Block Caving Production Layout Optimization Considering Uncertainty in Grade Models

• Author / Creator

  Ugarte-Zarate, Efrain

• The mining industry of today demands large-scale extraction methods, and caving has become the preferred underground mining technique because of high production rates, low mining costs, and low waste production. Moreover, there is a current growth of concerns about the effects of uncertainty and risk in mine design, safety, and production schedules. Companies are then moving away from traditional approaches to adopt techniques that quantify uncertainty and optimize critical processes to succeed. One key engineering factor for the success of a block caving is the drawpoint spacing layout, that is designed prior to operation. The current guides to design this important element remains controversial due to uncertainty influenced by different aspects of caving, but most importantly by the block model.
  Grade modeling is the basis of mine design and planning and plays an important role in the prediction of financial outcomes. Conventional layout design calculates layouts based on deterministic modeling that generates a single model of economic value and therefore is not capable of accounting for uncertainty. In contrast, stochastic orebody modeling allows for quantifying uncertainty by generating multiple equiprobable models which can be integrated into an optimization process. There are currently well-studied procedures to optimize mine designs using orebody uncertainty in open-pit mines, but little work is done in block caving.
  This research provides a methodology in which uncertainty from the block model is assessed with SGS to determine the optimal drawpoint spacing and level of extraction. Multiple models are used in a transfer function to provides a summary of responses and then select the optimal option. The approach is supported by block caving definitions and explained with conceptual examples. A copper-gold caving project is used to demonstrate the methodology using Gaussian simulation and a signed distance function. Data for the study is from 37 drill holes and assays is composited to 10 m with copper-gold mineralization. Fifteen potential layouts are selected. Optimizing the drawpoint spacing gives 30 × 13 layout as the optimal one, and the optimal extraction level is 440 m.
  Tonnage uncertainty is added to the case study. The variability of domain boundaries is incorporated into the work. A set of twenty implicit models with simulated grades are used to evaluate boundary uncertainty. The tonnage uncertainty confirms that the 31 × 14 layout and 31 × 15 present lower risk compared to the optimal 30 × 13 layout.

• Subjects / Keywords

  • caving
  • Gaussian
  • drawpoint
  • layout

• Graduation date

  Fall 2018

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R39Z90T9T

• License

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