Gisella Mena

and 1 more

Wyoming’s demonstrated coal reserves have significant potential for hydrogen generation. This study explores the integration of natural resources and advanced technologies for hydrogen production within the state, aligning with the U.S. DOE’s Energy Earthshot initiative and the National Clean Hydrogen Strategy and Roadmap. Wyoming’s coal resources, totaling 1.4 trillion metric tons, with 46 billion metric tons classified as recoverable reserves, present a significant opportunity for hydrogen production through gasification processes. Producing hydrogen from coal, especially when coupled with carbon emission reduction technologies, is a promising near- to mid-term opportunity. This approach leverages Wyoming’s relatively inexpensive and widely available coal resources, using existing gasification technologies to meet anticipate hydrogen demand. Beyond the availability of coal resources, Wyoming’s potential as a hydrogen production hub is supported by its strategic infrastructure and water resources, essential for large-scale hydrogen generation. GIS-suitability index identifies Powder River and Green River Basins as potential viable sites for large-scale hydrogen production facilities in Wyoming State. Also, this study includes an AspenPlus simulation for Supercritical Water Gasification (SCWG) of Wyoming’s coal using a thermodynamic equillibrium model based on Gibbs Free Energy minimization based on the Peng-Robinson EOS with Boston-Mathias alpha function (PR-BM) attribute method. The results underscore Wyoming’s potential to significantly contribute to the energy transition. 

Pablo Godoy

and 2 more

Flow instabilities and viscous fingering limit access to available subsurface pore space for carbon storage. Foams provide a pathway to mitigate these shortcomings and enhance storage capacity in subsurface systems by shifting the flow dynamics toward a stable flow, improving residual gas trapping, and reducing gravity segregation. Foam systems require careful consideration of various factors including surfactant formulation and  effective concentration to maximize foam stability. This work aims to optimize foam stability and carbon storage potential in the context of CCUS, by testing CO2-foams with different surfactant formulations and concentrations using a microfluidic platform. The microfluidic devices contain surrogate porous media that are representative of Berea sandstone and a Indiana limestone. The mediums are designed using X-ray tomography and porosity data from the core samples where pore connections are informed by throat size distribution data. The devices are fabricated utilizing an in-house photolithography method. Surfactants solutions are made using brine and three zwitterionic surfactant formulations with varying concentrations, ranging from below to above the critical micellar concentration (CMC). The solutions, along with CO2, are injected into the medium using a Surfactant Alternating Gas (SAG) scheme. Data is collected in the form of segmented high-resolution images of the medium during and after the injection process. Foam stability is evaluated based on changes in foam texture over time and bubble-size populations. The potential for carbon storage is evaluated based on residual fraction of trapped gas in the pore structure. Optimal surfactant formulation and concentration are identified for achieving a stable CO2 foam, a higher CO2residual saturation in the pore space for the lowest total cost.

Lingfu Liu

and 2 more

The efficient development of shale gas reservoirs requires an accurate understanding of methane gas transport in the matrix whose pore size is mainly in the nanoscale range. As a result, continuum-based approaches may be inadequate in simulating flow in such systems. Molecular dynamics (MD) simulations are capable of capturing the relevant microscale physics with high fidelity, albeit at a substantial computational cost. This high expense restricts MD simulations to rather small systems and computational domains, which may not be representative of complex hierarchical nature of shale reservoirs. To bridge this gap, we use a particle-based approach, the lattice Boltzmann method (LBM), as a suitable means to capture the physics of transport at microscale and simulate large complex domains. In this work, the multiple-relaxation-time (MRT)-LBM is used to study methane transport in nano-size pores. The adsorption effect and non-ideal gas behavior are incorporated using the pseudopotential model and appropriate force terms. The optimal values of the LB free parameters are determined for a nano-slit pore using reference velocity and density profiles from MD simulations. A preconditioning scheme is proposed to improve the stability of LBM in the presence of force terms. In this scheme, steady-state profiles obtained in the absence of regularization are used as the initial condition for simulation runs that include the regularization step. The results show how roughness adversely affects gas-transport in nanopores. The stability of the proposed framework makes it a potential approach for studying methane transport in more complex nano-porous media and translating transport behavior across scales.

Yuhang Wang

and 3 more

Fluid mixing in permeable media is essential in many practical applications. The mixing process is a consequence of velocity fluctuations owing to geological heterogeneities and mobility contrast of fluids. Heterogeneities in natural rocks are often spatially correlated, and their properties, such as permeability, may be described using fractal distributions. This work models the fractal characteristics of such permeability fields in which the covariance function is expressed as a power-law function. A generalized scaling relation is derived relating various fractal permeability fields using the magnitude of their fluctuations. This relation reveals the self-similar behavior of two-phase flow in such permeable media. To that end, a recently developed, high-resolution numerical simulator is employed to validate the analytically derived scaling relations. Two flow problems are considered in which flow is governed by 1) a linear, and 2) a nonlinear transport equation. Due to the probabilistic representation of the fractal permeability fields, a sensitivity study is conducted for each flow scenario to determine the number of realizations required for statistical convergence. Scaling analysis is performed using ensemble averages of simulated saturation profiles and their mixing lengths. Results support the validity of the developed scaling relation across the range of investigated flow conditions at intermediate times. The dynamics of linear flow in the asymptotic regime is affected by the correlation structure of heterogeneity. In nonlinear flow, scaling behavior appears to be dominated by the degree of nonlinearity.