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An extensive vertical seismic profiling (VSP) survey using wireline distributed acoustic sensing (DAS) technology was carried out between the 15th and 18th of February 2017 at the geothermal in-situ laboratory Groß Schönebeck, Germany. Borehole measurements were recorded in two 4.3 km deep wells E GrSk 3/90 and Gt GrSk 4/05. Two hybrid fibre optics cables were freely lowered inside the wells to form dense receiver arrays. As a seismic source, four heavy vibroseis trucks were used. The survey consisted of 61 source positions distributed in a spiral pattern around the target area. This data publication consists of raw uncorrelated seismic data acquired for 3D seismic imaging purposes. Supplementary information such as well trajectories, source point coordinates, and the pilot sweep data is also provided. Data related to zero-offset measurements can be found in Henninges et al. (2021, https://doi.org/10.5880/GFZ.4.8.2021.001). Further details on the survey design and data acquisition parameters can be found in Henninges et al. (2021, https://doi.org/10.5194/se-12-521-2021); Martuganova et al. (2021, 2022). Information on high-resolution 3D reflection seismic acquisition campaign carried out at Groß Schönebeck in February–March 2017 can be found in Krawczyk et al. (2019); Bauer et al. (2020); Norden et al. (2022). The 3D DAS VSP processing workflow, 3D DAS imaging results, and comparison with 3D surface seismics are presented in Martuganova et al. (2022).
Between early 2018 and late 2019 the STIMTEC hydraulic stimulation experiment was performed at ca.~130 m below surface at the Reiche Zeche underground research laboratory in Freiberg, Saxony/Germany. The project aimed at gaining insight into the creation and growth of fractures in anisotropic and heterogeneous metamorphic gneiss , to develop and optimise hydraulic stimulation techniques and to control the associated induced seismicity under in situ conditions at the mine-scale. These aspects of failure and associated seismicity are important for the development of enhanced geothermal energy systems. A combined seismic network consisted of 12 single-component acoustic emission sensors (sensitivity 1-100 kHz) and three single-component Wilcoxon accelerometers (sensitivity 50 Hz-25 kHz) were installed in boreholes drilled into the test volume, surrounding the stimulation site (Figure 1). A stimulation borehole with 63 m length was drilled with 15° northward inclination. This data set of 314 active ultrasonic transmission (UT) measurements is supplementary to Boese et al. (2021, in review), which introduces the STIMTEC experiment and its active measurement campaigns. This data set was used to derive an anisotropic velocity model for the STIMTEC rock volume. The active seismic data provided here are from six boreholes (BH09, BH10, BH12, BH15, BH16, BH17) as shown in Figure 1. of the associated data description. There are three tables provided as metadata that contain the STIMTEC sensor coordinates, event information of the 314 UT measurements and the UT picks. The UT measurements were recorded with a sampling rate of 1 MHz and results from an automatic stack of 1024 UT pulses generated by the ultrasonic transmitter and recorded by the STIMTEC sensors. The UT measurements are saved in binary file format (fsf file format). Fsf-files can be processed with FOCI software: https://www.induced.pl/software/foci Each fsf file contains 32768 samples, which corresponds to 0.032768 seconds. All UT event files were manual inspected and phase arrivals identified. These are stored in the fsf-file header as well as in the table STIMTEC_UT_picks.csv.
In 2020 and 2021 the STIMTEC-X hydraulic stimulation experiment was performed at ca.~130 m below surface at the Reiche Zeche underground research laboratory in Freiberg, Saxony/Germany. The project temporally followed the STIMTEC experiment at the same site and aimed at understanding the stress heterogeneity of the anisotropic and metamorphic gneiss rock mass. The STIMTEC-X experiment applied the hydraulic stimulation technique in several boreholes at the mine-scale. Complementary to the stimulations, there were active seismic ultrasonic transmission data acquired before the stimulations. We use a seismic monitoring network consisting of six single-component acoustic emission (AE) sensors (sensitivity 1-60 kHz), six hydrophone-like AE sensors (sensitivity 1-40 kHz) and four to twelve single-component Wilcoxon accelerometers (sensitivity 50 Hz-25 kHz). The AE sensors and remained stationary in sub-horizontal and upwards reaching boreholes, the accelerometers were mostly installed along the tunnel walls with one accelerometer in a shallow borehole in each tunnel, and the hydrophone-like AE sensors were installed in the down-going water filled boreholes, but repositioned for each measurement campaign (Figure 1). This data set of 120 active ultrasonic transmission (UT) measurements is supplementary to Boese et al. (2022, in review), which introduces some of the active measurement campaigns of the STIMTEC-X experiment in detail. The whole data set togetter with the “Ultrasonic transmission measurements from six boreholes from the STIMTEC experiment, Reiche Zeche Mine, Freiberg (Saxony, Germany)” [https://doi.org/10.5880/GFZ.4.2.2021.002] was used to evaluate performance measures such as sensitivity and frequency bandwith, coupling, placement and polarity of the hydrophone-like AE sensor compared to AE sensors. The active seismic data provided here are from seven boreholes (BH01, BH05, BH06, BH10, BH14, BH18, BH19) as shown in Figure 1. There are nine tables provided as metadata of which seven contain the STIMTEC-X sensor coordinates for each measurement campaign, the event information of all the 120 UT measurements and the UT picks. The UT measurements were recorded with a sampling rate of 1 MHz and results from an automatic stack of 1024 UT pulses generated by the ultrasonic transmitter and recorded by the STIMTEC-X sensors. The UT measurements are saved in binary file format (fsf file format). Fsf-files can be processed with FOCI software: https://www.induced.pl/software/foci. Each fsf file contains 32768 samples, which corresponds to 0.032768 seconds. All UT event files were manual inspected and phase arrivals identified. These are stored in the fsf-file header as well as in the table STIMTECX_UT_picks.csv.
