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Advanced geophysical underground coal gasification monitoring

  • Robert Mellors
  • X. Yang
  • J. A. White
  • A. Ramirez
  • J. Wagoner
  • D. W. Camp
Original Article

Abstract

Underground Coal Gasification (UCG) produces less surface impact, atmospheric pollutants and greenhouse gas than traditional surface mining and combustion. Therefore, it may be useful in mitigating global change caused by anthropogenic activities. Careful monitoring of the UCG process is essential in minimizing environmental impact. Here we first summarize monitoring methods that have been used in previous UCG field trials. We then discuss in more detail a number of promising advanced geophysical techniques. These methods – seismic, electromagnetic, and remote sensing techniques – may provide improved and cost-effective ways to image both the subsurface cavity growth and surface subsidence effects. Active and passive seismic data have the promise to monitor the burn front, cavity growth, and observe cavity collapse events. Electrical resistance tomography (ERT) produces near real time tomographic images autonomously, monitors the burn front and images the cavity using low-cost sensors, typically running within boreholes. Interferometric synthetic aperture radar (InSAR) is a remote sensing technique that has the capability to monitor surface subsidence over the wide area of a commercial-scale UCG operation at a low cost. It may be possible to infer cavity geometry from InSAR (or other surface topography) data using geomechanical modeling. The expected signals from these monitoring methods are described along with interpretive modeling for typical UCG cavities. They are illustrated using field results from UCG trials and other relevant subsurface operations.

Keywords

Underground coal gasification UCG Electrical resistivity tomography ERT Interferometric synthetic aperture radar InSAR 

Notes

Acknowledgements

S. Hunter and W. Foxall provided useful input and the results benefitted greatly from discussions of the LLNL UCG group. We also appreciate the guidance and comments from two reviewers that greatly improved the paper. ALOS SAR data copyright JAXA [2007]. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. Submission LLNL-JRNL-641052.

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Copyright information

© © Springer Science+Business Media Dordrecht (outside the USA) 2014

Authors and Affiliations

  • Robert Mellors
    • 1
  • X. Yang
    • 1
  • J. A. White
    • 1
  • A. Ramirez
    • 1
  • J. Wagoner
    • 1
  • D. W. Camp
    • 1
  1. 1.Lawrence Livermore National LaboratoryLivermoreUSA

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