Microseismic source physics reveals selective permeability enhancement in fractured crust

# Description of Uploaded Data and Code Files Xiao Tian, Quan Gan, Pengliang Yu, Hao Zhang, Chongyuan Zhang, Sida Jia, Zhenjiao Jiang, Manchao He, and Derek Elsworth. Microseismic source physics reveals selective permeability enhancement in fractured crust. ## 1. Microseismic Event Catalog (`event data.csv`) Catalog containing 934 event records, including event number, origin time, location and processing flags, local north-east-down coordinates, and local magnitude. A total of 579 records are marked as located and contain valid coordinates. ## 2. Receiver Locations (`20receivers.csv`) Locations of the 20 surface receivers used for microseismic monitoring. Columns include receiver name, identifier, horizontal coordinates, and TVDSS. ## 3. Velocity Model (`velocity_data_gonghev1.xlsx`) One-dimensional velocity model derived from the Gonghe site data. The file contains depth, P-wave velocity, and S-wave velocity. ## 4. Well Trajectories (`GH-01 Survey.csv`, `GH-02 Survey.csv`, and `GH-03 Survey.csv`) Survey data describing the trajectories of wells GH-01, GH-02, and GH-03. ## 5. Source Radius and Stress-Drop Code (`source_radius_and_stress_drop.py`) Python code for waveform quality control, multi-station spectral fitting, corner-frequency estimation, and calculation of source radius, seismic moment, and stress drop. ## 6. Rupture Geometry and Mode Code (`rupture_geometry_and_mode.py`) Python code for three-component waveform processing, moment-tensor inversion, fracture-plane geometry estimation, rupture-mode classification, and stability testing. ## 7. Fracture Permeability Upscaling Code (`fracture_permeability_upscaling.py`) Python code for mapping event-level permeability increments from oriented circular fracture discs onto a three-dimensional regular grid using a Sneddon-type aperture profile, the cubic law, and conservative area integration. ## 8. Seismic Waveform Data The waveform data used for the spectral and moment-tensor analyses are not publicly available because their distribution is restricted by relevant data-sharing policies.