Towards the integration of smart techniques for tunnel seismic applications

Thomas Dickmann*, Jozsef Hecht-Méndez, Dirk Krüger, Alla Sapronova, Paul Johannes Unterlaß, Thomas Marcher

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Applications of seismic measurements for the prediction of hazard zones are applied practice in many tunnel drives in rock mass today. Next to a large exploration range and accurate localisation of discontinuities, seismic data provide attributes for a comprehensive characterisation of the ground conditions. A good synchronisation of all technical components is required to obtain optimum data quality and quantity while the tunnel excavation is not obstructed thereby. Firstly, the signal source must feed as much energy as possible into the rock in a very short time. Secondly, continuity of the signal generation with constant quality and its precise timing by means of wireless data transmission also ensure a reliable measurement process. Artificial intelligence is used to determine the quality of the recorded data already in the tunnel and feedback is given to the user keeping the data quality high. From the tunnel site, recorded raw data can be transferred to a cloud, from where an authorised processor collects them, wherever in the world. An immediately started data processing delivers a result within an hour that includes a geological forecast of up to 150 m of heading, depending on the rock mass condition. In addition to data quality, the quality of the results is crucial. Therefore, techniques are currently under development using machine learning to correlate and analyse seismic attributes with geological properties. This should lead to a more objective evaluation of the geological forecast in the future.
Translated title of the contributionAuf dem Weg zur Integration intelligenter Techniken für seismische Tunnelanwendungen
Original languageEnglish
Pages (from-to)609-615
Number of pages7
JournalGeomechanics and Tunnelling
Issue number5
Publication statusPublished - 1 Oct 2021


  • tunnel seismic prediction
  • geological forecast
  • wireless solutions
  • machine learning
  • Rock mechanics
  • Geology
  • Geophysics
  • Innovative procedures/test techniques

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Civil and Structural Engineering


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