Numerical modeling of progressive gob formation in a deep longwall mine

Debasis Deb, Duk Won Park, Thomas Novak

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Because the Environmental Protection Agency has identified methane as a greenhouse gas, the degasification of coal bed methane through gob wells has become more critical. It has been observed that the degree of methane emission is closely related to the geomechanical characteristics of coal bearing strata, roof, floor, and surrounding coal seams. As a result, the study of progressive gob formation becomes necessary to understand the mechanism of strata movement and methane emission through gob wells. Several numerical models were developed to simulate gob formation of a longwall mine having similar geologic conditions as the Warrior Basin in Alabama. In addition, monthly production data from 250 gob wells and corresponding face position in each panel were collected from this area to corroborate the results of numerical modeling. This paper describes the techniques for numerical modeling of progressive gob formation and correlate the results with field investigations.

Original languageEnglish
Title of host publication2nd North American Rock Mechanics Symposium, NARM 1996
Editors Hassani, Mitri, Aubertin
Pages1893-1901
Number of pages9
StatePublished - 1996
Event2nd North American Rock Mechanics Symposium, NARM 1996 - Montreal, Canada
Duration: Jun 19 1996Jun 21 1996

Publication series

Name2nd North American Rock Mechanics Symposium, NARM 1996

Conference

Conference2nd North American Rock Mechanics Symposium, NARM 1996
Country/TerritoryCanada
CityMontreal
Period6/19/966/21/96

Bibliographical note

Publisher Copyright:
© 1996 Balkema.

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Geology
  • Geophysics

Fingerprint

Dive into the research topics of 'Numerical modeling of progressive gob formation in a deep longwall mine'. Together they form a unique fingerprint.

Cite this