Fracture Network Parameters Research Articles

Effect of proppant injection condition on fracture network structure and conductivity

AbstractThe hydraulic fracturing of shale reservoirs is an important topic, and adjusting the fracturing process can enhance fracturing efficiency. To analyze the effect of injection conditions on the fracture network structure and conductivity, numerical simulations and theoretical calculations are carried out based on the construction data, and the variation patterns of the fracture network parameters are determined. During the theory study, a fracture network conductivity model was obtained by combining the fracture network expansion model and the fracture diversion model. Then a numerical model was set up according to the analysis results of monitoring data. The numerical simulation results showed the fracture network structure and proppant distribution under different conditions. Throughout the simulation process, the structural parameters and conductivity of the fracture network can be determined by controlling the injection amount and adjusting the injection method, speed, and sand ratio. Results indicated that the proppant pulse frequency during the injection process was a major factor affecting the structure and conductivity of the fracture network. At the same time, a comparison of the distribution structure of the proppant revealed that although the intermittent injection of the proppant improved the flow channel, the efficiency of fracture utilization can still be improved.

A Practical probabilistic history matching framework for characterizing fracture network parameters of shale gas reservoirs

Simulating fluid flow in complex fracture systems encountered in subsurface systems, such as those encountered in tight or shale gas reservoirs, presents considerable challenges. Sophisticated numerical techniques and characterization approaches are required to integrate static and dynamic data from multiple sources to account for the intricate interplay between fractures and the surrounding rock matrix. A novel workflow using an indicator-based probability perturbation method (PPM) is applied to characterize uncertain discrete fracture network parameters. The posterior probability distributions of primary and secondary fracture transmissivity, aperture, length, height, and intensity of the secondary fracture are estimated according to the production (flow) histories. A case study based on the Horn River shale gas reservoir is presented. A pilot point scheme is formulated to update the distributions of P32L. The forward modelling entails upscaling each fracture model into a dual-porosity dual-permeability model and performing multiphase flow simulation. This approach produces an ensemble of history-matched discrete fracture and upscaled models by incorporating static and dynamic data. The results demonstrate the utility of the developed method for estimating secondary fracture parameters, which are not inferrable from other static information alone. The inference of both primary and secondary fractures offers a more comprehensive characterization of the fracture networks in tight or shale gas reservoirs. Integrating a pilot point parameterization technique and a sequential simulation approach into the PPM framework presents significant novelties in contributing to a comprehensive and effective method of simulating fluid flow in complex fracture systems, addressing the challenges associated with non-linear relationships between fracture model parameters and the corresponding flow response.

Model and Analysis of Pump-Stopping Pressure Drop with Consideration of Hydraulic Fracture Network in Tight Oil Reservoirs

The existing pump-stopping pressure drop models for the hydraulic fracturing operation of tight oil reservoirs only consider the main hydraulic fracture and the single-phase flow of fracturing fluid. In this paper, a new pump-stopping pressure drop model for fracturing operation based on coupling calculation of the secondary fracture and oil-water two-phase flow is proposed. The physical model includes the horizontal wellbore, the fracture network and the tight oil reservoir. Through the numerical simulation and calculation, the wellbore afterflow performance, the crossflow performance between the main hydraulic fracture and the secondary fracture, the fracturing fluid leakoff and the oil-water replacement after termination of pumping are obtained. The pressure drop characteristic curve is drawn out by the bottom-hole flow pressure calculated through the numerical simulation, and a series of analyses are carried out on the calculated pressure drop curve, which is helpful to diagnose the -oil-water two-phase flow state and the fracture closure performance under the control of the fracture network after hydraulic fracturing pumping. Finally, taking a multi-stage fractured horizontal well in a tight oil reservoir in the Junggar basin, China as an example, the pump-stopping pressure drop data of each stage after hydraulic fracturing are analyzed. Through the history fitting of the pressure drop characteristic curve, the key parameters such as fracture network parameters, which include the half-length of main hydraulic fracture, the conductivity of main hydraulic fracture and the density of secondary fracture, the fracture closure pressure are obtained by inversion, thus, the hydraulic fracturing effect of fractured horizontal well in tight oil reservoirs is further quantified.

