04/09/2023
Let's talk about Geology
With our Renewable Energy Division and our years of working withing the Quarry and Mining sector (I suppose this was inevitable being based in COALville), we have seen a sizeable increase in requirements within Geology, specifically due to the advancements in technology and the opportunities that have presented as a result of Automation, Drone Technology and Machine Learning techniques. I've broken these down below;
Automation
Automated Drilling: Automated drilling is the use of precision drilling tools and robotics to drill holes in rocks for the purpose of extracting resources. This helps reduce the amount of time required for manual drilling and can increase accuracy.
Automated Ore Sorting: Automated ore sorting is the use of optical or x-ray technology to sort ore into grades and categories. This can be used to identify viable ore for extraction and reduce the amount of waste ore.
Automated Haulage: Automated haulage is the use of remote-controlled or automated trucks and other vehicles for transporting resources around mine sites. This can help reduce the operational costs and improve safety.
Drone Technology
Monitoring and Surveying: Drones can be used to monitor and survey a site from the air, providing a bird's eye view of the area. This can be used to observe the physical conditions of a site and identify potential hazards.
Exploration: Drones can be used for exploratory purposes, such as locating viable ore deposits and identifying environmental concerns. This can help reduce the costs of exploration and increase the efficiency of resource extraction.
Mapping: Drones can be used to map a potential mining site, providing valuable data that can help determine the best way to extract resources. This can help reduce costs and increase efficiency.
Machine Learning
Predictive Analysis: Machine learning can be used to predict potential hazards in the workplace before they occur. This can help reduce the risk of injury or death, as well as improve operational efficiency.
Data Visualization: Machine learning can be used to create visually appealing graphs and charts to better understand and explore data. This can be used to make informed decisions in a variety of mining and geology engineering scenarios.
Pattern Recognition: Machine learning can be used to detect patterns in data and make predictions based on those patterns. This can help reduce the risk of human error and increase the accuracy of predictions.
