Search

Motivated by a triaxial coreflood experiment with a sample of Utica shale where an abrupt jump in permeability was observed, possibly due to the creation of a percolating fracture network through the sample, we perform numerical simulations based on the experiment to characterize how the effective permeability of otherwise low-permeability porous media depends on fracture formation, connectivity, and the contrast between the fracture and matrix permeabilities. While a change in effective permeability due to fracture formation is expected, the dependence of its magnitude upon the contrast between the matrix permeability and fracture permeability and the fracture network structure is poorly characterized. We use two different high-fidelity fracture network models to characterize how effective permeability changes as percolation occurs. The first is a dynamic two-dimensional fracture propagation model designed to mimic the laboratory settings of the experiment. The second is a static three-dimensional discrete fracture network (DFN) model, whose fracture and network statistics are based on the fractured sample of Utica shale. Once the network connects the inflow and outflow boundaries, the effective permeability increases non-linearly with network density. In most networks considered, a jump in the effective permeability was observed when the embedded fracture network percolated. We characterize how the magnitude of the jump, should it occur, depends on the contrast between the fracture and matrix permeabilities. For small contrasts between the matrix and fracture permeabilities the change is insignificant. However, for larger contrasts, there is a substantial jump whose magnitude depends non-linearly on the difference between matrix and fracture permeabilities. A power-law relationship between the size of the jump and the difference between the matrix and fracture permeabilities is observed. The presented results underscore the importance of fracture network topology on the upscaled properties of the porous medium in which it is embedded. [ABSTRACT FROM AUTHOR]

We present the preliminary results of a numerical model of fluid flow in a fault zone, based on field data acquired at the Majella Mountain, (Italy). The fault damage zone is described as a discretely fractured medium, and the fault core as a porous medium. Our model utilizes dfnWorks, a parallelized computational suite, developed at Los Alamos National Laboratory to model the damage zone and characterizes its hydraulic parameters. We present results from the field investigations and the basic computational workflow, along with preliminary results of fluid flow simulations at the scale of the fault. [ABSTRACT FROM AUTHOR]

The apertures of natural fractures in fractured rock are highly heterogeneous. However, in-fracture aperture variability is often neglected in flow and transport modeling and individual fractures are assumed to have uniform aperture distribution. The relative importance of in-fracture variability in flow and transport modeling within kilometer-scale field–scale fracture networks has been under a matter of debate for a long time because the flow in each single fracture is controlled not only by in-fracture variability but also by boundary conditions. Computational limitations have previously prohibited researchers from investigating the relative importance of in-fracture variability in flow and transport modeling within large-scale fracture networks. We address this question by incorporating internal heterogeneity of individual fractures into flow simulations within kilometer scale three-dimensional fracture networks, where fracture intensity, P 32 (ratio between total fracture area and domain volume) is between 0.027 and 0.031 [1/m]. A recently developed discrete fracture network (DFN) simulation capability, dfnWorks , is used to generate DFNs that include in-fracture aperture variability represented by a stationary log-normal stochastic field with various correlation lengths and variances. The Lagrangian transport parameters, non-reacting travel time and cumulative retention, are calculated along particles streamlines. It is observed that due to local flow channeling early particle travel times are more sensitive to in-fracture variability than the tails of travel time distributions, where no significant effect of the in-fracture transmissivity variations and spatial correlation length is observed. [ABSTRACT FROM AUTHOR]

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 CO 2 sequestration are also included. [ABSTRACT FROM AUTHOR]

Abstract: There are few peer-reviewed or major published studies that estimate the total amount of food loss in developed countries and even fewer attempt to estimate the monetary value. We compiled estimates of the amount and value of food loss for more than 200 individual foods in the United States using the US Department of Agriculture’s Economic Research Service’s Loss-Adjusted Food Availability data and then aggregated these values to estimate the total value of food loss and the value by food group. The results indicate that in 2008, the estimated total value of food loss at the retail and consumer levels in the United States as purchased at retail prices was $165.6billion. The top three food groups in terms of the value of food loss at these levels are: meat, poultry, and fish (41%); vegetables (17%); and dairy products (14%). Looking more closely at the estimates for the consumer level, this level of loss translates into almost 124kg (273lb) of food lost from human consumption, per capita, in 2008 at an estimated retail price of $390/capita/year. Food loss represents a significant share of household food expenditures: our estimates suggest that the annual value of food loss is almost 10% of the average amount spent on food per consumer in 2008 and over 1% of the average disposable income. This consumer level loss translates into over .3kg (0.7lb) of food per capita per day valued at $1.07/day. Our estimates of the total value of food loss in the United States and loss estimates by food group are useful in that they can generate awareness of the issue among the food industry members, governments, and consumers. Potential large-scale approaches and economic incentives to mitigate food loss in developed countries are also discussed. [Copyright &y& Elsevier]