A Semi-Analytical Model for Production Prediction of Deep CBM Wells Considering Gas-Water Two-Phase Flow

The productivity prediction of deep coalbed methane (CBM) wells is significantly influenced by gas-water two-phase flow characteristics and seepage parameters of the fracture network. While numerical simulations offer a comprehensive approach, analytical models are favored for their faster and broader applicability. However, conventional analytical models often oversimplify the complex problem of two-phase seepage equations, leading to substantial errors in dynamic analysis outcomes. Addressing this shortcoming, we establish a gas-water two-phase productivity prediction model for deep CBM reservoirs. This model takes into account the two-phase flow characteristics within the reservoir and fracture network, as well as the stress sensitivity of the reservoir and fractures. Additionally, a modified trilinear flow model characterizes the fractured modification body. By integrating the flowing material balance equation with the Newton Iteration method, we gradually update the seepage model’s nonlinear parameters using the average formation pressure. We also linearize the gas-water two-phase model through successive iterations to derive a semi-analytical solution. The accuracy of the model was verified through comparison with commercial numerical simulation software results and field application. The model also enabled us to scrutinize the influence of reservoir and fracture network parameters on productivity. Our research findings suggest that the semi-analytical solution approach can efficiently address the nonlinear seepage problem of gas-water two-phase flow, enabling quick and accurate prediction of deep CBM well productivity. Moreover, appropriate fracture network parameters are paramount for enhancing the productivity of deep CBM wells. Lastly, during the development of deep CBM reservoirs, it is crucial to control the production pressure difference appropriately to minimize the stress sensitivity impact on production capacity.

Novel calculation method to predict gas–water two-phase production for the fractured tight-gas horizontal well

The prediction of production capacity in tight gas wells is greatly influenced by the characteristics of gas–water two-phase flow and the fracture network permeability parameters. However, traditional analytical models simplify the nonlinear problems of two-phase flow equations to a large extent, resulting in significant errors in dynamic analysis results. To address this issue, this study considers the characteristics of gas–water two-phase flow in the reservoir and fracture network, utilizes a trilinear flow model to characterize the effects of hydraulic fracturing, and takes into account the stress sensitivity of the reservoir and fractures. A predictive model for gas–water two-phase production in tight fractured horizontal wells is established. By combining the mass balance equation with the Newton–Raphson iteration method, the nonlinear parameters of the flow model are updated step by step using the average reservoir pressure. The accuracy of the model is validated through comparisons with results from commercial numerical simulation software and field case applications. The research results demonstrate that the established semi-analytical solution method efficiently handles the nonlinear two-phase flow problems, allowing for the rapid and accurate prediction of production capacity in tight gas wells. Water production significantly affects gas well productivity, and appropriate fracture network parameters are crucial for improving gas well productivity. The findings of this work could provide more clear understanding of the gas production performance from the fractured tight-gas horizontal well.

A Volume Fracturing Percolation Model for Tight Reservoir Vertical Wells

Based on the non-linear seepage characteristics of tight reservoirs and the reconstruction mode of vertical wells with actual volume fracturing, a seven-area percolation model for volume fracturing vertical wells in tight reservoirs is established. Laplace transform and Pedrosa transform are applied to obtain analytical solutions of bottom hole pressure and vertical well production under a constant production regime. After verifying the correctness of the model, the influence of the fracture network parameters on the pressure and production is studied. The research results indicate that as the permeability modulus increases, the production of volume fracturing vertical wells decreases. The penetration ratio of the main crack and the half-length of the main crack have a small impact on production, while the diversion capacity of the main crack has a significant impact on the initial production, but it is ultimately limited by the effective volume of the transformation. Under constant pressure conditions, the greater the width and permeability of the ESRV region, the higher the vertical well production rate is. The smaller the aspect ratio of the ESRV region, the higher the mid-term yield and the faster the yield decrease. The research results show guiding significance for the design of vertical well volume fracturing in tight reservoirs.

A novel high-dimension shale gas reservoir hydraulic fracture network parameters optimization framework

