Abstract
Numerical modelling simulations of proposed mining sequences are used to evaluate mining induced stress concentrations and their migration associated with the progress of mining. This analysis is a standard practice for most prospective mining projects at various levels of feasibility study. The studies are usually initiated at the beginning of the mining cycle, on a global scale, and are maintained and updated throughout the life of mine (LoM) to identify or address local issues and the required remedies as and when needed.
Developments in numerical modeling techniques along with advancements in computing technology and data storage/management capacity have given rock engineers access to a huge volume of data that needs to be analyzed and assessed. The most common approach to numerically evaluate stress concentrations and migrations in underground mines is to select the points of interest in a given volume such as the back of an excavation or points within pillars around critical infrastructure, and plot the stresses or a derivative of stresses over time to represent life of mine concentrations and migrations of stresses. The problem with this approach is the sharp gradient of stresses close to excavation boundaries. Slight changes in the location of selected points can change the stress concentration and migration patterns substantially and all generalized statements about LoM risk can be challenged in one way or another. For global stresses, the most common current approach of data analysis is by viewing series of pictures representing stress contours. In this approach, it is easy to overlook some critical detail and/or be masked by personal preferences of contour/picture representation.
To overcome the problem of representing and analyzing huge volume of stress simulation data, the authors, through their experience at different mining operations, developed a volume-based technique to reliably evaluate mining-induced stress concentrations and migrations.
The volume-based approach is for risk-based assessments of adjacent regions in the rockmass, in and around planned stoping excavations. The volume of interest is the entire ore body that is planned to be mined, but it could be just a part of the ore body depending on the specific use case.
The risk identifiers are the induced stresses as compared to the strength of the rockmass. Over the LoM, the risk identifiers are tracked versus the corresponding excavation ratio of the zone. This approach is very effective in identifying the stages of mining that are contributing the most to the mining induced stress risk and the results can be used for proactive planning and mitigations measures such as alternative mining sequences, or stope sizes, or extraction methods.
The approach has also been very successful in application at mature mines, particularly in assessing the re-initiation of mining in zone that has been dormant for some time. The volume-based approach allows for an assessment of the current state of the rockmass and the identification of future risks when planning resumption of mining activities.