Integrated dynamic water and cooling simulation planning in deep-level mines

Abstract

The deep-level mining process is a dynamic and complex process where mines are getting deeper and new mining areas are constantly being developed. Some of the deep-level mines are reaching record depths of over 4 km with mined-out distances covering more than 200 km. To ensure that mines remain profitable and safe, efficient mine planning is essential, as it has direct implications on the profitability and safety of the mine.

Mine water- and cooling systems (WCS) are essential to cool workplaces and to achieve production targets. Effective WCS planning is important for the success of a mine and its long-term sustainability. However, these systems are complex due to their size and the large number of components involved. To add to the complexity, these components are also integrated with one another and consist of multiple dynamic variables.

A critical literature study shows that mines often neglect the integrated and dynamic aspects of WCS planning. Current methods often lead to wrong decisions that limit productivity and impact the safety of the mine. The large uncertainties associated with current methods require large safety margins that, in turn, lead to capital wastages and unnecessary operational costs. This means the industry requires a method that accurately simulates and predicts the outcome of planning decisions by accounting for the integrated and dynamic nature of the WCS.

In this study, a unique mine WCS planning method was developed. The new method makes use of simulation tools using empirical and dynamic data to predict operating conditions of large integrated mining systems. Applications of the method inter alia include life-of-mine planning, safety improvements, and identification of operational improvement opportunities. The new method differs from the old method which is non integrated, static and uses design variables. The old method also does not make use of simulation tools.

The new method (WCS planning) was applied to a complex deep-level mining operation in South Africa. At this mine, production decreased from maximum to complete closure over a two-year period. The method was used to forecast the effect of the mining changes on the WCS of the mine over the 27 months. As part of the method, an integrated and dynamic model was constructed that makes use of more than 2 000 semiempirical components to predict future operating conditions. By comparing the predictions with actual results, the new method is shown to be more than 90% accurate.

The new planning method was also tested on other case studies and the results were compared with the current non-integrated, static, and design approach. The new method showed that underground temperatures can be improved by between 16% and 34% compared with the current method. In some instances, the new method also predicted that underground temperatures can be improved by more than 3 °C. These improvements could have significant benefits on safety, production as well as cost. An estimated benefit of R2.2 billion over the life of mine was calculated. Another case study showed that, by implementing changes identified by the new planning method, the predicted time of mine flooding during a total power failure event could be increased by more than 22 hours compared with the current planning method.

The developed method was only applied on deep-level mine water and cooling systems which restricts the method's application to other industries or systems on the mine. However, it is possible to utilise the method for other industries or mining systems with some modification. The method also requires significant data to be accurate which is a challenge in the deep-level mining environment. It is recommended that data accuracy be improved in some instances data collection be automated.