Optimization design of hydraulic fracture network parameters significantly reduces the high investment risk in the production of shale gas. This is also a numerical simulation-based optimization problem. Surrogate-assisted optimization method which adopts a simple-yet-accurate approximate model to facilitate the optimization workflow is one of the most promising methods to lessen the computational burden. However, due to multi-stage fracturing and “well factory” production model, the dimension of variables in hydraulic fracture network parameters optimization increases sharply, and a significant number of data are required to ensure the performance of the surrogate model. To address this problem, a novel surrogate-assisted multi-objective optimization method using the tri-training strategy and variable-length non-dominated sorting genetic algorithm-II (VL-NSGA-II) is proposed for high-dimension hydraulic fracture network parameters optimization in shale gas reservoir. The proposed method is called HDWHF. In this HDWHF method, the tri-training strategy is adopted to infill solutions with the highest-confidence fitness as new samples to retrain the surrogate model during each iteration while VL-NSGA-II is adopted as the optimizer. This strategy enables the increase of samples without numerical simulation runs, which realizes a decrease of the numerical simulation runs and enhance the performance of the surrogate model. The superior performance of the HDWHF against conventional surrogate-assisted methods is verified using three high-dimension examples with various numbers of wells and fracture types. This proposed HDWHF workflow provides an intelligent means for efficient optimization and decision-making of high-dimension hydraulic fracture network parameters in shale gas reservoirs.

A deep-learning based model for fracture network characterization constrained by induced micro-seismicity and tracer test data in enhanced geothermal system

Fracture network developed in hot dry rock (HDR) primarily controls the flow and heat transport in enhanced geothermal system (EGS). Characterization of fracture network in deep geothermal reservoir is among the most challenging tasks. An interpretation framework for explicit delineating complex fracture network is proposed based on induced micro-seismic events, hydraulic stimulation and tracer test data, which are often available in EGS sites. It is processed by (1) the spatial distribution of fracture intensity, size and hydraulic aperture constrained by the hydraulic diffusivity derived from the spatio-temporal distribution of micro-seismic events, (2) numerical models and long short-term memory (LSTM) neural network models for the hydraulic stimulation and tracer test, and (3) parameter inversion model based on the multi-objective Harris hawks optimization (MOHHO) algorithm searching for optimal fracture network parameters minimizing the deviations between model predictions and field observations. This method has been applied to the Habanero EGS site, Australia. The prediction accuracy of the injection wellhead pressure and produced tracer concentration of the inversed micro-seismicity mapping DFN model is improved by 61.16% and 67.35%, respectively, compared with the stochastic DFN model. These results emphasize the importance to integrate induced micro-seismicity monitoring data for the characterization of hydraulically stimulated fracture network.

Enumerating hydraulically active fractures using multiple, high-resolution datasets to inform plume transport in a sandstone aquifer

It is widely known that flow in fractured sedimentary rock is dominated by the interconnected fractures in the rock mass, but it is difficult to determine which fractures observed in boreholes are active, meaning they transmit water under natural gradient conditions A methodology is presented that uses optical televiewer (OTV) and continuous core logs synergistically with FLUTe™ Transmissivity (T) profiling, straddle packer testing, rock core permeability testing, active line source temperature logs, and rock core VOC concentration profiles to determine the number and position of active fractures in a 196-meter borehole in sandstone. The application of this methodology indicates that 40% of the identified fractures are active in this borehole with a frequency of 0.61 active fractures per meter, which compares well with the number of fractures identified with the straddle packer Rec method used in the largest transmissive zones, while the low transmissivity zones tested are consistent with laboratory-measured rock matrix hydraulic conductivity. High-resolution, hydraulically based methods provide the necessary evidence to improve estimates of active fractures that control solute transport. This paper demonstrates how multiple, spatially resolved data sets can be used synergistically to inform fracture network parameters thereby constraining hydraulic aperture and surface area calculations that control flow and diffusion, with the aim of improving the estimation of plume migration rates and mass discharge to receptors in fractured sedimentary rocks.

Artificial neural network prediction models for Montney shale gas production profile based on reservoir and fracture network parameters

The prediction of shale gas production is necessary to evaluate the project's economical feasibility. Some studies suggested prediction models for predicting shale gas production. However, the model-based planar fracture assumption may not apply to a naturally fractured shale gas reservoir which induces a complex fracture network. This paper proposes three ANN architectures for predicting the peak production and Arps's hyperbolic decline parameters (Di and b) of a shale gas well in the Montney formation with an existing natural fracture system. A production profile can be reconstructed using the Arps' hyperbolic decline model and the predicted parameters. The ANN architectures were developed based on 370 simulation data of the reservoir, hydraulic fracture design parameters, and the fracture network properties, including fracture spacing and fracture conductivity, which remarkably affect shale gas production. The testing results, using another set of 92 simulation data, confirmed the high correlation between the input and objective functions with R2 > 0.86. Moreover, good agreement was observed between the measured and predicted cumulative gas production at one-, five-, ten-, fifteen-, and twenty-years of production with R2 > 0.94, and percentage errors were lower than 15.6%. This suggests that the shale gas production can be predicted efficiently and reliably using the Arps' hyperbolic model and the predicted parameters. The estimated production profiles can be used to continuously update the field development plans and calculate the project's NPV. Furthermore, the proposed method is applicable for predicting the production of newly produced reservoirs with limited production history.

