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Forecasting gob gas venthole production performances using intelligent computing methods for optimum methane control in longwall coal mines.

Authors
Karacan-C÷
Source
Int J Coal Geol 2009 Sep; 79(4):131-144
NIOSHTIC No.
20035774
Abstract
Gob gas ventholes (GGV) are used to control methane inflows into a longwall operation by capturing it within the overlying fractured strata before it enters the work environment. Thus, it is important to understand the effects of various factors, such as drilling parameters, location of borehole, applied vacuum by exhausters and mining/panel parameters in order to be able to evaluate the performance of GGVs and to predict their effectiveness in controlling methane emissions. However, a practical model for this purpose currently does not exist. In this paper, we analyzed the total gas flow rates and methane percentages from 10 GGVs located on three adjacent panels operated in Pittsburgh coalbed in Southwestern Pennsylvania section of Northern Appalachian basin. The ventholes were drilled from different surface elevations and were located at varying distances from the start-up ends of the panels and from the tailgate entries. Exhauster pressures, casing diameters, location of longwall face and mining rates and production data were also recorded. These data were incorporated into a multilayer-perceptron (MLP) type artificial neural network (ANN) to model venthole production. The results showed that the two-hidden layer model predicted total production and the methane content of the GGVs with more than 90% accuracy. The ANN model was further used to conduct sensitivity analyses about the mean of the input variables to determine the effect of each input variable on the predicted production performance of GGVs.
Keywords
Mining-industry; Underground-mining; Longwall-mining; Methane-control; Methanes; Mine-gases; Models; Computer-models; Engineering-controls; Control-technology; Author Keywords: Longwall mining; Gob gas ventholes; Production performance; Artificial neural networks; Sensitivity analysis; Methane control
Contact
C. ÷zgen Karacan, National Institute for Occupational Safety and Health (NIOSH), Pittsburgh Research Laboratory, Pittsburgh, PA 15236, USA
CODEN
IJCGDE
CAS No.
74-82-8
Publication Date
20090901
Document Type
Journal Article
Email Address
cok6@cdc.gov
Fiscal Year
2009
NTIS Accession No.
NTIS Price
Issue of Publication
4
ISSN
0166-5162
NIOSH Division
PRL
Priority Area
Mining
Source Name
International Journal of Coal Geology
State
PA
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