GRC Transactions, Vol. 31, 2007 Analysis of Microseismic Events from a Stimulation at Basel, Switzerland Hiroshi Asanuma 1, Yusuke Kumano 1, Akito Hotta 1, Ulrich Schanz 2, Hiroaki Niitsuma 1, and Markus Häring 2 1 Graduate School of Environmental Studies, Tohoku University (Japan) 2 Geothermal Explorer Ltd. (Switzerland) Keywords Microseismicity, HDR, HWR, HFR, stimulation, Basel ABSTRACT The researchers from Tohoku University, Japan, analyzed microseismic events collected during a stimulation at Basel, Switzerland in December 2006. More than 2,000 events from over 13,000 triggers were located by the single event determination (SED) method, by joint hypocenter determination (JHD), and by the coherence-collapsing method (COH-COL). The located events define a seismic cloud with a sub-vertical structure and an azimuth of N159 E, which is similar to that at Soultz. The percentage of multiplets among the located events was 75%, which was higher than that at Soultz. The spatio-temporal analysis of the microseismic locations showed clear shut-in events around the stimulated zone and continuous seismic activity after pumping, suggesting that the stress state around the reservoir was nearly critical for shear slip. Introduction Global efforts to reduce the environmental burden associated with energy production and possible regional shortages in fossil energy in the near future have stimulated the development of geothermal utilization systems in European countries recently. Geopower Basel AG with its operator Geothermal Explorers Ltd. (GEL) has been developing a cogeneration system of electrical power and heating energy (3 MW electric and 20 MW thermal) around Basel (Switzerland) since 1996. The city of Basel is located at the southern end of the Rhine Graben, which is widely regarded as one of the highest potential geothermal fields in Europe. GEL has drilled a 5,000m (TVD) deep borehole, penetrating into granitic basement from 2,516m (TVD) on, and made the first stimulation to enhance permeability in December 2006. The authors from Tohoku University, Japan have experience in the microseismic monitoring during the stimulation of worldwide HDR/HFR/EGS reservoirs as well as the stimulation of gas reservoirs (Asanuma et al., 2003, Moriya et al., 2003, Kumano et al., 2006). They have developed techniques to reduce uncertainty in microseismic mapping and have quantitatively evaluated its reliability through international collaboration. Expertise has also been developed in identifying the seismic characteristics indicative of individual fractures with multiple slip events. Coherence-based techniques have also been investigated. The current study extends this work into the semi-realtime environment needed in commercial geothermal development environment. To this end, the authors coded software to relocate microseismic events with higher reliability emphasizing the location of the similar seismic events (multiplets) within a few minutes after the occurrence of the event (Coherence-collapsing: Asanuma et al., 2003). GEL and Tohoku University have also collaborated on the coherence-based post analysis of the microseismic events collected at the Basel site and the Japanese researchers visited the Basel site for the data analysis. Although the data analysis and the interpretation are still underway, the initial outputs from this work are described in this paper. Outline of the Data The hydraulic stimulation was carried out by pumping a total of 11,500 m 3 of water into a 4,749 m bod borehole (Basel-1) for over 6 days. The whole open-hole section (from 4,378 m to 4,749 m bod) with some pre-existing permeable zones was pressurized. The maximum wellhead pressure was around 30 MPa at a flow rate of 3,000 l/min. The microseismic monitoring network consists of 6 permanent and 1 temporarily installed downhole stations (Figure 1), where multicomponent detectors were deployed. At each monitoring station the signal was digitized by a 24 bit recording system applying a sampling frequency of 1 khz. The continuous data stream was transferred via a reliable VPN link to a central server and processing system. The automatic realtime processing included event detection, traveltime picking and event location applying an exhaustive grid search algorithm. 265
In parallel the automatically determined P and S wave travel times were visually rechecked allowing consistent and reliable absolute event locations in near real time. During the stimulation, there were roughly 13,000 potential events detected and > 2,700 of them had reasonable picks and as well fulfilled the tight location criterions for the single event determination by GEL. The traces and picks of the located events were transferred to the researchers from Tohoku University. A simple 1D velocity model with constant velocities for the sedimentary section and the granitic basement was used throughout this study. A station correction was also used to compensate for velocity heterogeneity. A downhole geophone temporarily deployed on a ledge at 4422 bod in the injection Figure 2. Location of the microseismic events determined by the single event determination method (SED). Figure 1. Microseismic monitoring network at Basel in 2006. well (Basel-1) was used to refine the velocity model and the station corrections assuming that the initial events occurred very close to the borehole. Location of the Microseismic Events The picks of P and S waves used in this study were provided by GEL to researchers from Tohoku University. These were used firstly to locate the events by the commonly used single event determination (SED) method, where the individual location and origin time of each event was determined by minimizing its residual. The locations determined by SED are shown along with the distribution of the residuals in Figure-2. The SED-determined Figure 3. Distribution of spatial error after SED. 266
