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[1] We implement and apply a method to the jointly inverted of surface wave group velocities and gravity anomalies observations. Surface wave dispersion measurements are sensitive to seismic shear wave velocities, and the gravity measurements supply constraints on rock density variations. Our goal is to obtain a self-consistent three-dimensional shear velocity-density model with increased resolution of shallow geologic structures. We apply the method to investigate the structure of the crust and upper mantle beneath two large central Asian sedimentary basins: the Tarim and Junggar. The basins have thick sediment sections that produce substantial regional gravity variations (up to several hundred milligals). We used gravity observations extracted from the global gravity model derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. We combine the gravity anomalies with high-resolution surface wave slowness tomographic maps that provide group velocity dispersion values in the period range between 8 and 100 s for a grid of locations across central Asia. To integrate these data, we use a relationship between seismic velocity and density constructed through the combination of two empirical relations. One determined by Nafe and Drake, most appropriate for sedimentary rocks, and a linear Birch's law, more applicable to denser rocks (the basement). An iterative, damped least squares inversion including smoothing is used to jointly model both data sets, using shear velocity variations as the primary model parameters. Results show high upper mantle shear velocities beneath the Tarim basin and suggest differences in lower crust and upper mantle shear velocities between the eastern and western Tarim.Citation: Maceira, M., and C. J. Ammon (2009), Joint inversion of surface wave velocity and gravity observations and its application to central Asian basins shear velocity structure,

We use P wave receiver functions from the western U.S. and adjacent regions to construct a receiver function wavefield interpolation scheme that helps to equalize the lateral sampling of the receiver functions and the surface wave dispersion and to greatly simplify the receiver functions. Spatial interpolation and smoothing suppress poorly sampled and difficult to interpret back azimuthal variations and allow the extraction of the first‐order features in the receiver function wavefield, including observations from several ray parameter ranges. We combine the interpolated receiver functions with Rayleigh wave dispersion estimates and surface gravity observations to estimate the 3‐D shear wave speed beneath the region. Speed variations in the 3‐D model correlate strongly with expected geologic variations and illuminate broad‐scale features of the western U.S. crust and upper mantle. The model is smooth, self‐consistent, and demonstrates the compatibility of the interpolated receiver functions and dispersion observations.

Enhanced Geothermal Systems could provide a substantial contribution to the global energy demand if their implementation could overcome inherent challenges. Examples are insufficient created permeability, early thermal breakthrough, and unacceptable induced seismicity. Here we report on the seismic response of a mesoscale hydraulic fracturing experiment performed at 1.5-km depth at the Sanford Underground Research Facility. We have measured the seismic activity by utilizing a 100-kHz, continuous seismic monitoring system deployed in six 60-m length monitoring boreholes surrounding the experimental domain in 3-D. The achieved location uncertainty was on the order of 1 m and limited by the signal-to-noise ratio of detected events. These uncertainties were corroborated by detections of fracture intersections at the monitoring boreholes. Three intervals of the dedicated injection borehole were hydraulically stimulated by water injection at pressures up to 33 MPa and flow rates up to 5 L/min. We located 1,933 seismic events during several injection periods. The recorded seismicity delineates a complex fracture network comprised of multistrand hydraulic fractures and shear-reactivated, preexisting planes of weakness that grew unilaterally from the point of initiation. We find that heterogeneity of stress dictates the seismic outcome of hydraulic stimulations, even when relying on theoretically well-behaved hydraulic fractures. Once hydraulic fractures intersected boreholes, the boreholes acted as a pressure relief and fracture propagation ceased. In order to create an efficient subsurface heat exchanger, production boreholes should not be drilled before the end of hydraulic stimulations.

The important task of tracking seismic activity requires both sensitive detection and accurate earthquake location. Approximate earthquake locations can be estimated promptly and automatically; however, accurate locations depend on precise seismic phase picking, which is a laborious and time‐consuming task. We adapted a deep neural network (DNN) phase picker trained on local seismic data to mesoscale hydraulic fracturing experiments. We designed a novel workflow, transfer learning‐aided double‐difference tomography, to overcome the 3 orders of magnitude difference in both spatial and temporal scales between our data and data used to train the original DNN. Only 3,500 seismograms (0.45% of the original DNN data) were needed to retrain the original DNN model successfully. The phase picks obtained with transfer‐learned model are at least as accurate as the analyst's and lead to improved event locations. Moreover, the effort required for picking once the DNN is trained is a small fraction of the analyst's.