Mining Publication: Prediction of Porosity and Permeability of Caved Zone in Longwall Gobs
Original creation date: March 2010
The porosity and permeability of the caved zone (gob) in a longwall operation impact many ventilation and methane control related issues, such as air leakage into the gob, the onset of spontaneous combustion, methane and air flow patterns in the gob, and the interaction of gob gas ventholes with the mining environment. Despite its importance, the gob is typically inaccessible for performing direct measurements of porosity and permeability. Thus, there has always been debate on the likely values of porosity and permeability of the caved zone and how these values can be predicted. This study demonstrates a predictive approach that combines fractal scaling in porous medium with principles of fluid flow. The approach allows the calculation of porosity and permeability from the size distribution of broken rock material in the gob, which can be determined from image analyzes of gob material using the theories on a completely fragmented porous medium. The virtual fragmented fractal porous medium so generated is exposed to various uniaxial stresses to simulate gob compaction and porosity and permeability changes during this process. The results suggest that the gob porosity and permeability values can be predicted by this approach and the presented models are capable to produce values close to values documented by other researchers.
Authors: CĂ Karacan
Peer Reviewed Journal Article - March 2010
NIOSHTIC2 Number: 20036544
Transp Porous Media 2010 Mar; 82(2):413-439
See Also
- Effect of a Surface Borehole on Longwall Gob Degasification (Pocahontas No. 3 Coalbed)
- Field Study of Longwall Coal Mine Ventilation and Bleeder Performance
- Investigation into the Practical Use of Belt Air at US Longwall Operations
- A Methodology for Determining Gob Permeability Distributions and its Application to Reservoir Modeling of Coal Mine Longwalls
- Modeling and Prediction of Ventilation Methane Emissions of U.S. Longwall Mines Using Supervised Artificial Neural Networks
- A New Methane Control and Prediction Software Suite for Longwall Mines
- Prediction of Longwall Methane Emissions: An Evaluation of the Influence of Mining Practices on Gas Emissions and Methane Control Systems
- Probabilistic Modeling Using Bivariate Normal Distributions for Identification of Flow and Displacement Intervals in Longwall Overburden
- Reconciling Longwall Gob Gas Reservoirs and Venthole Production Performances Using Multiple Rate Drawdown Well Test Analysis
- Underground Gob Gas Drainage During Longwall Mining
- Content source: National Institute for Occupational Safety and Health, Mining Program