Objective: To estimate the costs of satisfying MyPyramid fruit and vegetable guidelines, with a focus on whether low-income households can bear these costs. Design: Descriptive analysis of the 2008 National Consumer Panel with information on the food purchases of 64,440 households across the contiguous United States was used to analyze the cost of fruits and vegetables. Costs per MyPyramid cup-equivalents were calculated by accounting for cooking yields and the portion of a food item's retail weight that is inedible. Variables Measured: Costs per cup-equivalent for less expensive fruits and vegetables by MyPyramid subgroup including whole and cut fruit, fruit juice, dark green vegetables, orange vegetables, starchy vegetables, other vegetables, and legumes. Results: In 2008, a variety of fruits and vegetables was available for an average cost of SO.40 to SO.50 per cup-equivalent. MyPyramid fruit and vegetable recommendations could be satisfied at this cost level. Conclusions and Implications: Low-income Americans facing national average food prices can satisfy MyPyramid fruit and vegetable guidelines with a budget equal to the Thrifty Food Plan allocation to fruits and vegetables. However, many low-income households spend too much money on food that is low in fruit and vegetable content. Some money should be reallocated to fruits and vegetables. [ABSTRACT FROM AUTHOR]

• Combined effects of flow variability and retention due to matrix-diffusion. • We perform a set of three-dimensional discrete fracture network simulations. • We develop an upscaled continuous time random walk (CTRW) approach. • Advective transport uses an Ornstein-Uhlenbeck model for the particle velocities. • Fracture-matrix coupling is represented using a compound Poisson process. We investigate the combined effects of network scale flow variability and retention due to matrix-diffusion on the scaling behavior of transport through fractured media. Two of the principal mechanisms controlling the transport of solutes through fractured low-permeability media are broad distributions of flow velocities and retention times in the solid matrix. We study the relative impact of these two processes under different initial conditions using a set of three-dimensional discrete fracture network simulations. We use these simulations to develop and calibrate an upscaled continuous time random walk (CTRW) approach for advective transport based on an Ornstein-Uhlenbeck model for the particle velocities that accounts for the fracture-matrix coupling using a compound Poisson process. This CTRW model can be conditioned on the initial solute distribution and allows to observe late-time scaling behavior at distances beyond what is feasible to observe using high-fidelity direct numerical simulations. We determine that the initial distribution of particles leads to marked differences in the persistent long-term scale behavior in the solute travel time distributions, even those undergoing retention due to matrix diffusion through implementation and analysis of the model. [ABSTRACT FROM AUTHOR]

Shale gas and hydraulic refracturing has revolutionized the US energy sector in terms of prices, consumption, and CO 2 emissions. However, key questions remain including environmental concerns and extraction efficiencies that are leveling off. For the first time, we identify key discoveries, lessons learned, and recommendations from this shale gas revolution through extensive data mining and analysis of 23 years of production from 20,000 wells. Discoveries include identification of a learning-by-doing process where disruptive technology innovation led to a doubling in shale gas extraction, how refracturing with emerging technologies can transform existing wells, and how overall shale gas production is actually dominated by long-term tail production rather than the high-profile initial exponentially-declining production in the first 12 months. We hypothesize that tail production can be manipulated, through better fracturing techniques and alternative working fluids such as CO 2 , to increase shale gas recovery and minimize environmental impacts such as through carbon sequestration. [ABSTRACT FROM AUTHOR]

In this paper, we introduce pySimFrac , an open-source python library for generating 3-D synthetic fracture realizations, integrating with fluid simulators, and performing analysis. pySimFrac allows the user to specify one of three fracture generation techniques (Box, Gaussian, or Spectral) and perform statistical analysis including the autocorrelation, moments, and probability density functions of the fracture surfaces and aperture. This analysis and accessibility of a python library allows the user to create realistic fracture realizations and vary properties of interest. In addition, pySimFrac includes integration examples to two different pore-scale simulators and the discrete fracture network simulator, dfnWorks. The capabilities developed in this work provides opportunity for quick and smooth adoption and implementation by the wider scientific community for accurate characterization of fluid transport in geologic media. We present pySimFrac along with integration examples and discuss the ability to extend pySimFrac from a single complex fracture to complex fracture networks. • A python library to develop synthetic complex fractures. • Fractures can be passed to single- and multiphase simulations for analysis. • Examples of fracture generation and analysis is provided in Jupyter notebooks. • The code-base and user-documentation are made available on GitHub and dfnWorks websites, respectively. [ABSTRACT FROM AUTHOR]

