• Fadakar-A Y, 2018, “DFNE Practices with ADFNE”. Alghalandis Computing, Toronto, Ontario, Canada, pp61.
  • Fadakar-A Y, 2018, “Data Preprocessing”, Alghalandis Computing, Toronto, Canada, pp10.
  • Fadakar-A Y, 2018, “Data Processing And Visualization”, Alghalandis Computing, Toronto, Canada, pp15.
  • Fadakar-A Y, 2018, “Import And Export For Irazu”, Alghalandis Computing, Toronto, Canada, pp8.
  • Fadakar-A Y, 2018, “Merging Layers”, Alghalandis Computing, Toronto, Canada, pp12.
  • Fadakar-A Y, 2018, “Permeability Tensors”, Alghalandis Computing, Toronto, Canada, pp11.
  • Fadakar-A Y, 2018, “Plurigaussian Simulations”, Alghalandis Computing, Toronto, Canada, pp21.
  • Fadakar-A Y, 2018, “Simulation Of Layered Formation”, Alghalandis Computing, Toronto, Canada, pp12.
  • Fadakar-A Y, 2018, “Critically Stressed Fractures”, Alghalandis Computing, Toronto, Canada, pp3.
  • Fadakar-A Y, 2018, “DFN, Meshed”, Alghalandis Computing, Toronto, Canada, pp2.
  • Fadakar-A Y, 2018, “DFN, Termination 2D”, Alghalandis Computing, Toronto, Canada, pp2.
  • Fadakar-A Y, 2018, “Extract Information from Well Data”, Alghalandis Computing, Toronto, Canada, pp3.
  • Fadakar-A Y, 2018, “Import Well Data”, Alghalandis Computing, Toronto, Canada, pp3.
  • Fadakar-A Y, 2018, “Irazu Mesh Import & Export”, Alghalandis Computing, Toronto, Canada, pp6.
  • Fadakar-A Y, 2018, “Layered Shale | Limestone 2D”, Alghalandis Computing, Toronto, Canada, pp3.
  • Fadakar-A Y, 2018, “Layered Shale | Limestone 3D”, Alghalandis Computing, Toronto, Canada, pp4.
  • Fadakar-A Y, 2018, “Merge Layers By Thickness”, Alghalandis Computing, Toronto, Canada, pp5.
  • Fadakar-A Y, 2018, “Mohr Circle, Practices”, Alghalandis Computing, Toronto, Canada, pp6.
  • Fadakar-A Y, 2018, “PluriGaussian Simulation 2D”, Alghalandis Computing, Toronto, Canada, pp4.
  • Fadakar-A Y, 2018, “PluriGaussian Simulation 3D”, Alghalandis Computing, Toronto, Canada, pp5.
  • Fadakar-A Y, 2018, “Simulation Conditioned To Borehole”, Alghalandis Computing, Toronto, Canada, pp4.
  • Fadakar-A Y, 2018, “Tensor Permeability”, Alghalandis Computing, Toronto, Canada, pp7.
  • Fadakar-A Y, 2018, “Well To Reservoir All Stages”, Alghalandis Computing, Toronto, Canada, pp5.

Fadakar-A Y, “Stochastic modelling of fractures in rock masses”, PhD Thesis

  • Online (Mar 2015) Library, University of Adelaide
  • Printed (Jul 2014) School of Civil, Environmental and Mining Engineering, the University of Adelaide, Adelaide, SA, Australia

Fracture and fracture network modelling is a multi-disciplinary research area. Although the literature in general is significant, many research challenges remain. The complex geometry and topology of realistic fracture networks largely determine the static and dynamic mechanical properties of rock. In applications to hot dry rock geothermal reservoirs it is not possible to observe or measure fractures directly on any scale and the only data available are indirect measurements, such as seismic activity generated by hydraulic fracture stimulation. The lack of direct data and the complexities of the fracture characteristics make fracture network prediction and modelling in these applications very difficult. The ultimate purpose of the fracture and fracture network models is to evaluate the response of the fracture system to stress regimes and fluid flow. As understanding of the effective factors in the geometrical modelling of fractures and consequently topological properties of fracture networks increases, more accurate and hence more reliable results can be achieved from associated analyses. For flow modelling in geothermal reservoirs, the critical component of a fracture model is the connectivity of the fractures as this determines the technical feasibility of heat production and is the single most significant factor in converting a heat resource to a reserve. The ability to model this component effectively and to understand the associated system is severely constrained by the lack of direct data. In simulations, the connectivity of a fracture network can be controlled to a limited extent by adjusting the fracture and fracture network parameters (e.g., locations, orientations) of the defining distribution functions. In practical applications connectivity is a response of the system not a variable. It is essential to pursue modelling methods that maximise the extraction of information from the available data so as to achieve the highest possible accuracy in the modelling. Although the evaluation of fracture connectivity is an active research area, widely reported in the literature, almost all connectivity measures are based on degraded representations of the fracture network i.e., lattice-based. The loss of fracture connectivity information caused by using discrete representations is significant even when very high resolutions (assuming they are feasible) are used. This is basically due to the fact that the aperture dimensions of fractures are several magnitudes smaller than their lengths. If discretisation is necessary, then a better approach would be to retain all connectivity information between fractures, i.e. for connectivity information to remain invariant to the resolution of the discretisation. Such a method would provide more reliable evaluation of connectivity. This thesis covers the modelling of fracture networks, the characterisation (particularly connectivity) of fracture networks and applications.

