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Mining Publication: A CART Technique to Adjust Production from Longwall Coal Operations under Ventilation Constraints

March 2012

Image of publication A CART Technique to Adjust Production from Longwall Coal Operations under Ventilation Constraints

Methane emissions in longwall coal mines can arise from a variety of geologic and production factors, where ventilation and degasification are primary control measures to prevent excessive methane levels. However, poor ventilation practices or inadequate ventilation may result in accumulation of dangerous methane-air mixtures. The need exists for a set of rules and a model to be used as guidelines to adjust coal production according to expected methane emissions and current ventilation conditions. In this paper, hierarchical classification and regression tree (CART) analyses are performed as nonparametric modeling efforts to predict methane emissions that can arise during extraction of a longwall panel. These emissions are predicted for a range of coal productivities while considering specific operational, panel design and geologic parameters such as gas content, proximate composition of coal, seam height, panel width, cut height, cut depth, and panel size. Analyses are conducted for longwall mines with and without degasification of the longwall panel. These models define a range of coal productivities that can be achieved without exceeding specified emissions rates under given operating and geological conditions. Finally, the technique was applied to longwall mines that operate with and without degasification system to demonstrate its use and predictive capability. The predicted results proved to be close to the actual measurements to estimate ventilation requirements. Thus, the CART-based model that is given in this paper can be used to predict methane emission rates and to adjust operation parameters under ventilation constrains in longwall mining.

Authors: CÖ Karacan, GV Goodman

Peer Reviewed Journal ArticleMarch - 2012

  • Adobe Acrobat - Portable Document Format (.PDF)

    1.24 MB

NIOSHTIC2 Number: 20040133

Saf Sci 2012 Mar; 50(3):510-522

 
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