This data publication contains vertical seismic profiling (VSP) data collected at the Groß Schönebeck site, Germany, from February 15-18, 2017. Energy excitation was performed with vibroseis sources. Data was acquired in the two 4.3 km deep wells E GrSk 3/90 and Gt GrSk4/05 using hybrid wireline fiber-optic sensor cables and distributed acoustic sensing (DAS) technology. The survey design and data acquisition, the overall characteristics of the acquired data, as well as the data processing and evaluation for a zero-offset source position are described in the paper of Henninges et al. (2021) published in Solid Earth. The data for several source positions presented in this paper is contained here, mostly in the form of full waveform data stored in seg-y format. A detailed description of the individual data sets is given in the attached data description document.
For the safe and sustainable use of deep geothermal wells, construction must proceed as intended. An integer well ensures that all fluids within the borehole are always under control. One of the most critical steps is the cementing of the casings. Despite extensive experience in the petroleum industry, challenges with well integrity are a worldwide phenomenon. One reason could be that conventional measurement methods can only verify the success of cementing once the cement job has been completed. In contrast, distributed fiber optic sensing methods can monitor the entire cementing process along the entire drilling path. This data set contains the results of the Distributed Temperature Sensing (DTS) and the derived product "vibrational energy" of a Distributed Dynamic Strain Sensing (DDSS or DAS) of the whole cementing process. We collected this data during the primary cementing of an injection well's 874m surface casing at the geothermal site Schäftlarnstr, Munich. We measured the cement placement and 24 hours of the early hydration. We obtained the data with a fiber optic cable permanently deployed behind the casing. The cable contained Multi-Mode fibers (for DTS) and Single-Mode fibers (for DAS). Table 1 in the data description document shows the units used and the key parameters of our measurement. In the first step, we allocated each channel to its depth in the borehole. We used a cold spray (for DTS) and a tap test (for DAS) to locate the entry to the borehole. To obtain the vibrational energy of the DAS data, we summarized the raw dynamic strain with a Root Mean Square (RMS) in a window of 60 seconds. We calculated the vibrational energy for a wide range of different frequency ranges (Butterworth bandpass). The data are provided in csv formats and further explained in the data description document. Acknowledgement: GFK-Monitor is funded by the Federal Ministry for Economic Affairs and Climate Action via the Project Management Jülich (PTJ) (funding code: 03EE4036, project duration: July 1, 2022 - June 30, 2025). The fiber optic infrastructure was provided by GAB (Geothermie Allianz Bayern): Funded by: Bayerisches Staatsministerium für Wissenschaft und Kunst (Hauptgebäude: Salvatorstraße 2, 80333 München).
