The Kimberlina synthetic multiphysics dataset for <scp>CO₂</scp> monitoring investigations

We present a synthetic multi-scale, multi-physics dataset constructed from the Kimberlina 1.2 CO2 reservoir model based on potential storage site in Southern San Joaquin Basin of California. Among 300 models, one selected reservoir-simulation scenario produces hydrologic-state models at onset and after 20 years injection. Subsequently, these were transformed into geophysical properties, including P- S-wave seismic velocities, saturated density where saturating fluid can be combination brine supercritical CO2, electrical resistivity using established empirical petrophysical relationships. From 3D distributions we have generated time-lapse seismic, gravity electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys are achievable actual field situations. also created series well logs saturation, acoustic velocity, induction injection three wells. These by combining low-frequency trend high-frequency variations collected site. In addition, to better calibrate our datasets, measurements permeability pore connectivity been made cores Vedder Sandstone, which forms primary unit. provide range scales otherwise as close real-world situation possible. This consisting simulated testbed for designing testing systems imaging characterization algorithms. The suite numerical data publicly available downloading National Energy Technology Laboratory's (NETL) Data Exchange (EDX) website.