Figure 5. Percentage of the multiplets. Figure 4. 3D distribution of residual for a synthetic event around the injection well. locations were nearly identical to those determined by GEL with maximum differences in location of no more than a few meters, although the techniques to minimize the residuals were different. To assess the reliability of the mapping we evaluated the spatial distribution of the residual and calculated confidence ellipsoids (spatial 1σ surface) for each event. These are represented by their three principle axes in Figure-3. The spatial distribution of the residual for a synthetic event around the injection well was also determined to see if the imposed station geometry introduces inhomogeneity into the error distribution (Figure-4) for the case of no error in the phase picking. The trace from monitoring well Riehen2 was used for event clustering because it showed best signal to noise ratio and bandwidth. For each event, the trace was cut by a time window with a length of 512 ms at around the arrival of the S wave, and the average coherency in the frequency range from 40 Hz - 97 Hz (resolution 0.977 Hz) was then evaluated. A coherency threshold of 0.68 was used to identify multiplets. This threshold has previously been established by the authors through experiments. In this study, we have clustered events under a criterion such that any event with at least one coherency link to the other events within a cluster is included in that multiplet cluster. In effect this means that within a multiplet cluster there may be some pairs of events which do not have direct coherence links. A circular graphic chart of the multiplet percentage is shown in Figure-5. Figure-6 shows a example traces of identified multiplets. Figure 6. An example of multiplet group at Reihen-2 station. Figure 7. Location of the events after the Coherence-collapsing (black circles: multiplets, grey circles: single events). 267
Figure 8. Source migration after the Coherence-collapsing (black circles: multiplets, grey circles: single events). As a next step all events were relocated by a joint hypocenter determination (Frohlich, 1979). The resulting hypocenters of the multiplets and incoherent events (single events) were then relocated by the Coherence-collapsing method (Asanuma et al., 2003), which is a variation of a statistical optimization technique of the whole cloud, the Collapsing method (Jones and Stewart, 1997). The distribution of the events after the Coherence-collapsing is shown in Figure-7, where multiplets are plotted by solid black circles over single events in grey circles. The microseismic source migration is plotted with the hydraulic record from the stimulation in Figure-8. Current Interpretation From the results shown in Figures 2-8, the authors currently interpret the characteristics of the microseismic events and the response of the stimulated rock mass as follows: * Generally, the collected microseismic signals had reasonable signal to noise ratio (SNR) for reliable picking and coherency evaluation. The introduction of a 24 bit high resolution acquisition system made it possible to analyze events with a wide variation in magnitude. It should also be noted that the station geometry did not impose any strong heterogeneous error distribution. The residual in the SED is around 5 ms, which corresponds to an error ellipsoid (1 σ) with a size of around 40 m. The confidence ellipsoids had vertical and horizontal orientations which are consistent with that of the whole seismic cloud. However, considering the size of the error ellipsoids, it is unlikely that the orientation of the seismic cloud is strongly affected by the error. * The seismic cloud showed a subvertical and nearly planar structure with an orientation at N159 E. This trend is similar to the seismic cloud at Soultz which suggests that the stress state and orientation of the pre-existing fractures may be similar at both sites in the Rhine Graben. * The percentage of multiplets (around 70%) is smaller than that for the data from the Australian HFR site in the Cooper Basin (96%) (Asanuma et al., 2004), where two or three large existing fracture zones with a subhorizontal orientation were mainly stimulated. On the other hand, the percentage of multiplets for the data collected at Soultz was only around 37% (shallow reservoir), and 58% (deep reservoir) (Moriya et al., 2002, 2003) suggesting that the stimulation process may be simpler at Basel than at Soultz, even though both sites are in the Rhine Graben. * After coherence-collapsing, a zone with lower seismic activity (aseismic zone) clearly appeared at the south side of the injection well. There are