The dataset is supplementary material to Kwiatek et al. (2019, Science Advances).The dataset is a refined seismic catalog acquired during the hydraulic stimulation of the future geothermal sites located in Espoo, Finland. There, the injection well, OTN-3, was drilled down to 6.1 km-depth into Precambrian crystalline rocks. Well OTN-3 was deviated 45° from vertical and an open hole section at the bottom was divided into several injection intervals. A total of 18,159 m3 of fresh water was pumped into crystal-line rocks during 49 days in June- and July, 2018. The stimulation was monitored in near-real time using (1) a 12-level seismometer array at 2.20-2.65 km depth in an observation well located ~10 m from OTN3 and (2) a 12-station network installed in 0.3-1.15 km deep bore-holes surrounding the project site. On completion of stimulation it the catalog contained 8452 event detections overall, and 6152 confirmed earthquakes located in the vicinity of the project site (epicentral distance from the well head of OTN-3 <5 km). These were recorded in a time period lasting 59 days: 49 days of active stimulation campaign and the 10 days following completion.The initial industrial seismic catalog of 6150 earthquakes was manually reprocessed. The P- and S-wave arrivals of larger seismic events with M>0.5 were all manually verified, and, if necessary, refined. Earthquakes with sufficient number of phases and seemingly anomalous hypocenter depths (e.g. very shallow or very deep) were manually revised as well. The hypocenter locations were calculated using the Equivalent differential time method and optimized with an Adaptive Simulated Annealing algorithm. The updated catalog contained 4,580 earthquakes that occurred at hypocenter depths 4.5-7.0 km, in the vicinity of the stimulation section of OTN-3. To increase the precision of their locations, the selected 2155 earthquakes with at least 10 P-wave and 4 S-wave picks were relocated using the double-difference relocation technique. The relocation uncertainties were estimated using bootstrap resampling technique. The relocation reduced the relative precision of hypocenter determination to approx. 66 m and 27 m for 95% and 68% of relocated earthquakes. The final relocated catalog that constitutes the here published contained 1,977 earthquakes (91% of the originally selected events).
The GFZ-Landsvirkjun Theistareykir Fibre array is located in the Theytareykir geothermal area, in North Iceland. It is collocated with arrays of broadband seismometers and gravity meters (see e.g., https://doi.org/10.1186/s40517-021-00208-w). The geometry of the fibre array is following the telecom network in the area, and was chosen to test the seismological capabilities of telecom cables in this geothermal environment. We connected an iDAS V2 interrogator from Silixa. The interrogator location is lat=65.898041, lon=-16.966274. The array starts N-S and after 1.5 km, turns towards the East, up to a local transmission antenna station for mobile phones. The length of the path is ~5 km. The length of the cable is actually more than 15 km, as other fibre instance is connected at the transmission antenna station.. Jumps were performed along the cable to geo-locate the channels. The exact location of the fibre can unfortunately not be disclosed. Original recordings at 1000 Hz were downsampled to 200 Hz using a software from INGV-OE (michele.prestifilippo@ingv.it) and are provided in an h5 format. We provide here the first fibre instance (5 km long). The data contain 1 h long recording intervals framing M>5 teleseismic earthquakes recorded in the frame of the global DAS month, an initiative to collaboratively record and share simultaneously recorded DAS data from all over the world (https://www.norsar.no/in-focus/global-das-monitoring-month-february-2023). DAS is an emerging technology increasingly used by seismologists to convert kilometer long optical fibers into seismic sensors.
This data publication contains seismic waveform data of 507 earthquakes recorded during the St1 Deep Heat project in June and July 2018, where the 6.1 km deep OTN-3 well near Helsinki, Finland, was hydraulically stimulated over 49 days (Kwiatek et al., 2019). The waveforms were recorded on a surrounding seismic monitoring network consisting of 12 stations, deployed at epicentral distances between 0.6 to 8.2 km and at depths between 0.23 to 1.15 km. Each station consists of three-component, 4.5 Hz, Sunfull PSH geophones, sampling at 500 Hz. The 507 earthquakes analysed were chosen from the relocated event catalogue by Leonhardt et al. (2021a). The dataset is supplementary material to the Geophysical Research Letters research article of Holmgren et al. (2022), which applied the Empirical Green’s Function technique to examine microseismic rupture behaviour at the Helsinki site.
