Pore-scale studies involve using pore-scale imaging (e.g., micro CT scan) and modeling (e.g., solving Navier-Stokes equation, Poisson Equation) techniques to understand the fundamental properties and processes governing the macroscopic or effective properties of geological materials. Current focuses include electrical resistivity, hydraulic conductivity, streaming potential, and spectral induced polarization. Some examples are shown below.
Pore-Scale simulation of induced polarization in frequency domain
The induced polarization of porous geological materials results mainly from the electrical double layer (EDL) formed at the solid-liquid interface in response to the charged mineral surface. Under an external electric field, the charge in EDL may change its spatial distribution and store part of the energy. The induced polarization is used to quantify the material's ability to store energy. We have developed schemes that can incorporate this microscopic polarization mechanism into a pore-scale numerical simulation. By doing this, the spectral induced polarization of a porous medium can be reproduced computationally once the microstructure of the material is known (e.g., from micro-CT scan). This technique can be used to study the factors controlling the spectral induced polarization of geological materials.
Rock under mineral precipitation and dissolution
The physical properties of rocks evolve continuously during diagenesis in response to the changes in microstructure. A clear understanding of the diagenetic control is crucial for developing physics-based models for many hydrogeological applications involving water-rock interactions, e.g., CO2 sequestration, bioremediation, and bio-mediated soil improvement. We incorporated the mineral precipitation/dissolution process in traditional digital rock physics such that the macroscopic properties of the rock can be reproduced as well also the microstructure changes. Different end-members conditions can also be considered (e.g., transport limited or reaction limited cases).
Laboratory scale studies use lab instruments to measure physical properties of soils and rocks at different hydrological, chemical, or mechanical conditions and study the factors (materials structure or environmental conditions) controlling these properties. Lab-scale studies also include the development of theoretical models (mostly physics-based) to describe soil/rock properties and the development of new data-processing techniques to extract more information from lab measurements.
Integrated hydrogeophysical soil column
In hydrogeophysical applications, it is critical to extract the hydrological information from geophysical measurements. The key in this interpretation process is the knowledge of both geophysical and hydraulic properties of geological materials. We have developed an integrated soil column system, which can be arranged to conduct both saturated and unsaturated flow tests on the same soil sample; the electrical responses of the flows can also be monitored. These data can be processed to acquire electrical resistivity, induced polarization, and hydraulic conductivity of soils under both saturated and unsaturated conditions. The soil water retention curve may also be estimated. Potential applications of this soil column include critical zone materials, aquifer materials, etc.
Joint inversion of SIP and NMR data
Spectral induced polarization and nuclear magnetic resonance have been used to estimate the pore size distribution of porous geological media. Each method has its only advantages and limitations. To improve the pore size distribution estimation, we proposed a method that can jointly use SIP and NMR data. Both synthetic and real samples demonstrate the usefulness of the new data processing method. The method can be updated in the future by employing new and more advanced petrophysics models. It can also be used to evaluate the performance of the petrophysical models.
Incorporate subsurface structure into soil moisture estimation from resistivity
The electrical resistivity method has been frequently used to estimate the moisture content in the field. The uncertainty associated with resistivity-estimated moisture content is mainly from two sources: regularized inversion and petrophysical interpretation. In this study, we use subsurface structural information from seismic data to relax the smoothness-based regularization at structural boundaries. In addition, we also use structural unit-specific petrophysical relationships to translate resistivity into moisture content. Examples (e.g., above figure) have shown that spatial patterns and the moisture content values estimated with the new method are very close to the true model with low uncertainty.