Hari S. Viswanathan

Nanoscale simulation of shale transport properties using the lattice Boltzmann method: permeability and diffusivity

Porous structures of shales are reconstructed using the markov chain monte carlo (MCMC) method based on scanning electron microscopy (SEM) images of shale samples from Sichuan Basin, China. Characterization analysis of the reconstructed shales is performed, including porosity, pore size distribution, specific surface area and pore connectivity. The lattice Boltzmann method (LBM) is adopted to simulate fluid flow and Knudsen diffusion within the reconstructed shales. Simulation results reveal that the tortuosity of the shales is much higher than that commonly employed in the Bruggeman equation, and such high tortuosity leads to extremely low intrinsic permeability. Correction of the intrinsic permeability is performed based on the dusty gas model (DGM) by considering the contribution of Knudsen diffusion to the total flow flux, resulting in apparent permeability. The correction factor over a range of Knudsen number and pressure is estimated and compared with empirical correlations in the literature. For the wide pressure range investigated, the correction factor is always greater than 1, indicating Knudsen diffusion always plays a role on shale gas transport mechanisms in the reconstructed shales. Specifically, we found that most of the values of correction factor fall in the slip and transition regime, with no Darcy flow regime observed.

Greening Coal: Breakthroughs and Challenges in Carbon Capture and Storage

Like it or not, coal is here to stay, for the next few decades at least. Continued use of coal in this age of growing greenhouse gas controls will require removing carbon dioxide from the coal waste stream. We already remove toxicants such as sulfur dioxide and mercury, and the removal of CO₂ is the next step in reducing the environmental impacts of using coal as an energy source (i.e., greening coal). This paper outlines some of the complexities encountered in capturing CO₂ from coal, transporting it large distances through pipelines, and storing it safely underground.

A reactive transport model of neptunium migration from the potential repository at Yucca Mountain

Abstract Characterization and performance assessment studies for the potential high-level nuclear waste repository at Yucca Mountain have identified 2 3 7 Np as a radionuclide of concern for the proposed repository. To predict the migration of neptunium after a repository breach, an understanding of the relevant hydrologic and geochemical processes is required. The hydrologic flow in the unsaturated zone at Yucca Mountain is dependent on the infiltration rate, the stratigraphy of the vadose zone, and the heat generated by the decaying radioactive waste. The geochemical processes that strongly affect 2 3 7 Np migration include: solubility-limited release of 2 3 7 Np from the near-field environment, aqueous speciation of neptunium into non-sorbing carbonate/hydroxy complexes and the sorbing NpO 2 + cation, sorption of neptunium onto the zeolitic tuffs via an ion exchange mechanism, and radioactive decay. The finite element heat and mass transfer (FEHM) code was used to investigate the coupled effects of chemical interactions and heat on neptunium transport from the potential repository to the water table. The selective coupling method is introduced to solve these reactive transport problems. The simulations indicate that in the absence of irreversible changes in the hydrologic and transport properties, the heat pulse does not significantly affect the migration of neptunium, as the time scale of heat pulse propagation is shorter than the time scales associated with neptunium release and migration. Water chemistry, particularly pH, calcium, and sodium concentration significantly affect the retardation of neptunium by the zeolitic rocks between the repository and the water table.

CO2 Accounting and Risk Analysis for CO2 Sequestration at Enhanced Oil Recovery Sites.

Using CO2 in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce sequestration costs in the absence of emissions policies that include incentives for carbon capture and storage. This study develops a multiscale statistical framework to perform CO2 accounting and risk analysis in an EOR environment at the Farnsworth Unit (FWU), Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil/gas-water flow and transport in the Morrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2/water injection/production rates, cumulative net CO2 storage, cumulative oil/gas productions, and CO2 breakthrough time. The median and confidence intervals are estimated for quantifying uncertainty ranges of the risk metrics. A response-surface-based economic model has been derived to calculate the CO2-EOR profitability for the FWU site with a current oil price, which suggests that approximately 31% of the 1000 realizations can be profitable. If government carbon-tax credits are available, or the oil price goes up or CO2 capture and operating expenses reduce, more realizations would be profitable. The results from this study provide valuable insights for understanding CO2 storage potential and the corresponding environmental and economic risks of commercial-scale CO2-sequestration in depleted reservoirs.

dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

Abstract dfn W orks is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using dfn G en , which combines fram (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the L a G ri T meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in dfn F low , which utilizes the massively parallel subsurface flow and reactive transport finite volume code pflotran . A Lagrangian approach to simulating transport through the DFN is adopted within dfn T rans to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

The cross-scale science of CO2 capture and storage: from pore scale to regional scale

We describe state-of-the-art science and technology related to modeling of CO2 capture and storage (CCS) at four different process scales: pore, reservoir, site, and region scale. We present novel research at each scale to demonstrate why each scale is important for a comprehensive understanding of CCS. Further, we illustrate research linking adjacent process scales, such that critical information is passed from one process scale to the next adjacent scale. We demonstrate this cross-scale approach using real world CO2 capture and storage data, including a scenario managing CO2 emissions from a large U.S. electric utility. At the pore scale, we present a new method for incorporating pore-scale surface tension effects into a relative permeability model of CO2-brine multiphase flow at the reservoir scale. We benchmark a reduced complexity model for site-scale analysis against a rigorous physics-based reservoir simulator, and include new system level considerations including local site-scale pipeline routing analysis (i.e., reservoir to site scale). We also include costs associated with brine production and treatment at the site scale, a significant issue often overlooked in CCS studies. All models that comprise our total system include parameter uncertainty which leads to results that have ranges of probability. Results suggest that research at one scale is able to inform models at adjacent process scales, and that these scale connections can inform policy makers and utility managers of overall system behavior including the impacts of uncertainty.