This data set is supplementary to the BSSA research article of Blanke et al. (2019), in which the local S-wave coda quality factor at The Geysers geothermal field, California, is investigated. Over 700 induced microseismic events recorded between June 2009 and March 2015 at 31 short-period stations of the Berkeley-Geysers Seismic Network were used to estimate the frequency-dependent coda quality factor (Q_C) using the method of Phillips (1985). A sensitivity analysis was performed to different input parameters (magnitude range, lapse time, moving window width, total coda length and seismic sensor component) to gain a better overview on how these parameters influence Q_C estimates. Tested parameters mainly show a low impact on the outcome whereas applied quality criteria like signal-to-noise ratio and allowed uncertainties of Q_C estimates were found to be the most sensitive factors.Frequency-dependent mean-Q_C curves were calculated from seismograms of induced earthquakes for each station located at The Geysers using the tested favored input parameters. The final results were tested in the context of spatio-temporal behavior of Q_C in the reservoir considering distance-, azimuth and geothermal production rate variations. A distance and azimuthal dependence was found which is related to the reservoir anisotropy, lithological-, and structural features. By contrast, variations in geothermal production rates do not influence the estimates. In addition, the final results were compared with previous estimated frequency-independent intrinsic direct S-wave quality factors (Q_D) of Kwiatek et al. (2015). A match of Q_D was observed with Q_C estimates obtained at 7 Hz center-frequency, suggesting that Q_D might not be of an intrinsic but of scattering origin at The Geysers. Additionally, Q_C estimates feature lower spreading of values and thus a higher stability.The Geysers geothermal field is located approximately 110 km northwest of San Francisco, California in the Mayacamas Mountains. It is the largest steam-dominated geothermal reservoir operating since the 1960s. The local seismicity is clearly related to the water injections and steam production with magnitudes up to ~5 occurring down to 5 km depth, reaching the high temperature zone (up to 360°C). The whole study area is underlain by a felsite (granitic intrusion) that shows an elevation towards the southeast and subsides towards northwest. A fracture network induces anisotropy into the otherwise isotropic rocks featuring different orientations. Moreover, shear-wave splitting and high attenuating seismic signals are observed and motivate to analyze the frequency-dependent coda quality factor.Two data sets were analyzed: one distinct cluster located in the northwest (NW) close to injection wells Prati-9 and Prati-29, and the other one southeast (SE) of The Geysers, California, USA, close to station TCH (38° 50′ 08.2″ N, 122° 49′ 33.7″ W and 38° 46′ 59.5″ N, 122° 44′ 13.2″ W, respectively).The frequency-dependent coda quality factor is estimated from the seismic S-wave coda by applying the moving window method and regression analysis of Phillips (1985). Different input parameters including moving widow width, lapse time and total coda length are used to obtain Q_C estimates and associated uncertainties. Within a sensitivity analysis we investigated the influence of these parameters and also of magnitude ranges and seismic sensor components on Q_C estimates. The coda analysis was performed for each event at each sensor component of each station. The seismograms were filtered in predefined octave-width frequency bands with center-frequencies ranging from 1-69 Hz. The moving window method was applied starting in the early coda (after the S-onset) for each frequency band measuring the decay of Power Spectral Density spectra. The decay of coda amplitudes was fitted with a regression line and Q_C estimates were calculated from its decay slope for each frequency band. In a final step a mean-Q_C curve was calculated for each available station within the study area resulting in different curves dependent on event location sites in the northwest and southeast.Data DescriptionThe data contain final mean-Q_C estimates of the NW and SE Geysers, coda Q estimates at 7 Hz center-frequency calculated by using the NW cluster, and initial direct Q estimates of Kwiatek et al. (2015) using the same data of the NW cluster. Table S1 shows final mean coda quality factor estimates obtained from the NW cluster at injection wells Prati-9 and Prati-29. The column headers show stations (station), center-frequencies of octave-width frequency bands in Hertz (f[Hz]), mean coda Q estimates (meanQc) and related standard deviations (std), all obtained by coda analysis. Table S2 shows the final mean coda quality factor estimates obtained from additional selected 100 events in the SE Geysers. Column headers correspond to those in Table S1. Table S3 shows coda Q estimates related to 7 Hz center-frequency. The column headers show stations (station), center-frequency of octave-width frequency bands in Hertz (f[Hz]), coda Q estimates at 7 Hz center-frequency (Q_C) and related standard deviations (std2sigma; 95% confidence level), all obtained by coda analysis. Table S4 shows selected direct S-wave quality factors of Kwiatek et al. (2015) obtained by spectral fitting. The column headers show stations (station) and direct S-wave Q estimates (Q_D). The four tables are provided in tab separated txt format.Tables S3 and S4 are used for a comparative study and displayed in Figure 12 of the BSSA article mentioned above.
This service provides routing information for distributed data centres, in the case where multiple different seismic data centres offer access to data and products using compatible types of services. Examples of the data and product objects are seismic timeseries waveforms, station inventory, or quality parameters from the waveforms. The European Integrated Data Archive (EIDA) is an example of a set of distributed data centres (the EIDA „nodes“). EIDA have offered Arclink and Seedlink services for many years, and now offers FDSN web services, for accessing their holdings. In keeping with the distributed nature of EIDA, these services could run at different nodes or elsewhere; even on computers from normal users. Depending on the type of service, these may only provide information about a reduced subset of all the available waveforms.To be effective, the Routing Service must know the locations of all services integrated into a system and serve this information in order to help the development of smart clients and/or services at a higher level, which can offer the user an integrated view of the entire system (EIDA), hiding the complexity of its internal structure.The service is intended to be open and able to be queried by anyone without the need of credentials or authentication.
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