fuel consumption, and wear and tear of components such as tires. In addition, wet mining conditions result in re-work such as drilling and blasting while also increasing the risk to workers because of slope stability reductions.
According to a first aspect of the invention, there is provided a method for determining sections of a mining operation impacted by wetness comprising:
According to another aspect of the invention, there is provided a method for mining operation water management comprising:
According to another aspect of the invention, there is provided a method for teaching a machine learning algorithm for predicting conditions at risk of resulting in algal bloom in a water source comprising:
According to another aspect of the invention, there is provided a method for predicting algal bloom in a water source comprising:
According to another aspect of the invention, there is provided a method for training a machine learning algorithm to predict tailings dam failure comprising:
According to another aspect of the invention, there is provided a method for preventing tailings dam failure comprising:
According to another aspect of the invention, there is provided a method for teaching a machine learning algorithm for predicting conditions at risk of resulting in algal bloom in a water source comprising:
According to another aspect of the invention, there is provided a method for predicting algal bloom in a water source comprising:
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are now described. All publications mentioned hereunder are incorporated herein by reference.
As discussed above, 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 is 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. As will be appreciated by one of skill in the art, 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.
As discussed herein, the necessary information is gathered from various data sources and the methods apply different statistical and/or mathematical analyses to the data. In some embodiments, data and associated outcomes are analyzed by one or more machine learning algorithms for developing predictive methods, as discussed herein.
According to an aspect of the invention, there is provided a method for determining sections of a mining operation impacted by wetness comprising:
As will be appreciated by one of skill in the art, as used herein, “a mining operation” refers not only to the ore extraction locations but also to vehicle pathways, mining support structures such as for example tailings ponds and seepage ponds and the surrounding areas.
As will be appreciated by one of skill in the art, the method described above can be used to develop a “heatmap” of areas within the mining operation most impacted by wet mining conditions and consequently optimal areas for ore extraction and blasting during wet mining conditions. As will be appreciated by one of skill in the art, this is not limited to merely measuring, determining or predicting the wetness of extracted ore, but also on the suitability for required vehicle traffic to reach specific ore mining locations. Accordingly, in one embodiment of the invention, the wetness information is used to determine optimal pathways for truck traffic, for example, as a function of optimal extraction locations, distance driven, and slope stability.
Furthermore, measurement of water flow will also provide information on impending changes to wetness, for example, that a location that is currently suitable for mining will be too wet to be mined in the very near future, based on measured changes in water flow.
Accordingly, in some embodiments, the method further comprises external data, for example, weather forecast data, historical data and local trends. Historical data may include for example but by no means limited to historical moisture data, historical weather data, historical water levels, historical water flow rates and historical water evaporation rates. Local trends may include for example but by no means limited to weather trends, determined from collecting of data from weather stations at the mining operation as well as groundwater and surface water level trends, which can be determined from the groundwater level sensors and water flow sensors described above.
As will be apparent to one of skill in the art, this information can be used to develop an operational forecast for blasting and ore extraction locations and required vehicle pathways based on projected future wetness levels. That is, specific locations may be preferentially used for extraction or prioritized for extraction based on weather forecasts and/or historical data which suggest that for example the ore at a given location within the mining operation may either be too wet or inaccessible because of its location in the immediate future.
The historical data and/or weather forecast data can be used to predict water level and water flow data, but can also be used to predict evaporation rates, which can be used to forecast when particular routes and/or particular extraction sites will be useable. This can be combined with operational data, for example, desired ore extraction volumes, as well as for planning work schedules based on projected wetness conditions.
In some embodiments of the invention, the method further comprises providing a plurality of water level sensors positioned in one or more water sources. As will be appreciated by one of skill in the art, these water sources include water sources within the mining operation such as for example tailing ponds and seepage ponds, as well as streams and rivers that impact or interact with the mining operation. That is, the whole mine water balance is being monitored.
In some embodiments, the method further comprises providing mine dewatering pump data to the control system for projecting water volumes within specific reservoirs as well as wetness of specific locations.
In other embodiments, the method may include seismic sensors and/or geotechnical sensors reporting ground and/or slope stability information to the control unit for routing mine vehicle traffic.
In other embodiments, the control system is arranged to collect GPS data from mine vehicles. As will be appreciated by one of skill in the art, this provides information on routes followed by the mine vehicles, which can be incorporated into a functional map of the mining operation, as discussed below.
In some embodiments of the invention, the control unit generates a map of the mining operation, for example, a functional map of the mining operation which indicates which locations are currently suitable for transport as well as suitable for ore extraction. In other embodiments of the invention, predicted functional maps may be generated by the control unit which show near- or immediate-future functionality of the mining operation based on projected data which incorporate for example weather forecast data and/or historical trends. In other embodiments, the control unit may generate functional maps according to specific wetness for mining operation long-term planning.
