The effectiveness of hydraulic fracturing fluid injection is influenced by numerous factors, including pre-existing discontinuities such as Discrete Fracture Networks (DFNs). Among the geometric characteristics of DFNs, Fracture density is a critical factor. In deep reservoirs, which often consist of hot dry rock (HDR), thermal conduction through the rock and fluid, as well as advection and convective heat transfer within the fluid, can significantly impact fluid–rock interactions. This study examines the influence of DFN density on hydraulic Fracture (HF) propagation in HDR, with a particular focus on the thermo-hydro-mechanical (THM) behavior of HDR using the combined finite-Discrete element method (FDEM). Key controlling factors, such as flow rate, fluid kinematic viscosity, in-situ stress magnitude, pre-existing Fracture aperture, and working fluid temperature, are analyzed. The findings highlight the significant role of DFN density in determining the pattern and extent of HF propagation under varying conditions. Additionally, the interaction between the working fluid and DFNs is shown to vary considerably with changes in these controlling factors. However, the study reveals that variations in DFN density or the values of the controlling factors have minimal impact on the temperature field. This is attributed to the rapid heat exchange between the cold fluid and the HDR, which quickly raises the fluid temperature, resulting in negligible temperature variations.

Summary Simulating a rock Fracture distribution is an important issue, which is common in various fields of geosciences. This issue is of particular importance in determination of hydraulic conductivity of rock mass and forecasting the amount of water entering the underground spaces. Theoretical studies has been demonstrated that the result of three-dimensional (3D) modeling Discrete Fracture Network is closer to reality than other models. One of the limitations of the statistical methods for modeling Fracture Network is the lack of spatial behavior considerations of modeling Fracture Network parameters. In other words, based on Monte Carlo algorithm in statistical methods, generation of Fracture Network parameters are based on probability distribution functions, and are carried out randomly. In this study, a computational GFracIUT code is developed. In order to generate the 3D Discrete Fracture Network and considering geometrical parameters of the Fractures surveyed from the outcrops and boreholes, probability density functions are developed using geostatistical methods. In the mentioned code, initially the density of micro-Fractures are conjectured using sequential Gaussian simulation. Then, the locations of the centres of the micro-Fractures are determined by Poisson’ s process. When the center locations of the micro-Fractures are determined orientation components estimated using geostatistical approaches. The developed program is capable of modeling Fractures with various geometrical shapes according to operator’ s desired specifications. As examples in this regard, disc and quadrilateral shapes have been considered in this paper. In order to practically apply the program, an area in Gachsaran oil field has been considered as a case study. Introduction Fracture is one of the main characteristics of the rock mass. Fracture Network modeling by statistical method has some limitations. One of the limitations of the statistical methods for modeling Fracture Network is the lack of spatial behavior considerations of modeling Fracture Network parameters. Geostatistical methods can be employed to spatially characterize Fracture Network. Methodology and Approaches First, using the GFracIUT code, we obtain the Fracture density map by employing sequential Gaussian simulation method. Then, the location of the centre of each micro-Fracture by Poisson’ s process is determined using the software. Finally, the micro-Fractures orientation component is estimated by geostatistical methods. Results and Conclusions In this study, a computational GFracIUT code is developed. The GFracIUT code is composed of two steps: positioning the centers of Fractures using the Fractures density data by sequential Gaussian simulation, and assigning the directions (strikes and dips) of the Fractures. In order to practically apply the software, an area in Gachsaran oil field has been considered as a case study.

Fluid flow in a jointed rock mass with an impermeable matrix is often controlled by joint properties, including aperture, orientation, spacing, persistence, etc. On the other hand, since the rock mass is made of heterogeneous and anisotropic natural materials, the geometric properties of joints may possess dispersed values. One of the most powerful methods for simulation of the stochastic nature of joins geometric characteristics is three dimensional stochastic Discrete Fracture Network (DFN) modelling. The main goal of this research is development of a method and an instrument for hydraulic analyses of complicated DFN. For this purpose, DFN-FRAC3D program – which has been proposed for mechanical analyses – was developed to construct a hydraulic DFN. The joint aperture parameter was added to other geometric features of the model and to increase the accuracy, the correlation between the joint aperture and the length was considered. In addition, the program was developed for detecting the connected joint Networks. In the next step, the connected joint Networks were converted to equivalent pipe Networks. Finally to study the fluid flow within this Network, WaterGEMS, a Numerical software for flow modeling, was used that had the capability to make complex pipes and to receive other hydraulic information. In order to test the performance of the provided program, a 3D hydraulic model was presented for Fractured Networks of the rock mass in the Mazino region. It can be concluded that in the case of executing the Underground Coal Gasification panels in the Mazino coalmine of Central Iran, the resulting gases will not leak to the ground.

