The project involves modeling the execution of the planned mine, which would take place over a period of 50 years, and predicting the resulting impacts to the regional groundwater system, out to 150 years post closure. The groundwater model and accompanying results are subject to a rigorous level of review by stakeholders, as well as Federal and State agencies for permitting purposes. Therefore, an accurate representation of the block cave mine within the groundwater model is required for producing the most defensible model and associated predictions.

Block cave mining is an underground mining method in which the ore body is mined from the bottom up, as opposed to more traditional methods of open pit surface mining or underground tunneling. In the case of this project, the base of the ore body sits approximately 7,000 feet below the ground surface and the resulting cave is expected to reach a mile in width.

The mining industry presents unique challenges for groundwater modeling projects, given the frequent and continuous changes to surface and subsurface ground conditions. Mining practices—underground tunneling, blasting, backfilling and block cave mining, for example—alter rock and change the hydraulic properties of the affected rock mass over time.

The block cave mining process, in particular, induces a large stress on the overlying rock mass through the removal of rock at the base of the ore body. This stress in turn causes a network of fractures to propagate upwards resulting in increases to hydraulic conductivity and storage parameter values by orders of magnitude. A standard groundwater modeling approach may implement broad, general assumptions in regards to the timing and magnitude of hydraulic property changes. By contrast, the approach WSP has taken utilizes geotechnical modeling outputs, which quantifies the deformation of the ore body and overlying rock through time, and translates these data into transient hydraulic property changes. The use of geotechnical model output for groundwater model parameter estimation provides a more accurate and defensible model for integrated groundwater modeling, providing higher confidence predictions.

The benefit of coupling a geotechnical model with a groundwater model is the ability to capture a highly dynamic system changing in four dimensions (i.e. hydraulic properties changing in 3-dimensional space and time). Although simplistic assumptions regarding hydraulic property changes can be approximated, collaboration with geotechnical modelers allows for more detailed estimates of bulk rock-mass hydraulic property changes through time. The geotechnical model provides a detailed history of rock deformation and cave progression that would otherwise be grossly simplified. Geotechnical model outputs, plastic strain and rock-mass volume changes, are translated into multipliers and applied to hydraulic conductivity and storage parameter values, respectively, at numerous model times.

Translated geotechnical data are implemented into the groundwater model via the Time-varying Material Properties (TMP) package of MODFLOW-SURFACT. This package allows the model to vary hydraulic properties within the model over time, providing a method for simulating the transient effects of mining activities which helps determine the impacts of these changes.

The incorporation of geotechnical data via the TMP package allows for the simulation of the future block cave by modeling each groundwater model cell representing the cave with a unique time history of hydraulic properties, and therefore, simulates the highly dynamic rock fracturing process both spatially and through time.

One aspect of this technique is the ability to more accurately predict the timing at which water bearing units would be altered and to quantify the predicted flows that could be expected when those units are encountered. This integration allows clients to gain insight into future expectations of groundwater inflows and develop operational planning for dewatering systems based on model results. In addition, the timing and magnitude of potential impacts (reduction of water levels) to the groundwater system can also be quantitatively predicted with higher confidence. Model results can then be used to develop mitigation and monitoring plans for potential impacts.

The mining industry is heavily invested in the collection and utilization of geotechnical data for various purposes. The mining industry is also invested in groundwater modeling for other purposes, sometimes unrelated to those involving geotechnical analysis.

This integrated modeling technique demonstrates the value that geotechnical data can provide to construct more accurate groundwater models even when those purposes are not directly aligned.

The translation of geotechnical datasets is key to creating data driven model inputs which hold up to rigorous review as opposed to broad, generalized assumptions regarding hydraulic property changes through time.

The approach developed by WSP aims to set a new standard for groundwater modeling of highly dynamic systems like block cave mines. It is an example of the firm’s goal of creating a Future Ready™ world that seeks new solutions for a changing world that is facing new environmental challenges. By viewing traditional approaches from a fresh perspective, and by using new tools developed through improving technology, WSP is helping its clients improve efficiency, reduce impact on the environment, and create safer work spaces.

The method and techniques developed on this project should also be considered for developing groundwater predictions associated with other types of subsurface construction projects, extending its influence even further.

Christopher Pantano is a WSP USA project hydrogeologist with the Mine Water Services Group in Butte, Montana. He and his WSP colleagues, Doug Oliver and Gustavo Meza-Cuadra, co-authored and presented “Geotechnical and Groundwater Modeling: An Integrated Approach for Block Cave Mining,” on Feb. 26, 2019 at the Society for Mining, Metallurgy & Exploration (SME) Annual Conference in Denver, Colorado.

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