A pressure drop model of post-fracturing shut-in considering the effect of fracturing-fluid imbibition and oil replacement

Since the production regime of shut-in after fracturing is generally adopted for wells in shale oil reservoir, a shut-in pressure drop model coupling wellbore-fracture network-reservoir oil-water two-phase flow has been proposed. The model takes into account the effects of wellbore afterflow, fracture network channeling, and matrix imbibition and oil exchange after stop of pumping. The simulated log-log curve of pressure-drop derivative by the model presents W-shape, reflecting the oil-water displacement law between wellbore, fracture network and matrix, and is divided into eight main control flow stages according to the soaking time. In the initial stage of pressure drop, the afterflow dominates; in the early stage, the pressure drop is controlled by the cross-flow and leakoff of the fracture system, and the fractures close gradually; in the middle stage of pressure drop, matrix imbibition and oil exchange take dominance, and the fracturing fluid loss basically balances with oil replaced from matrix; the late stage of pressure drop is the reservoir boundary control stage, and the leakoff rate of fracturing-fluid and oil exchange rate decrease synchronously till zero. Finally, the fracture network parameters such as half-length of main fracture, main fracture conductivity and secondary fracture density were inversed by fitting the pressure drop data of five wells in Jimsar shale oil reservoir, and the water imbibition volume of matrix and the oil replacement volume in fracture were calculated by this model. The study results provide a theoretical basis for comprehensively evaluating the fracturing effect of shale oil horizontal wells and understanding the oil-water exchange law of shale reservoir after fracturing.

A New Approach for Automatic Optimization of Complex Fracture Network in Shale Reservoirs

AbstractShale gas reservoirs have gradually become the main source for oil and gas production. The automatic optimization technology of complex fracture network in fractured horizontal wells is the key technology to realize the efficient development of shale gas reservoirs. In this paper, based on the flow model of shale gas reservoirs, the porosity/permeability of the matrix system and natural fracture system is characterized. The fracture network morphology is finely characterized by the fracture network expansion calculation method, and the flow model was proposed and solved. On this basis, the influence of matrix permeability, matrix porosity, fracture permeability, fracture porosity, and fracture length on the production of shale gas reservoirs is studied. The optimal design of fracture length and fracture location was carried, and the automatic optimization method of complex fracture network parameters based on simultaneous perturbation stochastic approximation (SPSA) was proposed. The method was applied in a shale gas reservoir, and the results showed that the proposed automatic optimization method of the complex fracture network in shale gas reservoirs can automatically optimize the parameters such as fracture location and fracture length and obtain the optimal fracture network distribution matching with geological conditions.

The Investigation of Fracture Networks on Heat Extraction Performance for an Enhanced Geothermal System

Hydraulic fracturing is usually employed to create a complex fracture network to enhance heat extraction in the development of an enhanced geothermal system. The heat extraction depends on the heat conduction from the rock matrix to the flowing fractures and the heat convection through a complex fracture network. Therefore, the geometries of the fracture network have important influences on the thermal breakthrough. In this paper, a hydro-thermal coupling mathematical model considering a complex fracture network is established. The embedded discrete fracture model is adopted to explicitly model the individual fracture on the mass flow and heat transfer. The model is validated by analytical solutions. Fracture network parameters are changed systematically to investigate the effects of fracture network distribution including regular and complex shape on the thermal production performance. The results show that the increase of producing pressure differential, fracture number, and conductivity will cause an early thermal breakthrough. The strong variation in fracture conductivity, as well as spacing and orientation, will cause thermal flow channeling and decrease the efficiency of heat extraction. A modified connectivity field is proposed to characterize the spatial variation of fracture network connectivity, which can be used to infer the thermal flow path.