• Novel fabrication methods are combined to make a core-scale micromodel for EOR. • Long micromodels capture core-scale physics such as the formation of oil banks. • Increasing viscosity of displacing phase in long micromodels increases the amount of oil recovered at breakthrough. Fluid injection experiments in rocks, commonly referred to as corefloods, are widely used to study and understand fluid flow in the subsurface. However, visual inspection of flow in cores requires computed tomography machines which may not be widely accessible. We introduce a novel micromodel that is as long as a typical core (40 cm), has adjustable pore structure, and includes 2.5D pore throats that can be used to conduct fluid displacements analogous to those in cores. Flow can be visualized inexpensively in the micromodel with an optical microscope. We performed standard coreflood tests in our micromodel including a tracer test and a steady state permeability test. We also conducted multiphase displacements by injecting aqueous solutions at varying glycerol concentrations to displace oil from the micromodel and observed the effect of the viscosity ratio on macro-scale recovery efficiency. When the injected aqueous solution was less viscous than the resident oil, it fingered through the oil. Fingering was not observed in the cases where the injected glycerol solution was more viscous than the oil. Moreover, as the viscosity of the injected glycerol solution increased, oil was recovered more rapidly. Additionally, we performed surfactant and glycerol floods in short (2.4 cm) and long (40 cm) micromodels that show long chips capture scale dependent physics, such as oil banking, that small chips do not capture. The novel micromodel shows promise as a screening tool for chemical EOR because it captures phase banks that are desirable in corefloods. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing of shale formations in the United States has led to a domestic energy boom. Currently, water is the only fracturing fluid regularly used in commercial shale oil and gas production. Industry and researchers are interested in non-aqueous working fluids due to their potential to increase production, reduce water requirements, and to minimize environmental impacts. Using a combination of new experimental and modeling data at multiple scales, we analyze the benefits and drawbacks of using CO 2 as a working fluid for shale gas production. We theorize and outline potential advantages of CO 2 including enhanced fracturing and fracture propagation, reduction of flow-blocking mechanisms, increased desorption of methane adsorbed in organic-rich parts of the shale, and a reduction or elimination of the deep re-injection of flow-back water that has been linked to induced seismicity and other environmental concerns. We also examine likely disadvantages including costs and safety issues associated with handling large volumes of supercritical CO 2 . The advantages could have a significant impact over time leading to substantially increased gas production. In addition, if CO 2 proves to be an effective fracturing fluid, then shale gas formations could become a major utilization option for carbon sequestration. [ABSTRACT FROM AUTHOR]

In this work, we compare hydrocarbon production curves obtained from a graph-based reduced-order model with the high-fidelity Discrete Fracture Network (DFN) predictions for a fracture network created using data from a real shale site. We observe that the bounds for the high fidelity DFN model lie within the bounds for the reduced order model, implying that the reduced-order model provides a conservative estimate. Moreover, we found that except for first-passage times and late arriving mass, the production curves from the reduced-order model predict transport accurately. However, it is to be noted that the results are inspite of trading a three-dimensional geometry for a reduced system in the form of a graph, one that is 500–1000 times faster in terms of computational efficiency (for this particular application). In addition, we also compare the production curves for large drawdown and small drawdown using our graph approach. The reduced-order model is successful in showing that the long term productivity is higher in case of small drawdown although the initial productivity is higher for large drawdown. Thus, this reduced-order model offers great potential in uncertainty quantification for production, as well as in providing operators with information to make real-time decisions for optimal production. • Flow and transport simulation on DFN mesh is replaced with flow and transport simulation on a graph representation of the DFN. • Graph theory provides a much faster and elegant way for model order reduction of DFNs. • Production curves for the reduced-order model match well with the high fidelity DFN model except early times and late times. [ABSTRACT FROM AUTHOR]

A quantitative assessment of how faults control the migration of geofluids is critical in many areas of geosciences. We integrated geological fieldwork, quantitative analysis of the fractures distribution and numerical modeling to build a geometrical representation of a fault zone and to characterize its hydraulic properties. Our target is a fault located in the Majella Mountain (Italy). We collected 21 scan lines across the fault profile in order to characterize its architecture. The numerical modeling of the fracture network of the damage zones and their hydraulic parameters was performed using both commercial (Move®) and open source software (dfnWorks and PFLOTRAN). Move® was used to build a representative model of the fault zone using fracture spacing as a proxy, and to model the hydraulic parameters of the different fault domains. dfnWorks and PFLOTRAN were employed to infer the hydraulic parameters of the damage zones of the fault and then upscale these properties to an equivalent continuum domain, suitable for fluid flow simulations through the whole fault zone. Our findings show how even in a relatively small area it is possible to describe changes in terms of hydraulic properties of a fault zone and to build models capable to represent these variations. • We integrate geological fieldwork, quantitative analysis of fractures and numerical modeling to infer the hydraulic properties of a fault zone. • Our results stress the value of detailed field investigations in the hydraulic characterization of fault zones. • The use of open source software like dfnWorks and PFLOTRAN allows for a wide control of the parameters used to build a numerical model of the fault. • The proposed workflow has potential applications in several fields, especially when is crucial to assess the impact of faults on fluid migration. [ABSTRACT FROM AUTHOR]