two possible interpretations of this aseismic zone depending on permeability. High permeability could be due to previous natural slip and associated de-stressing. This would suppress microseismicity during the hydraulic stimulation. Alternatively, the lack of seismicity could indicate a region of low permeability into which the stimulation fluid had no access. We currently understand that this aseismic zone is related to an impermeable zone because the seismic cloud extended along this aseismic zone not passing through this zone. * There is some correlation between the appearance of the multiplets and the change in the flow rate during the stimulation. These new multiplet groups tended to appear at the edge of the seismic cloud perhaps correlating with the creation of new flow paths. * Continued extension of the seismic cloud occurred after pumping stopped. These events are considered as shut-in events, which are induced by the increase of pore pressure at the edge of the stimulated zone because of vanishing of pressure loss associated with water flow (Hayashi et al., 1991). * Although the bleed valve was opened after pumping stopped, the observed microseismic activity continued for a long time. This suggests that the fractures were nearly under critical stress state for shear slip and that the stimulated zone has a rather closed hydraulic nature. 268
* The multiplets were widely distributed within the seismic cloud. This may be correlated with dominant flow paths created within the seismic cloud by the stimulation and increased reservoir pressure resulting in multiple slips. In principle, the orientation of the seismic structure of each multiplet group can be effectively used to interpret/ understand the reservoir creation process (Evans et al., 2005). However, the current results do not have sufficient resolution. Further relocation using high resolution relative mapping techniques will be required. Conclusion Recording and current processing of the microseismic results collected during the December 2006 hydraulic stimulation of Basel-1 has yielded useful mapping results. The quality of the seismic signal and network station geometry are satisfactory for reliable hypocenter mapping and for the continuative analysis (see below). The mapped seismic cloud of events was found to be sub-vertical and oriented at N159 E. Of the total events processed, 70% were identified as multiplets which are considered to be indicative of repeated slip on individual planes. Although further investigation is needed, we currently interpret that dominant flow paths were created through the granite rock mass by the stimulation. This encouraged the development of the multiplets. Ongoing work includes precise multiplet relocation and estimation of their origin as well as source mechanism and magnitude analyses. Acknowledgements The collaborative microseismic monitoring work was only possible with much help from Geothermal Explorers Ltd. and Geopower Basel AG, who gave us this opportunity to publish the results. We also thank Dr. Ben Dyer, Semore Seismic, and Dr. Prame Chopra, Earthinsite, for their comments and suggestions on the data analysis. Part of this study is supported by JOGMEC. References Asanuma, H., Kumano, Y., Izumi, T., Soma, N., Kaieda, H., Aoyagi, Y., Tezuka, K., Wyborn D., and Niitsuma, H., 2004, Microseismic monitoring of a stimulation of HDR reservoir at Cooper Basin, Australia, Geothermal Resources Council Transactions, v. 28, p. 191-195. Asanuma, H., Izumi, T., Niitsuma, H., Jones, R., and Baria, R., 2003, Development of coherence collapsing method and its application to microseismicity collected at Soultz, Geothermal Resources Council Transactions, v. 27, p. 349-353. Evans, K., Moriya, H., Niitsuma, H., Jones, R. H., Phillips, W. S., Genter, A., Sausse, J., and, Baria, R., 2005, Microseismicity and permeability enhancement of hydro-geologic structures during massive fluid injection into granite at 3km depth at the Soultz HDR site, Geophysical Journal International, v. 160, p. 388-412. Frohlich, C., 1979, An efficient method for joint hypocenter determination for large groups of earthquakes, Computational Geoscience, v. 5, p. 387-389. Hayashi, K., and Haimson, B. C., 1991, Characteristics of shut-in curves in hydraulic fracturing stress measurements and determination of in situ minimum compressive stress, JGR, v. 96, p. 18311-18321. Jones, R. H., and Stewart, R. C., 1997, A method for determining significant structures in a cloud of earthquakes, JGR, v. 102, p. 8245-8254. Kumano, Y., Asanuma, H., Niitsuma, H., Tezuka, K., and Kamitsuji, R., 2006, Delineation of reservoir structure at Yufutsu gas field, JAPAN by analysis of induced microseismic multiplets, SEG Expanded Abstracts, p. 600-604. Moriya, H., Niitsuma, and H., Baria, R., 2003, Multiplet-clustering analysis reveals structural details within the seismic cloud at the Soultz geothermal field, France, Bull. Seismological Society of America, v. 93, p. 1606-1620. Moriya, H., Miyano, S., Niitsuma, and H., Baria, R., 2002, Fracture system and stress field of Soultz deep reservoir estimated by mulisipletclustering analysis of microseismic events, Geothermal Resources Council Transactions, v. 26, p. 229-233. 269
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