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Dive into the research topics where Satish Karra is active.

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Featured researches published by Satish Karra.


Computers & Geosciences | 2015

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

Jeffrey D. Hyman; Satish Karra; Nataliia Makedonska; Carl W. Gable; Scott L. Painter; Hari S. Viswanathan

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.


Computational Geosciences | 2015

Particle tracking approach for transport in three-dimensional discrete fracture networks

Nataliia Makedonska; Scott L. Painter; Quan M. Bui; Carl W. Gable; Satish Karra

The discrete fracture network (DFN) model is a method to mimic discrete pathways for fluid flow through a fractured low-permeable rock mass, and may be combined with particle tracking simulations to address solute transport. However, experience has shown that it is challenging to obtain accurate transport results in three-dimensional DFNs because of the high computational burden and difficulty in constructing a high-quality unstructured computational mesh on simulated fractures. We present a new particle tracking capability, which is adapted to control volume (Voronoi polygons) flow solutions on unstructured grids (Delaunay triangulations) on three-dimensional DFNs. The locally mass-conserving finite-volume approach eliminates mass balance-related problems during particle tracking. The scalar fluxes calculated for each control volume face by the flow solver are used to reconstruct a Darcy velocity at each control volume centroid. The groundwater velocities can then be continuously interpolated to any point in the domain of interest. The control volumes at fracture intersections are split into four pieces, and the velocity is reconstructed independently on each piece, which results in multiple groundwater velocities at the intersection, one for each fracture on each side of the intersection line. This technique enables detailed particle transport representation through a complex DFN structure. Verified for small DFNs, the new simulation capability enables numerical experiments on advective transport in large DFNs to be performed. We demonstrate this particle transport approach on a DFN model using parameters similar to those of crystalline rock at a proposed geologic repository for spent nuclear fuel in Forsmark, Sweden.


Water Resources Research | 2015

Effect of advective flow in fractures and matrix diffusion on natural gas production

Satish Karra; Nataliia Makedonska; Hari S. Viswanathan; Scott L. Painter; Jeffrey D. Hyman

Although hydraulic fracturing has been used for natural gas production for the past couple of decades, there are significant uncertainties about the underlying mechanisms behind the production curves that are seen in the field. A discrete fracture network based reservoir-scale work flow is used to identify the relative effect of flow of gas in fractures and matrix diffusion on the production curve. With realistic three dimensional representations of fracture network geometry and aperture variability, simulated production decline curves qualitatively resemble observed production decline curves. The high initial peak of the production curve is controlled by advective fracture flow of free gas within the network and is sensitive to the fracture aperture variability. Matrix diffusion does not significantly affect the production decline curve in the first few years, but contributes to production after approximately 10 years. These results suggest that the initial flushing of gas-filled background fractures combined with highly heterogeneous flow paths to the production well are sufficient to explain observed initial production decline. Lastly, these results also suggest that matrix diffusion may support reduced production over longer time frames.


Water Resources Research | 2015

Influence of injection mode on transport properties in kilometer-scale three-dimensional discrete fracture networks

Jeffrey D. Hyman; Scott L. Painter; Hari S. Viswanathan; Nataliia Makedonska; Satish Karra

We investigate how the choice of injection mode impacts transport properties in kilometer-scale three-dimensional discrete fracture networks (DFN). The choice of injection mode, resident or flux-weighted, is designed to mimic different physical phenomena. It has been hypothesized that solute plumes injected under resident conditions evolve to behave similarly to solutes injected under flux-weighted conditions. Previously, computational limitations have prohibited the large scale simulations required to investigate this hypothesis. We investigate this hypothesis by using a high performance DFN suite, dfnWorks, to simulate flow in kilometer-scale three-dimensional DFNs based on fractured granite at the Forsmark site in Sweden, and adopt a Lagrangian approach to simulate transport therein. Results show that after traveling through a pre-equilibrium region both injection methods exhibit linear scaling of the first moment of travel time and power law scaling of the breakthrough curve with similar exponents, slightly larger than two. The physical mechanisms behind this evolution appear to be the combination of in-network channeling of mass into larger fractures, which offer reduced resistance to flow, and in-fracture channeling, which results from the topology of the DFN. This article is protected by copyright. All rights reserved.


Philosophical Transactions of the Royal Society A | 2016

Understanding hydraulic fracturing: a multi-scale problem

Jeffrey D. Hyman; Joaquín Jiménez-Martínez; Hari S. Viswanathan; James William Carey; Mark L. Porter; Esteban Rougier; Satish Karra; Qinjun Kang; Luke P. Frash; Li Chen; Zhou Lei; D. O’Malley; Nataliia Makedonska

Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nanometres to kilometres. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical and experimental efforts/methods. At the field scale, we use discrete fracture network modelling to simulate production of a hydraulically fractured well from a fracture network that is based on the site characterization of a shale gas reservoir. At the core scale, we use triaxial fracture experiments and a finite-discrete element model to study dynamic fracture/crack propagation in low permeability shale. We use lattice Boltzmann pore-scale simulations and microfluidic experiments in both synthetic and shale rock micromodels to study pore-scale flow and transport phenomena, including multi-phase flow and fluids mixing. A mechanistic description and integration of these multiple scales is required for accurate predictions of production and the eventual optimization of hydrocarbon extraction from unconventional reservoirs. Finally, we discuss the potential of CO2 as an alternative working fluid, both in fracturing and re-stimulating activities, beyond its environmental advantages. This article is part of the themed issue ‘Energy and the subsurface’.


