Engineering topics
Publications and source records attributed to Matzel, Eric.
We proposed to conduct the following activities in Budget Period 2 with respect to Task 2.1 of the overall project management plan: 1) Local SWS using microseismicity catalog. 2) Continuation of VSM analysis. 3) Synthesis of seismic data and uncertainty analyses. Milestone G: Apply ANT, VSM, and SWS methods to Kansas microseismicity catalog. Calculate 3D model and moment tensor elements and meet milestone E.
Predictions of the long term stability of the major ice sheets depend on the ability to identify where melt is occurring and to monitor changes over time. Particularly important is the detection of melting along the grounding line, where the glacier is in contact with the solid earth. Melting along the grounding line significantly increases the speed at which glaciers flow, increasing the risk of ice sheet collapse. Passive seismology offers an effective, relatively low cost and precise means of measuring the dynamic changes in the ice. If we can demonstrate its effectiveness, it would allow continuous monitoring of the critical contact between the ice-sheet and the subsurface. The purpose of this study was to determine whether this method can be applied to detect liquid water within the glacial ice system using currently available data. The objectives would be: (1) To identify the attenuation characteristics of glacial ice and the contrast within fractured and fluid-filled zones. (2) To map fluid-solid contacts within the ice sheets and particularly between ice and the underlying solid earth. (3) To identify changes in the system over time. (4) To identify an optimal network configuration for the purposes of monitoring critical points within the glacier
Abstract not provided.
CCT is a Java based application for calibrating 10 shear wave coda measurement models to observed data using a much smaller set of reference moment magnitudes (MWs) calculated from other means (waveform modeling, etc.). These calibrated measurement models can then be used in other tools to generate coda moment magnitude measurements, source spectra, estimated stress drop, and other useful measurements for any additional events and any new data collected in the calibrated region.
Abstract not provided.
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also included are links to the documentation for the dataset, Jupyter Notebook tutorials for working with the data as it is stored in AWS S3, and links to data viewers in OEDI for the horizontal (DASH) and vertical (DASV) DAS datasets. Horizontal DAS (DASH) data collection began 3/8/16, paused, and then started again on 3/11/2016 and ended 3/26/2016 using zigzag trenched fiber optic cabels. Vertical DAS (DASV) data collection began 3/17/2016 and ended 3/28/16 using a fiber optic cable through the first 363 m of a vertical well. These are raw data files from the DAS deployment at (DASH) and below (DASV) the surface during testing at the PoroTomo Natural Laboratory at Brady Hot Spring in Nevada. SEG-Y and hdf5 files are stored in 30 second files organized into directories by day. The hdf5 files available via HSDS are stored in daily files. Metadata includes information on the timing of recording gaps and a file count is included that lists the number of files from each day of recording. These data are available for download without login credentials through the free and publicly accessible Open Energy Data Initiative (OEDI) data viewer which allows users to browse and download individual or groups of files.
These files are ambient noise correlation (ANC) functions calculated for 11 days of continuous seismic data recorded by the Lawrence Berkeley network in the Brady geothermal field. These are SAC formatted seismic waveforms. The stations included are BPB04, BPB05, BPB07, BPB08, BPRT1, BPRT2, BPRT3, BPRT5, BRB10, BRP01, BRP02, BRP03, BRP04, BPR06, and BRP09 The original data were cut into hour long traces and processed by differentiating, removing the mean, removing the trend, applying a 1% taper, whitening, removing the mean and trend again, and converting to single bit traces. The data were then correlated with those from other stations and stacked. The resulting files were then named according to the convention: STA1.STA2.CHAN1_CHAN2.NHOURS.stacked.sac The days included are from records during 2013 (julian days, 200,220-229). The ANC correlations were calculated on the raw data traces (without instrument corrections applied) to assess the quality of the signal as a function of frequency throughout the network. The data were recorded at 500 Hz. We observe high quality signals 30 Hz on all traces, and measurable signal up to 80 Hz on a subset of the traces.
A global validation dataset of 116 seismic events and 20,977 associated Pn and P arrivals is used to assess travel-time prediction and event location accuracy for the global-scale, 3D, P-wave velocity model called LLNL-G3Dv3 (Simmons et al., 2012). Strong regional trends that are observed for ak135 travel-time residuals are largely removed when LLNL-G3Dv3 is used for prediction. The 25th–75th quantile spread of travel-time residuals is reduced by 30%–40% at teleseismic distances, and the spread is reduced by ~60% at regional distances (<16°). Epicenter error decreases when more data are used to constrain event locations until more than ~40 arrivals times are used. At which point, epicenter error reduction tends to plateau. Median epicenter errors for the ak135 and LLNL-G3Dv3 models plateau at ~8:0 and ~5:5 km, respectively, for teleseismic P datasets. Median epicenter errors for the ak135 and LLNL-G3Dv3 models plateau at ~12:0 and ~4:0 km, respectively, for regional Pn datasets. We demonstrate that spatially correlated travel-time residual errors for the ak135 model lead to increasing epicenter error when ~40 to ~100 Pn arrivals are used to constrain the location. The effect of correlated error is mitigated by LLNL-G3Dv3, for which epicenter error steadily decreases to ~4 km when 100 Pn arrivals are used. The median area of 0.95 epicenter probability bounds for ak135 and LLNL-G3Dv3 are 1811 and 758 km 2 , respectively. The ak135 ellipses are inflated to achieve the desired rate of true events occurring inside the probability region, whereas LLNLG3Dv3 error ellipses based on empirical residual distributions cover the true location at the expected rate because location bias is minimal.
Effective enhanced geothermal system (EGS) sites require optimal fracture networks for efficient heat transfer between hot rock and fluids. Microseismic mapping is a key tool used to infer the subsurface fracture geometry and is widely used in the petroleum industry to monitor fracture propagation during hydraulic stimulations. Traditional earthquake detection techniques (e.g. STA/LTA detectors) and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection even in difficult signal processing environments.
Not Available