Application of predictive blasting model to improve grade control and optimize blast value
Pratama, Ryan Yoga
Pratama, Ryan Yoga
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2024
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Abstract
Each block in the geological block model has an economic value. The block economic value (BEV) distinguishes economic (ore) and uneconomic blocks (waste). A block will be economic to mine if its BEV is positive and uneconomic if it is negative, assuming there are no waste blocks on top of it.
Reconciliation is a process to verify the resource model against actual production data. The grade control model as an important part of reconciliation process is a model developed for daily ore/waste selection to determine where each material mined should go. It is crucial to avoid sending the block of material to the wrong destination as the consequences can be overall ore loss and dilution which lead to loss of value.
Blasting is a process of breaking rock mass using explosives. Blasting can break a large amount of rocks at a low cost. However, regardless of how well-controlled the blasting is, rock displacement will occur due to the forces applied. The blasting for rock breakage will result in movement of ore and waste blocks in the grade control block model from their pre blast positions into new post blast positions. This can affect the definition and accuracy of the ore and waste boundaries used for grade control within the resulting post blast muck pile compared to pre blast definition of ore and waste boundaries. Accurate definition of precise post blast grade control polygons is vital for the economics of any mine.
The vital question is, "What is the impact of blasting on grade control value and how can the most value be captured by considering the probable changes caused by the blast?" Orica developed OREPro™ 3D Predict ("The Predictive Model"), a real-time blast movement prediction model that uses complex physics algorithms to predict rock movement and the post blast muckpile in minutes allowing one to be able to predict the post blast location of individual blocks within the grade control block model. The Predictive Model utilizes these new block locations within the grade control polygon optimizer tool to generate post blast grade control polygons that maximize value of the extracted resource before initiating the blast.
This thesis investigates and evaluates the potential application of the Predictive Model to improve grade control model and optimize blast value. Additionally, variables were identified and reviewed when utilizing the Predictive Model in various blasting conditions.
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