Ground Water | 2016

Where Does Water Go During Hydraulic Fracturing

Daniel O'Malley; Satish Karra; Robert P. Currier; Nataliia Makedonska; Jeffrey D. Hyman; Hari S. Viswanathan

During hydraulic fracturing millions of gallons of water are typically injected at high pressure into deep shale formations. This water can be housed in fractures, within the shale matrix, and can potentially migrate beyond the shale formation via fractures and/or faults raising environmental concerns. We describe a generic framework for producing estimates of the volume available in fractures and undamaged shale matrix where water injected into a representative shale site could reside during hydraulic fracturing, and apply it to a representative site that incorporates available field data. The amount of water that can be stored in the fractures is estimated by calculating the volume of all the fractures associated with a discrete fracture network (DFN) based on real data and using probability theory to estimate the volume of smaller fractures that are below the lower cutoff for the fracture radius in the DFN. The amount of water stored in the matrix is estimated utilizing two distinct methods-one using a two-phase model at the pore-scale and the other using a single-phase model at the continuum scale. Based on these calculations, it appears that most of the water resides in the matrix with a lesser amount in the fractures.


Water Resources Research | 2016

Fracture size and transmissivity correlations: Implications for transport simulations in sparse three‐dimensional discrete fracture networks following a truncated power law distribution of fracture size

Jeffrey D. Hyman; Garrett Aldrich; Hari S. Viswanathan; Nataliia Makedonska; Satish Karra

We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fractures size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics. This article is protected by copyright. All rights reserved.


Water Resources Research | 2016

Push-pull tracer tests: Their information content and use for characterizing non-Fickian, mobile-immobile behavior: INFORMATION CONTENT OF PUSH-PULL TESTS

Scott K. Hansen; Brian Berkowitz; Velimir V. Vesselinov; Daniel O'Malley; Satish Karra

Path reversibility and radial symmetry are often assumed in push-pull tracer test analysis. In reality, heterogeneous flow fields mean that both assumptions are idealizations. To understand their impact, we perform a parametric study which quantifies the scattering effects of ambient flow, local-scale dispersion and velocity field heterogeneity on push-pull breakthrough curves and compares them to the effects of mobile-immobile mass transfer (MIMT) processes including sorption and diffusion into secondary porosity. We identify specific circumstances in which MIMT overwhelmingly determines the breakthrough curve, which may then be considered uninformative about drift and local-scale dispersion. Assuming path reversibility, we develop a continuous time random walk-based interpretation framework which is flow-field agnostic and well suited to quantifying MIMT. Adopting this perspective, we show that the radial flow assumption is often harmless: to the extent that solute paths are reversible, the breakthrough curve is uninformative about velocity field heterogeneity. Our interpretation method determines a mapping function (i.e. subordinator) from travel time in the absence of MIMT to travel time in its presence. A mathematical theory allowing this function to be directly “plugged into” an existing Laplace-domain transport model to incorporate MIMT is presented and demonstrated. Algorithms implementing the calibration are presented and applied to interpretation of data from a push-pull test performed in a heterogeneous environment. A successful four-parameter fit is obtained, of comparable fidelity to one obtained using a million-node 3D numerical model. Finally, we demonstrate analytically and numerically how push-pull tests quantifying MIMT are sensitive to remobilization, but not immobilization, kinetics. This article is protected by copyright. All rights reserved.


IEEE Transactions on Visualization and Computer Graphics | 2017

Analysis and Visualization of Discrete Fracture Networks Using a Flow Topology Graph

Garrett Aldrich; Jeffrey D. Hyman; Satish Karra; Carl W. Gable; Nataliia Makedonska; Hari S. Viswanathan; Jonathan Woodring; Bernd Hamann

We present an analysis and visualization prototype using the concept of a flow topology graph (FTG) for characterization of flow in constrained networks, with a focus on discrete fracture networks (DFN), developed collaboratively by geoscientists and visualization scientists. Our method allows users to understand and evaluate flow and transport in DFN simulations by computing statistical distributions, segment paths of interest, and cluster particles based on their paths. The new approach enables domain scientists to evaluate the accuracy of the simulations, visualize features of interest, and compare multiple realizations over a specific domain of interest. Geoscientists can simulate complex transport phenomena modeling large sites for networks consisting of several thousand fractures without compromising the geometry of the network. However, few tools exist for performing higher-level analysis and visualization of simulated DFN data. The prototype system we present addresses this need. We demonstrate its effectiveness for increasingly complex examples of DFNs, covering two distinct use cases – hydrocarbon extraction from unconventional resources and transport of dissolved contaminant from a spent nuclear fuel repository.


Transport in Porous Media | 2013

A Model for Tracking Fronts of Stress-Induced Permeability Enhancement

Kayla C. Lewis; Satish Karra; Sharad Kelkar

Using an analogy to the classical Stefan problem, we construct evolution equations for the fluid pore pressure on both sides of a propagating stress-induced damage front. Closed form expressions are derived for the position of the damage front as a function of time for the cases of thermally-induced damage as well as damage induced by over-pressure. We derive expressions for the flow rate during constant pressure fluid injection from the surface corresponding to a spherically shaped subsurface damage front. Finally, our model results suggest an interpretation of field data obtained during constant pressure fluid injection over the course of 16 days at an injection site near Desert Peak, NV.

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Hari S. Viswanathan

Los Alamos National Laboratory

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Jeffrey D. Hyman

Los Alamos National Laboratory

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Nataliia Makedonska

Los Alamos National Laboratory

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Gowri Srinivasan

Los Alamos National Laboratory

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Scott L. Painter

Oak Ridge National Laboratory

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Esteban Rougier

Los Alamos National Laboratory

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Maruti Kumar Mudunuru

Los Alamos National Laboratory

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Carl W. Gable

Los Alamos National Laboratory

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Velimir V. Vesselinov

Los Alamos National Laboratory

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