The effect of natural fractures on CO2storage performance and oil recovery from CO2and WAG injection in an Appalachian basin reservoir

AbstractNatural fractures affect both the oil recovery from the enhanced oil recovery (EOR) process and the associated CO2storage during and after EOR. The main objective of this study is to evaluate two performance parameters: (1) oil recovery during CO2and water alternating gas (WAG) injection, and (2) CO2storage, during and after EOR, in a fractured oil reservoir of the Appalachian basin. While previous studies have shown the potential of CO2‐EOR to enhance oil recovery in the Appalachian basin, this work investigates WAG performance in comparison to continuous CO2‐EOR. A compositional numerical modeling approach was used to quantify the incremental oil recovery stemming from incorporating natural fractures. History matching of primary production and CO2huff‐and‐puff pilot test for a well producing from a depleted oil field in Ohio was used to assign the fracture network parameters in the dual continuum model. The scenarios modeled include continuous CO2and WAG injection under two injection pore volumes. Each scenario is followed by a CO2storage phase. These simulations help evaluate the performance of different scenarios in terms of oil recovery and CO2storage. Simulation results show how oil recovery and CO2storage vary significantly as a function of operational parameters. The results also show the amount of CO2stored during WAG injection is significantly lower than that stored during the storage phase at the end of oil recovery. In addition, the operational parameters during WAG affect the amount of CO2stored at the end of following storage phase. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

Fracture Characterization Using Flowback Water Transients from Hydraulically Fractured Shale Gas Wells.

Fracture characterization is necessary to evaluate fracturing operations and forecast well performance. However, it is challenging to quantitatively characterize the complex fracture network in shale gas reservoirs because of the unknown density and reactivation of natural fractures. The flowback water transients can provide useful information about the complexity of the fracture network after the fracturing operations. In this paper, a mathematical model for modeling fracturing fluid flowback of hydraulically fractured shale gas wells is established. This proposed model characterizes the flow of water and gas in a hydraulic fracture-induced natural fracture–shale matrix system. Hydraulic, capillary, and osmotic convections; gas adsorption; and natural fracture closure are considered in this model. Flowback simulation of a hydraulically fractured shale gas well is conducted using the developed numerical simulator, and the water/gas transients between hydraulic fractures, natural fractures, and matrix are obtained. Finally, two field cases from the Longmaxi Formation, Southern Sichuan Basin, China, are used for comparison of the flowback data with the model results. The good match of the two water transients provides a group of fracture network parameters, that is, the effective length and conductivity of main hydraulic fractures and the density of induced natural fractures. The proposed model for describing the flowback process and its meaningful relationship with the fracture–network complexity provides an alternative approach for post-stimulation evaluation.

Coupling image analysis and thermo-mechanical simulation results to produce a model of the fracture network in a nuclear glass canister

Understanding nuclear glass alteration in a fracture network of a block of nuclear glass is critical in predicting the release of the radionuclides in the subsurface and is relevant for the security of nuclear waste disposal. Here, we present an image processing-based fracture network characterization workflow that enables us to characterize a glass block fracture network, establish a link between a physical parameter representing an internal state of glass structural relaxation and an internal structure of the block fracture network, and generate multiple realizations of equivalent fracture networks by considering the variability of the fracture network parameters such as fracture distribution and apertures. The proposed workflow includes the following stages: (i) fracture network extraction, (ii) measurement of apertures of all distinct ramifications of the fracture network, (iii) image segmentation, (iv) anisotropy characterization, (v) passage to segment representation with the intention of modeling block equivalent fracture networks by using an algorithm of mesh growth, (vi) geostatistical modeling of average apertures and variables responsible for fracture spatial distribution, and (vii) simulation of equiprobable realizations of fracture network equivalent tessellations. Given this processing, the workflow is able to provide data for further steps including upscaling of diffusivity and permeability, and it facilitates reactive transport modeling at the glass block scale. As an illustrative example, we apply the proposed sequence of actions to a two-dimensional (2D) high-resolution image of two blocks of nuclear glass. This application brings into service both hard data obtained by direct measurement of the fracture network and soft physics-based explanatory data and considers the variability in the fracture network. The results show that implementation of the devised procedure presents an opportunity for better understanding of the impact of fracturing on aqueous alteration of glass.