In some embodiments of the invention, these maps are supported and/or supplemented by aerial data, for example, satellite and/or aerial drone data, for example, for the generation of digital terrain models. In some embodiments of the invention, this aerial data may include hyperspectral data.
In some embodiments of the invention, wetness is measured and reported to the control unit in real time. That is, data is analyzed, processed and reported by the control unit within a minute of being reported. In some embodiments of the invention, the reported data is constantly updated.
The intervention taken may be that a particular vehicular route is closed due to stability concerns when the wetness of the location is outside of the suitable window. While this will generally mean that the ground is too wet, it may also be that the ground is too dry to support specific types of vehicular traffic. As used herein, “stability” does not necessarily mean just the stability of the ground, but may also mean that particular vehicles, for example, vehicles with particular treads or wheels or vehicles above a certain weight may not be able to travel the route without problems with traction or without damaging the integrity of the route.
In preferred embodiments, the method employs non-stationary, adaptive algorithms that can adapt with the mine over time as the topography and site dynamics shift.
According to an aspect of the invention, there is provided a method for mining operation water management comprising:
As will be appreciated by one of skill in the art, with this information, the water content of the entire mining operation can be better managed. For example, it is possible to adjust pumping rates from specific locations as well as selecting what locations to pump from. This would be based on forecasted wetness as a function of weather and water level/flow/moisture predictions.
In some embodiments, the method further comprises external data, for example, weather forecast data, historical data and local trends.
The historical data and/or weather forecast data can be used to predict water level and water flow data. This can be combined with operational data, for example, desired ore extraction volumes, as well as for planning work schedules based on projected conditions.
In some embodiments of the invention, water levels and water usage are measured and reported to the control unit in real time. That is, data is analyzed, processed and reported by the control unit within a minute of being reported. In some embodiments of the invention, the reported data is constantly updated.
Mining water quality can also be impacted by algal bloom, that is, a rapid increase or accumulation in the algae population within the water reservoir. As known to those of skill in the art, this overgrowth of algae can render the water in the water reservoir unsuitable for use within the mining operation.
According to another aspect of the invention, there is provided a method for teaching a machine learning algorithm for predicting conditions at risk of resulting in algal bloom in a water source comprising:
According to another aspect of the invention, there is provided a method for predicting algal bloom in a water source comprising:
In some embodiments, the at least some of said algae data includes at least dissolved organic carbon (DOC) to create a surrogate phosphorous parameter which is a known factor for algal blooms. Based on this information, the mining operation is able to take steps to prevent the algal bloom or adapt operations, for example, to prepare water reserves or plan for loss of water availability.
Tailings dams store pools of toxic mineral waste. The mine tailing water movement needs to be monitored as an early warning of tailings dam failure. Specifically, these dam failures can contaminate rivers and drinking water as well as ruin property and fisheries. Common practice today is to use lasers and slope indicators to detect the movement.
Specifically, there are two types of dam failures: structural failures and containment failures. Containment failure is more frequent and indicates that contaminated water is seeping through the dam into neighbouring water supplies—As discussed herein, containment failures can be detected using the spectrometer. In some embodiments, conductivity sensors are also used. Early detection of a containment failure allows maintenance to be performed, for example, installing or repairing liners, which prevents further contamination and also prevents further damage to the dam. Specifically, containment failure can eventually lead to structural failure, for example, as a result of a piping effect, wherein flowing water creates a hole within an embankment of a dam and is the leading cause of structural failure. According to one aspect of the invention, there is provided a method for training a machine learning algorithm to predict tailings dam failure comprising:
As will be apparent to one of skill in the art, the “associated water source” refers to water supplies adjacent to the tailings pond, for example, water sources at risk of contamination from the tailings pond if seepage occurs.
That is, by using diagnostic features in the UV/VIS spectral fingerprint, algorithms can be designed to detect predictive changes in the seepage water. That is, changes of the spectrum within the tailings pond but also within the associated water source, that is, the adjacent body of water. When a spike occurs in the seepage water, alerts are triggered and email sent to the appropriate staff, indicating that tailings dam maintenance, for example, repairing a geotechnical liner, is required.
According to one aspect of the invention, there is provided a method for preventing tailings dam failure comprising:
In some embodiments of the invention, the method further comprises subsurface sensors for monitoring for deformation of the embankment, for example, for determining if an evacuation will be necessary.
The scope of the claims should not be limited by the preferred embodiments set forth in the examples but should be given the broadest interpretation consistent with the description as a whole.
The instant application claims the benefit of US Provisional Patent Application 63/405,580, filed Sep. 12, 2022 and entitled “METHOD FOR WATER AND MOISTURE MANAGEMENT FOR A MINING OPERATION”, the entire contents of which are incorporated herein by reference for all purposes.
| Number | Date | Country | |
|---|---|---|---|
| 63405580 | Sep 2022 | US |
