Hydrogen storage in porous media shows promise if we can effectively understand and manage its behavior. Unlike CO2, hydrogen is highly mobile, may react in situ with rocks and fluids, and be affected by microbial activity. Though few have been conducted, these complexities are best explored through subsurface experiments. Our goal is to take a step-wise approach to understanding H2 behavior in porous media with the first stop being to inject H2 into water-bearing sandstone to address fundamental questions. The small-scale nature of the injection requires a geophysical monitoring design capable of providing detailed insights. Through reservoir simulations, we have determined that closely spaced (15-30 m) monitoring wells are ideal for studying H2 flow. This spacing allows for high-resolution cross-well seismic and Electrical Resistivity Tomography (ERT), which can reveal the migration of H2 and determine if fingering occurs. Rapid changes in gas residual saturation can be tracked, with ERT playing crucial role in verifying simulation results. Cross-well seismic data illuminate the plume along a 2D cross-section. To characterize the plume shape as a prominent diffractor in 3D, we will use multi-offset, multi-azimuth DAS VSP with permanent fibers in two wells to detect plume asymmetry and preferential pathways.The initial design is being validated through numerical simulations, from fluid flow models to geophysical properties using full-waveform modeling. The modeling includes the borehole environment, replicating realistic source and receiver radiation patterns, and assessing energy loss to tube waves. Despite using permanent sensors for seismic and ERT measurements, these near-field changes may alter source/receiver responses, complicating cross-well interpretations. The repeatability of non-permanent wireline sources will also be evaluated.The next step is to validate the design by conducting a comprehensive field characterization exercise to establish the signal-to-noise ratio, availability of desired signals, and repeatability of each technique planned for the monitoring phase.We will present a tentative design based on reservoir simulations and assess value of each geophysical measurement and their combination for understanding H2 migration, paving the way for the actual field test.

Monitoring changes in the subsurface associated with hydrocarbon production, geothermal energy extraction, or carbon dioxide sequestration relies on the ability to detect subtle changes in seismic signals over time. Accurate characterization of the subsurface requires high-resolution seismic data. The heterogeneities in the near-surface geological environments cause seismic waves to scatter, leading to severe distortions in seismic signals that are often difficult to interpret. Scatterednoise obscures essential geological features, making distinguishing between reflections and noise difficult and reducing the effectiveness of monitoring efforts. This kind of noise, sometimes called “seismic speckle noise,” impacts seismic data quality, complicating the seismic characterization and monitoring in sedimentary and crystalline environments. Using high-density geophone arrays and distributed sensing can suppress the effect of strong near-surface scatterings. However, finding ways to mitigate the noise could significantly improve efforts and reduce the number of instruments needed. To address the problem, it is crucial to understand the near-surface scattering better. We describe a model similar to scattering phenomena observed in optics and acoustics, which explains wavefield distortions in seismic waves. Our multiplicative-noise mathematical model simulates two significant types of noise: random phase perturbations and random time shifts, both of which are assumed to follow a normal distribution akin to that observed in field data. We illustrate speckle noise through numerical simulations and scrutinize its phase and amplitude characteristics across time and frequency domains in broadband seismic data. We investigate the transformation of the amplitude and phase of locally stacked data and demonstrate that the combined action of phase perturbations and residual statics could explain the distortions observed in field land seismic data from a desert environment. This understanding paves the way for mitigation strategies.