West Virginia University will implement procedures for a fractal analysis of fractures in reservoirs. This procedure will be applied to fracture networks in outcrops and to fractures intersecting horizontal boreholes. The parameters resulting from this analysis will be used to generate synthetic fracture networks with the same fractal characteristics as the real networks. Recovery from naturally fractured, tight-gas reservoirs is controlled by the fracture network. Reliable characterization of the actual fracture network in the reservoir is severely limited. The location and orientation of fractures intersecting the borehole can be determined, but the length of these fractures cannot be unambiguously determined. Because of the lack of detailed information about the actual fracture network, modeling methods must represent the porosity and permeability associated with the fracture network, as accurately as possible with very little a priori information. In the sections following, the authors will (1) present fractal analysis of the MWX site, using the box-counting procedure; (2) review evidence testing the fractal nature of fracture distributions and discuss the advantages of using the fractal analysis over a stochastic analysis; and (3) present an efficient algorithm for producing a self-similar fracture networks which mimic the real MWX outcrop fracture network.

Recovery from naturally fractured, tight-gas reservoirs is controlled by the fracture network. Reliable characterization of the actual fracture network in the reservoir is severely limited. The location and orientation of fractures intersecting the borehole can be determined, but the length of these fractures cannot be unambiguously determined. Fracture networks can be determined for outcrops, but there is little reason to believe that the network in the reservoir should be identical because of the differences in stresses and history. Because of the lack of detailed information about the actual fracture network, modeling methods must represent the porosity and permeability associated with the fracture network, as accurately as possible with very little apriori information. Three rather different types of approaches have been used: (1) dual porosity simulations; (2) 'stochastic' modeling of fracture networks, and (3) fractal modeling of fracture networks. Stochastic models which assume a variety of probability distributions of fracture characteristics have been used with some success in modeling fracture networks. The advantage of these stochastic models over the dual porosity simulations is that real fracture heterogeneities are included in the modeling process. In the sections provided in this paper the authors will present fractal analysis of the MWX site, using the box-counting procedure; (2) review evidence testing the fractal nature of fracture distributions and discuss the advantages of using their fractal analysis over a stochastic analysis; (3) present an efficient algorithm for producing a self-similar fracture networks which mimic the real MWX outcrop fracture network.

This book presents and describes an innovative method to simulate the growth of natural fractural networks in different geological environments, based on their geological history and fundamental geomechanical principles. The book develops techniques to simulate the growth and interaction of large populations of layer-bound fracture directly, based on linear elastic fracture mechanics and subcritical propagation theory. It demonstrates how to use these techniques to model the nucleation, propagation and interaction of layer-bound fractures in different orientations around large scale geological structures, based on the geological history of the structures. It also explains how to use these techniques to build more accurate discrete fracture network (DFN) models at a reasonable computational cost. These models can explain many of the properties of natural fracture networks observed in outcrops, using actual outcrop examples. Finally, the book demonstrates how it can be incorporated into flow modelling workflows using subsurface examples from the hydrocarbon and geothermal industries. Modelling the Evolution of Natural Fracture Networks will be of interest to anyone curious about understanding and predicting the evolution of complex natural fracture networks across large geological structures. It will be helpful to those modelling fluid flow through fractures, or the geomechanical impact of fracture networks, in the hydrocarbon, geothermal, CO2 sequestration, groundwater and engineering industries.

This important resource explores recent theoretical advances and modelling on fluids transport in fractal porous systems and presents a systematic understanding of the characterization of complex microstructure and transport mechanism in fractal porous media. Modelling of Flow and Transport in Fractal Porous Media shows how fractal theory and technology, combined with other modern experiments and numerical simulation methods, will assist researchers and practitioners in modelling of transport properties of fractal porous media, such as fluid flow, heat and mass transfer, mechanical characteristics, and electrical conductivity. - Presents the main methods and technologies for transport characterization of fractal porous media, including soils, reservoirs and artificial materials - Provides the most recent theoretical advances in modelling of fractal porous media, including gas and vapor transport in fibrous materials, nonlinear seepage flow in hydrocarbon reservoirs, mass transfer of porous nanofibers, and fractal mechanics of unsaturated soils - Includes multidisciplinary examples of applications of fractal theory to aid researchers and practitioners in characterizing various porous media structures

Present models for the representation of naturally fractured systems rely on the double-porosity Warren-Root model or on random arrays of fractures. However, field observation in outcrops has demonstrated the existence of multiple length scales in many naturally fractured media. The existing models fail to capture this important fractal property. In this paper, we use concepts from the theory of fragmentation and from fractal geometry for the numerical construction of networks of fractures that have fractal characteristics. The method is based mainly on the work of Barnsley (1) and allows for great flexibility in the development of patterns. Numerical techniques are developed for the simulation of unsteady single phase flow in such networks. It is found that the pressure transient response of finite fractals behaves according to the analytical predictions of Chang and Yortsos (6), provided that there exists a power law in the mass-radius relationship around the test well location. Otherwise, the finite size effects become significant and interfere severely with the identification of the underlying fractal structure. 21 refs., 13 figs.

In the Earth Sciences, the concept of fractals and scale invariance is well-recognized in many natural objects. However, the use of fractals for spatial and temporal analyses of natural hazards has been less used (and accepted) in the Earth Sciences. This book brings together twelve contributions that emphasize the role of fractal analyses in natural hazard research, including landslides, wildfires, floods, catastrophic rock fractures and earthquakes. A wide variety of spatial and temporal fractal-related approaches and techniques are applied to 'natural' data, experimental data, and computer simulations. These approaches include probabilistic hazard analysis, cellular-automata models, spatial analyses, temporal variability, prediction, and self-organizing behaviour. The main aims of this volume are to present current research on fractal analyses as applied to natural hazards, and to stimulate the curiosity of advanced Earth Science students and researchers in the use of fractals analyses for the better understanding of natural hazards.

