sceval

Origin evaluation

Overview

High-sensitivity earthquake monitoring

sceval automatically discriminates real earthquakes from fake solutions. Reliable automatic monitoring of earthquakes at low magnitudes is challenging due to the low number and the possibly low quality of available phase detections. Therefore, automatic systems are often tuned to only accept robust solutions with many observations preventing fake events. Such systems potentially miss weak events resulting in incomplete earthquake catalogs.

With sceval seismic monitoring systems can be tuned to even accept very weak events detected under unfavourable conditions. sceval will evaluate the solutions and find fakes or mark them as real if the solution is likely to represent a real event. In this way earthquake catalogs can reach high completeness while being clean from fakes and operators can focus on analyzing the most relevant events.

Automatic tuning

Tuning of such event discrimination may be time-consuming and diffult. Therefore, sceval comes with a self-tuning tool providing the optimum configuration parameters based on manual observations.

Brochure Documentation

Applications

Apply sceval to evaluate solutions from other modules such as scautoloc, scanloc or ccloc:

  • high-sensitivity monitoring
  • networks with large or small aperture
  • flagging of fake events
  • confirmation of real events
  • networks with noisy stations having many false phase detections.

Promotion

Approved by science

sceval has been demonstrated, promoted and discussed with scientists and the SeisComP community at international science conferences, e.g.:

  • D. Roessler, B. Weber, E. Ellguth, J. Spazier the team of gempa: Evaluierung der Qualität und Geschwindigkeit von Erdbebendetektionen in SeisComP3, 2017, Bad Breisig, Germany, AG Seismologie meeting

  • D. Roessler, B. Weber, E. Ellguth, J. Spazier the team of gempa: EVALUATION OF EARTHQUAKE DETECTION PERFORMANCE IN TERMS OF QUALITY AND SPEED IN SEISCOMP3 USING THE NEW MODULES QCEVAL, NPEVAL AND SCEVAL, 2017, New Orleans, USA, AGU Fall Meeting, abstract S13B-0648