Probabilistic evaluation of shallow groundwater resources at a hypothetical carbon sequestration site

Carbon sequestration in geologic reservoirs is an important approach for mitigating greenhouse gases emissions to the atmosphere. This study first develops an integrated Monte Carlo method for simulating CO2 and brine leakage from carbon sequestration and subsequent geochemical interactions in shallow aquifers. Then, we estimate probability distributions of five risk proxies related to the likelihood and volume of changes in pH, total dissolved solids, and trace concentrations of lead, arsenic, and cadmium for two possible consequence thresholds. The results indicate that shallow groundwater resources may degrade locally around leakage points by reduced pH and increased total dissolved solids (TDS). The volumes of pH and TDS plumes are most sensitive to aquifer porosity, permeability, and CO2 and brine leakage rates. The estimated plume size of pH change is the largest, while that of cadmium is the smallest among the risk proxies. Plume volume distributions of arsenic and lead are similar to those of TDS. The scientific results from this study provide substantial insight for understanding risks of deep fluids leaking into shallow aquifers, determining the area of review, and designing monitoring networks at carbon sequestration sites.

Efficient numerical techniques for modeling multicomponent ground-water transport based upon simultaneous solution of strongly coupled subsets of chemical components

An iterative solution technique for reactive transport problems is developed, which we call the selective coupling method, that represents a versatile alternative to traditional uncoupled iterative techniques and the fully coupled global implicit method. The chemical formulation studied allows a combination of equilibrium and kinetic reactions, and therefore is a more versatile model formulation than a purely equilibrium-based system. However, this is a very challenging system for obtaining an efficient numerical solution. Techniques that sequentially compute the concentrations of aqueous components possibly ignore important derivatives in the Jacobian matrix of the full system of equations. The selective coupling method developed here allows only the strongly coupled components to be solved together, and the transport iteration consists of solving groups of components simultaneously. We also develop a method denoted as coupled normalization to reduce the computational work and memory requirements for particular types of reactive transport problems. These approaches can result in computational savings relative to the global implicit method by achieving a similar iteration count while reducing the cpu time per iteration. More importantly, the memory requirements of the selective coupling technique are controlled by the maximum number of coupled components, rather than by the total number of components. For complex aqueous chemical systems and grids with a large number of nodes, memory efficiency is the characteristic that makes the selective coupling method particularly attractive relative to the global implicit method. A series of example cases illustrate the efficiency of the new approach. These test problems are also used to address the implementation issues surrounding the most efficient strategy for coupling the aqueous components when carrying out the chemical transport iteration. In-depth knowledge of the behavior of the chemical system is required to select an appropriate solution strategy.

Hydraulic fracturing fluid migration in the subsurface: A review and expanded modeling results

Understanding the transport of hydraulic fracturing (HF) fluid that is injected into the deep subsurface for shale gas extraction is important to ensure that shallow drinking water aquifers are not contaminated. Topographically driven flow, overpressured shale reservoirs, permeable pathways such as faults or leaky wellbores, the increased formation pressure due to HF fluid injection, and the density contrast of the HF fluid to the surrounding brine can encourage upward HF fluid migration. In contrast, the very low shale permeability and capillary imbibition of water into partially saturated shale may sequester much of the HF fluid, and well production will remove HF fluid from the subsurface. We review the literature on important aspects of HF fluid migration. Single-phase flow and transport simulations are performed to quantify how much HF fluid is removed via the wellbore with flowback and produced water, how much reaches overlying aquifers, and how much is permanently sequestered by capillary imbibition, which is treated as a sink term based on a semianalytical, one-dimensional solution for two-phase flow. These simulations include all of the important aspects of HF fluid migration identified in the literature review and are performed in five stages to faithfully represent the typical operation of a hydraulically fractured well. No fracturing fluid reaches the aquifer without a permeable pathway. In the presence of a permeable pathway, 10 times more fracturing fluid reaches the aquifer if well production and capillary imbibition are not included in the model.

Generalized lattice Boltzmann model for flow through tight porous media with Klinkenberg's effect.

Gas slippage occurs when the mean free path of the gas molecules is in the order of the characteristic pore size of a porous medium. This phenomenon leads to Klinkenbergs effect where the measured permeability of a gas (apparent permeability) is higher than that of the liquid (intrinsic permeability). A generalized lattice Boltzmann model is proposed for flow through porous media that includes Klinkenbergs effect, which is based on the model of Guo et al. [Phys. Rev. E 65, 046308 (2002)]. The second-order Beskok and Karniadakis-Civans correlation [A. Beskok and G. Karniadakis, Microscale Thermophys. Eng. 3, 43 (1999) and F. Civan, Transp. Porous Med. 82, 375 (2010)] is adopted to calculate the apparent permeability based on intrinsic permeability and the Knudsen number. Fluid flow between two parallel plates filled with porous media is simulated to validate the model. Simulations performed in a heterogeneous porous medium with components of different porosity and permeability indicate that Klinkenbergs effect plays a significant role on fluid flow in low-permeability porous media, and it is more pronounced as the Knudsen number increases. Fluid flow in a shale matrix with and without fractures is also studied, and it is found that the fractures greatly enhance the fluid flow and Klinkenbergs effect leads to higher global permeability of the shale matrix.