Accurate simulation of geometrical properties of Fractures is an important goal in rock engineering. One of the most capable methods for simulating the random nature of geometrical properties of Fractures is Discrete Fracture Network (DFN) random modelling, which presents the heterogeneous nature of Fractured rock mass with statistically defined geometrical properties. Up to now, all properties of Fractures such as location, shape, orientation, size (persistence), spacing, and opening of joints have been simulated and applied in 3D DFN modelling. In this research, a statistical solution based on Kernel’s non-parametric distribution is used for simulating roughness. Through this method, even those geometric properties of Fractures which do not have their own specific distribution functions can be simulated. After simulating the roughness value, the roughness geometry should also be simulated in a way that evokes the roughness value. Therefore, in order to simulate the surface of Fractures in this research, the DRS method is applied in 2D and then, developed into 3D. At the end, simulation of discontinuity’s roughness is added as a separate package to DFN-FRAC3D computer program. DFN-FRAC3D computer program, as one of the most capable tools in this field, is able to develop a 3D Fracture Network block model by using the surveyed data and then simulating geometrical properties of the Fracture; thus, by applying the results of this research in this compute software, all geometrical properties of Fractures can be simulated. Finally, in order to explain the results of this research, outcomes of DFN-FRAC3D computer program for both with and without applying the roughness property on DFN are compared.

Almost all of the proposed models of Discrete Fracture Networks (DFN) embedded within rock masses are discontinuities with zero tension strength. While, potential discontinuities and weak surfaces such as rock bridges, veinlet and schistose surfaces are candidate for breakage under stress and have also significant effect on rock mass strength. Simultaneously with geometrical parameters, this geomechanical heterogeneous nature of Fractures are crucial for understanding rock mass behavior and characteristics. This paper focuses on the probabilistic effect of potential discontinuities property on the rock mass strength using Potential Discrete Fracture Networks (PDFN)-bonded block models (BBM) framework. By means of this approach, potential Fractures such as weak surfaces such as rock bridges, veinlet and schistose surfaces (surfaces with tension and shear strength) are considered, which have significant effect on rock mass strength. Maximum obtained rock mass strength differences for 4 Fracture intensities: 1. 2, 3. 6, 6 and 8. 4 m-1 are 12. 9, 7. 4, 15. 1 and 10. 2 MPa respectively. Results indicates performance and importance of the proposed model for assessment of realistic rock mass strength.

Nowadays, modeling of rock masses is widely used in order to accurately determine the properties of the rock mass and improve its behavior. In most cases, the geometric components of the Fractures in the rock have a random nature. one of the most important methods to simulate the random nature of joints is the stochastic modeling of the Fracture Network of rock. The stochastic modeling of the Fracture Network makes the heterogeneous nature of rock mass with Discrete elements, with geometrical properties and features that are statistically defined. In this study, the samples taken from the Liroo dam foundation are surveyed and analyzed. Then using the EasyFit that is a statistical software, the known distribution functions were determined by the maximum fitting on the surveyed geometric components and then their moments were determined. On the other hand, using the written code with Mathematica software, 3D-DFN three dimensional Discrete Fracture Network method Fractures simulated. Finally, the geometric model validated based on the comparison of the statistics of the distribution functions obtained from the model output with statistics of input distribution. The results in most cases indicate compliance of more than 90%. Also, P10, P21 and P32 values of the two-dimensional sections in a same strike with reality and in three-dimensional model were determined and compared with real values. The values of P10 and P32 showed more than 90% compliance and the P21 component was more than 75% consistent with actual data.

