Detecting and Modeling Subsurface Fracture Systems in Geothermal Fields Using Shear-wave Splitting

• Main Author: Tang, Chuanhai
• Other Authors: College of Arts and Sciences, Department of Geological Sciences, Rial, Jose
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: 2009
• Subjects: Hengill; Krafla; Iceland
• Online Access: https://doi.org/10.17615/mh6j-3233; https://cdr.lib.unc.edu/downloads/c247dt24h?file=thumbnail; https://cdr.lib.unc.edu/downloads/c247dt24h

Shear wave splitting (SWS) is emerging as a useful exploration tool for geothermal fields as it can detect the geometry of the fracture system and the intensity of cracking within the geothermal reservoir. The method is based on the analyses of polarizations and time delays of split shear-waves that have been distorted by the anisotropy of the medium through which the seismic waves have propagated. Two experiments were conducted in Krafla and Hengill geothermal fields in Iceland in the summers of 2004 and 2005 respectively. Clear evidences of SWS were observed in both sites. In Krafla, in addition to the observed prevalence of a crack system oriented in approximately N-S direction which is consistent with the direction of regional rift zone, fast shear-wave polarization directions along a general E-W direction are also persistent. In Hengill, the measurements and consequent inversions of the shear-wave splitting parameters have provided evidence for a predominant fracture system oriented approximately NNE-SSW which is consistent with the regional tectonics in SW Iceland. Based on our previous research we have developed and consolidated a number of algorithms that can in principle make possible the automatic monitoring of subsurface fracture systems in geothermal fields. Seismic data are collected from an array of three-component seismic sensors. When a seismic event is detected it will be readily located provided that the record is available at no less than four seismometers. If shear-wave splitting is determined to be present for an event, both parameters will be automatically measured using a newly developed method based on the analysis of multiple time windows. An automated SWS algorithm is performed for a series of time windows to yield a series of estimated pairs, followed by a cluster analysis to finally determine the best estimate of polarization and time delay. Then, if the event is within the shear-wave window of any recording station, the measured parameters will be combined with all available ...