Recent advances in fracture network characterization have identified high degrees of heterogeneity and permeability anisotropy in conventional reservoirs and complex fracture network generation after well stimulation in unconventional reservoirs. Traditional methods to model such complex systems may not capture the key role of fracture network geometry, spatial distribution, and connectivity on well performance. Because of the ubiquitous presence of natural fractures in conventional and unconventional reservoirs, it is key to provide efficient tools to model them accurately. We extend the application of the embedded discrete fracture model (EDFM) to study the influence of natural fractures represented by discrete fracture network (DFN) models on well performance. Current state-of-the-art modeling technologies have been able to describe natural fracture systems as a whole, without providing flexibility to extract, vary, and group fracture network properties. Our developed implementations analyze fracture network topology and provide advanced mechanisms to model and understand fracture network properties. The first application features a numerical model in combination with EDFM to study water intrusion in a naturally fractured carbonate reservoir. We developed a workflow that overcomes conventional methods limitations by modeling the fracture network as a graph. This representation allowed to identify the shortest paths that connect the nearby water zone with the well perforations, providing the mechanisms to obtain a satisfactory history match of the reservoir. Additionally, we modeled a critically-stressed carbonate field by modeling faults interactions with natural fractures. Our workflow allowed to discretize the hydraulic backbone of the field and assess its influence on the entire field gas production. Our next application applies a connectivity analysis using an efficient and robust collision detection algorithm capable of identifying groups of connected or isolated natural fractures in an unconventional reservoir. This study uses numerical models in combination with EDFM to analyze the effect of fracture network connectivity on well production using fractal DFN models. We concluded that fracture network connectivity plays a key role on the behavior of fractured reservoirs with negligible effect of non-connected fractures. Finally, we performed assisted history matching (AHM) using fractal methods to characterize in a probabilistic manner the reservoir properties and to offer key insights regarding spatial distribution, number, and geometry of both hydraulic and natural fractures in unconventional reservoirs. In this work, we provided computational tools that constitute the foundations to conduct advanced modeling using DFN models in conjunction with EDFM in several reservoir engineering areas such as well-interference, water intrusion, water breakthrough, enhanced oil recovery (EOR) efficiency characterization, and fracture network connectivity assessments. The benefits of our work extend to conventional, unconventional, and geothermal reservoirs

Fractals have changed the way we understand and study nature. This change has been brought about mainly by the work of B. B. Mandelbrot and his book The Fractal Geometry of Nature. Now here is a book that collects articles treating fractals in the earth sciences. The themes chosen span, as is appropriate for a discourse on fractals, many orders of magnitude; including earthquakes, ocean floor topography, fractures, faults, mineral crystallinity, gold and silver deposition. There are also chapters on dynamical processes that are fractal, such as rivers, earthquakes, and a paper on self-organized criticality. Many of the chapters discuss how to estimate fractal dimensions, Hurst exponents, and other scaling exponents. This book, in a way, represents a snapshot of a field in which fractals has brought inspiration and a fresh look at familiar subjects. New ideas and attempts to quantify the world we see around us are found throughout. Many of these ideas will grow and inspire further work, others will be superseded by new observations and insights, most probably with future contributions by the authors of these chapters.

This book provides theoretical concepts and applications of fractals and multifractals to a broad range of audiences from various scientific communities, such as petroleum, chemical, civil and environmental engineering, atmospheric research, and hydrology. In the first chapter, we introduce fractals and multifractals from physics and math viewpoints. We then discuss theory and practical applications in detail. In what follows, in chapter 2, fragmentation process is modeled using fractals. Fragmentation is the breaking of aggregates into smaller pieces or fragments, a typical phenomenon in nature. In chapter 3, the advantages and disadvantages of two- and three-phase fractal models are discussed in detail. These two kinds of approach have been widely applied in the literature to model different characteristics of natural phenomena. In chapter 4, two- and three-phase fractal techniques are used to develop capillary pressure curve models, which characterize pore-size distribution of porous media. Percolation theory provides a theoretical framework to model flow and transport in disordered networks and systems. Therefore, following chapter 4, in chapter 5 the fractal basis of percolation theory and its applications in surface and subsurface hydrology are discussed. In chapter 6, fracture networks are shown to be modeled using fractal approaches. Chapter 7 provides different applications of fractals and multifractals to petrophysics and relevant area in petroleum engineering. In chapter 8, we introduce the practical advantages of fractals and multifractals in geostatistics at large scales, which have broad applications in stochastic hydrology and hydrogeology. Multifractals have been also widely applied to model atmospheric characteristics, such as precipitation, temperature, and cloud shape. In chapter 9, these kinds of properties are addressed using multifractals. At watershed scales, river networks have been shown to follow fractal behavior. Therefore, the applications of fractals are addressed in chapter 10. Time series analysis has been under investigations for several decades in physics, hydrology, atmospheric research, civil engineering, and water resources. In chapter 11, we therefore, provide fractal, multifractal, multifractal detrended fluctuation analyses, which can be used to study temporal characterization of a phenomenon, such as flow discharge at a specific location of a river. Chapter 12 addresses signals and again time series using a novel fractal Fourier analysis. In chapter 13, we discuss constructal theory, which has a perspective opposite to fractal theories, and is based on optimizationof diffusive exchange. In the case of river drainages, for example, the constructal approach begins at the divide and generates headwater streams first, rather than starting from the fundamental drainage pattern.