The interpretation of the pressure data of naturally Fractured reservoirs (NFRs) has particular significance. The most famous theory for analyzing the pressure data of NFRs is the dual-porosity model presented by Warren and Root. Recent studies have shown that the dual-porosity model may not be appropriate for interpreting well test from all NFRs because this model has limits. In this study, the pressure transient response of naturally Fractured reservoirs was investigated by using numerical simulation without considering analytical and semi-analytical methods. To this end, a set of models including connected and disconnected Fracture Networks was simulated in the numerical simulator. The Warren and Root well-testing signature was observed in all simulations but it was highly evident for a well was located in the matrix and was negligible for a well that was intersected by Fractures. The results of the simulation for the well that was intersected by Fractures showed the bilinear flow regime with the slope of 1/4. The period of this flow regime increased in the unconnected Fracture Network and changed to the linear flow regime with a slope of 1/2 in two cases: firstly, by increasing Fracture permeability in the connected Fracture Network, secondly, in the small-unconnected Fractures. Moreover, the sensitivity analysis was performed on the well location in the connected Fracture Network. This research showed that by decreasing the distance between well and Fracture Network, the transition period becomes deeper and appears earlier.

Estimation of the in-situ block size is known as a key parameter in the characterization of the mechanical properties of rock masses. As the in-situ block size cannot be measured directly, several simplified methods have been developed, where the intrinsic variability of the geometrical features of discontinuities are commonly neglected. This work aims to estimate the in-situ block size distribution (IBSD) using the combined photogrammetry and Discrete Fracture Network (DFN) approaches. To this end, four blasting benches in the Golgohar iron mine No. 1, Sirjan, Iran, are considered as the case studies of this research work. The slope faces are surveyed using the photogrammetry method. Then 3D images are prepared from the generated digital terrain models, and the geometrical characteristics of discontinuities are surveyed. The measured geometrical parameters are statistically analysed, and the joint intensity, the statistical distribution of the orientation, and the Fracture trace length are determined. The DFN models are generated, and IBSD for each slope face is determined using the multi-dimensional spacing method. In order to evaluate the validity of the generated DFN models, the geological strength index (GSI) as well as the stereographic distribution of discontinuities in the DFN models are compared against the field measurements. A good agreement has been found between the results of the DFN models and the filed measurements. The results of this work show that the combined photogrammetry and DFN techniques provide a robust, safe, and time-efficient methodology for the estimation of IBSD.

Hydraulic fracturing is one of the conventional and common methods to stimulate oil and gas formations with low permeability. This method is widely used for creating artificial Fractures and stimulate fluid flow in oil and gas wells. In this paper, Fracture propagation process was simulated by using a Discrete Fracture Network (DFN) in UDEC software. Discrete Element Method (DEM) is a key for simulating hydraulic fracturing which is capable of performing a fully coupled hydromechanical analysis to model fluid flow through a Network of Fractures. In this regard, fictitious joints were used for modeling Fracture propagation in a medium with equal to intact rock properties. To achieve this goal, the mechanical and strength properties of discontinuities were considered equal to mechanical and strength properties of intact rock. Then, the role of rock mechanics parameters including elastic modulus, cohesion and friction angle were studied in the process of Fracture propagation. The results of numerical simulations showed that the extended Fracture length is increased by increasing the elastic modulus and decreasing the friction angle. Also, increasing in the cohesion does not have a significant effect on the extended Fracture length, but it reduces the hydraulic Fracture opening.

Optimizing reservoir performance in Fractured reservoirs relies heavily on understanding and harnessing Fracture connectivity at the reservoir scale. Voroni triangulation Discrete Fracture Network (DFN) models offer a unique depiction of Fractures and their connectivity compared to other methods. Petrophysical property modeling involves various algorithms, with DFN emerging as a novel mathematical approach. This study centers on a segment of Khangiran's hydrocarbon formations, analyzing reservoir porosity and permeability. Among the plethora of available methods, fractal geometry, particularly through the box counting method, proves apt for estimating these properties. By increasing the box size to explore point distribution in the background space, the method calculates fractal dimensions, aiding in porosity and permeability estimation. Applied in modeling, this technique presents a new ellipsoid-based prediction model, providing a comprehensive description of petrophysical properties in reservoir-prone areas. The results, aligned with geological features, mud loss data, and production outcomes, demonstrate remarkable compatibility with lower uncertainty, presenting a promising avenue for enhanced reservoir characterization and performance optimization. The three-dimensional block model estimations derived from the Integrated Discrete Fracture Network (DFN) algorithm with a fractal dimension of complex sequences distribution align with well test analysis and production data results. The iterative application and refinement of the DFN algorithm and fractal dimension modeling process hold potential for further enhancement across the Khangiran reservoir or other hydrocarbon fields. The findings indicate that well 11 is optimally configured and likely exhibits superior performance in terms of hydrocarbon production within the reservoir.