Transient flow analysis in flowback period for shale reservoirs with complex fracture networks

Model developments for transient analysis of fractured horizontal wells have gained tremendous attention in shale reservoirs, especially, during the flowback period. However, the existing models so far have rarely considered two-phase flow and complex fracture networks. To improve this situation, in this work, we present a comprehensively semianalytical two-phase flow model. Two fluids simultaneously flow in the matrix and fracture networks. By iteratively correcting the relative permeability to the phases, we incorporate the two-phase flow into fracture model. Complex fracture networks with arbitrary geometries are described and the fluid flow interplays at fracture intersections are eliminated by mass balance equation. The model solution is obtained by using Laplace transform inversion, and it is verified by performing a case study with numerical simulators. Our results show that there exist two distinct flow regimes: fluid feed and pseudo-boundary dominated flow (PBDF), which is generated by the permeability contrast between fracture networks and matrix. We also investigate the impacts of some key reservoir and fracture properties on the characteristics of the two-phase productivity index. Results indicate that the two-phase productivity index increases with an increase in initial water saturation. Furthermore, it is found that during the PBDF, different fracture-network parameters have various constant productivity indexes, providing an efficient tool to characterize the fracture networks. Based on that, we apply the model to estimate the fracture networks of a well in CJ formation from China with flowback data and micro seismic data, which provides an efficient technique to estimate the fracture parameters during the flowback period.

An analysis of stochastic discrete fracture networks on shale gas recovery

Complex fracture networks are created by hydraulic fracturing in shale gas reservoirs. The well performance is largely affected by the geometrical properties of fracture networks. It is difficult to estimate well performance because a large number of parameters are used for characterization of a fracture network. In this study, only two parameters are screened to estimate the shale gas recovery by the method of design of experiments. Synthetic fracture networks are generated based on the stochastic theory to represent the secondary fractures in the hydraulic fracture network. Two numerical experiments are designed to correlate the fracture network properties to gas recovery estimated by a commercial software. Various fracture network parameters derived from the analyses of fracture intersection, fractal and percolation are screened to correlate the gas recovery. In terms of the internal structure of a fracture network, a dimensionless parameter called the effective fracture density is proposed to estimate shale gas recovery. It is a combination of the number of fractures, fracture length and orientation. In terms of the boundary of a fracture network, the shale gas recovery is determined by the number of intersection points between the primary fractures and secondary fractures (NIPS). The shale gas recovery predicted by the two parameters (the NIPS and the dimensionless fracture density) is accurate compared with that calculated by the commercial software, which provides us a practical method to estimate the gas recovery by eliminating the number of parameters used for fracture network properties.

An exploration of pressure dynamics using differential equations defined on a fractal geometry

Pressure tests have been used to understand the behavior of naturally fractured reservoirs (NFRs) by establishing parameters such as permeability, connectivity of fractures, system compressibility, fracture network parameters, and others associated with the physical properties of the reservoir. The complex fracture network of a NFR produces anomalous fluid flow, which is shown by the pressure behavior at the well. A plausible model to explain this behavior is to assume that it arises from a fractal fracture system. However, to estimate the parameters that define this fractal fracture system, fluid flow models based on the modification of Darcy’s law are used. On the other hand, in this work, a fractal structure with known fractal dimension: Sierpinski gasket (SG) is proposed. The objective of this work is to solve numerically the diffusion equation on SG, and establish a comparison with flow models used in the oil industry to investigate the fractality assumption. This study is focused on the qualitative behavior of the solution of the diffusion equation defined on a SG supported by the Kigami’s theory of differential equations on fractals.

Connectivity, permeability, and channeling in randomly distributed and kinematically defined discrete fracture network models

AbstractA major use of DFN models for industrial applications is to evaluate permeability and flow structure in hardrock aquifers from geological observations of fracture networks. The relationship between the statistical fracture density distributions and permeability has been extensively studied, but there has been little interest in the spatial structure of DFN models, which is generally assumed to be spatially random (i.e., Poisson). In this paper, we compare the predictions of Poisson DFNs to new DFN models where fractures result from a growth process defined by simplified kinematic rules for nucleation, growth, and fracture arrest. This so‐called “kinematic fracture model” is characterized by a large proportion of T intersections, and a smaller number of intersections per fracture. Several kinematic models were tested and compared with Poisson DFN models with the same density, length, and orientation distributions. Connectivity, permeability, and flow distribution were calculated for 3‐D networks with a self‐similar power law fracture length distribution. For the same statistical properties in orientation and density, the permeability is systematically and significantly smaller by a factor of 1.5–10 for kinematic than for Poisson models. In both cases, the permeability is well described by a linear relationship with the areal density , but the threshold of kinematic models is 50% larger than of Poisson models. Flow channeling is also enhanced in kinematic DFN models. This analysis demonstrates the importance of choosing an appropriate DFN organization for predicting flow properties from fracture network parameters.