Fadakar-A Y, “Applications of fuzzy logic and fractal geometry in geochemical explorations”, MSc Thesis

  • Printed (Sep 2004) Department of Mining Engineering, the University of Tehran, Tehran, Iran

The complexity which governs in natural phenomena makes them irregular at first; but nowadays by using new topics of Fractals which use specific regularities for accurate and real description and also fuzzy which shows obviousness of doubts, our knowledge about nature continuously increase. In this thesis we have tried to use modern techniques of fractal geometry in geochemical explorations which consists technique of concentration-area and technique of power-spectrum analysis and also modem methods of fuzzy logic which consists of fuzzy clustering and fussy c-means clustering analysis with all of the details which processed with chemical element data such as Pb, Zn, Cu, As obtained from samples witch were taken from the stream sediments of Raver 1:50000 sheet. For all the methods the results were shown in graphs and maps. There are complete chapters which include each of these techniques. It was shown in this thesis that fractal methods could successfully separate the anomaly area from background. The Fuzzy methods could also separate anomaly from background in several models (residual, enrichment index). Each of these methods has their own advantages and disadvantages that can be evaluated based on the stage of comparison. The simplicity of fractal concentration-area method in comparison with fractal power-spectrum analysis method which is really complex has been shown.

Fadakar-A Y, Elmo D, Eberhardt E, “Similarity Analysis of Discrete Fracture Networks”

Applications of Discrete Fracture Network (DFN) modeling are becoming increasingly prevalent in engineering analyses involving fractured rock masses. For example, kinematic evaluations of slope or underground excavation stability and the modeling of fluid flow in fractured rock have been shown to benefit significantly from the explicit representation of DFN realizations in the simulations. In practice, due to high computing costs, namely time, a balance must be struck that limits analyses to the consideration of only a few realizations as input. As a stochastic representation, a single realization is only one possibility. It is therefore critical that the selected realizations (possibilities) are able to summarize the range of variations present in the input parameters adequately for the purpose of study or practice. That is, the significance of diversity (dissimilarity) in the generated fracture networks is of great importance and should be assessed prior to further often time-consuming processing stages. We demonstrate here a novel development in the analysis of the similarity between three-dimensional fracture networks, which provides an accurate, efficient and practical solution with comprehensive coverage of model variations. Several examples are presented together with a comparison between the proposed three-dimensional method and existing methods limited to two-dimensional assumptions. It is shown that the two-dimensional similarity methods despite their popularity are heavily biased and poorly represent the reality.

Fadakar-A Y, “ADFNE: Open Source Software for Discrete Fracture Network Engineering, Two and Three Dimensional Applications”

  • Online (Feb 2017) {}
  • Printed (May 2017) Journal of Computers and Geosciences, 102:1-11

Rapidly growing topic, the discrete fracture network engineering (DFNE), has already attracted many talents from diverse disciplines in academia and industry around the world to challenge difficult problems related to mining, geothermal, civil, oil and gas, water and many other projects. Although, there are few commercial software capable of providing some useful functionalities fundamental for DFNE, their costs, closed code (black box) distributions and hence limited programmability and tractability encouraged us to respond to this rising demand with a new solution. This paper introduces an open source comprehensive software package for stochastic modeling of fracture networks in two- and three-dimension in discrete formulation. Functionalities included are geometric modeling (e.g., complex polygonal fracture faces, and utilizing directional statistics), simulations, characterizations (e.g., intersection, clustering and connectivity analyses) and applications (e.g., fluid flow). The package is completely written in Matlab scripting language. Significant efforts have been made to bring maximum flexibility to the functions in order to solve problems in both two- and three-dimensions in an easy and united way that is suitable for beginners, advanced and experienced users.

The above paper (ADFNE…) featured as the most downloaded article from Journal of Computers & Geosciences (Apr 2017).

Fadakar-A Y, Dowd P.A, Xu C, “Connectivity Field: A Measure for Characterising Fracture Networks”

  • Online (Feb 2014)
  • Printed (Jan 2015) Journal of Mathematical Geosciences, 47(1):63-83

Analysis of the connectivity of a fracture network is an important component of the design, assessment and development of fracture-based reservoirs in geothermal, petroleum and groundwater resource applications. It is a useful means of characterising the flow pathways and the mechanical behaviours of reservoirs. An appropriate practical measure is required for connectivity characterisation because of the extreme complexity of fracture networks. In this paper, we propose the {connectivity field} (CF), as a useful measure to evaluate the spatial connectivity characteristics of fractures in a fracture network. The CF can be applied on both a particular realisation of a fracture network model (for deterministic evaluation) and on stochastic fracture network models using stochastic modelling and Monte Carlo simulations (for probabilistic evaluation with uncertainties). Two extensions are also proposed: the generalised connectivity field, a measure that is independent of support size, and the probabilistic connectivity field. Potential applications of the CF and its extensions are in determining the optimal location of an injection or production well so as to maximise reservoir performance and in determining potential flow pathways in fracture networks. The average CF map shows strong correlations with the Xf and P21 measures. The relationships between the CF measures, the fracture intersection density and the fracture network connectivity index are also investigated.

Seifollahi S, Dowd P.A, Xu C, Fadakar-A Y, “A Spatial Clustering Approach for Stochastic Fracture Network Modelling.”

  • Online (Jul 2013)
  • Printed (Jul 2014) Journal of Rock Mechanics and Rock Engineering, 47(4):1225-1235

Fracture network modelling plays an important role in many application areas in which the behaviour of a rock mass is of interest. These areas include mining, civil, petroleum, water and environmental engineering and geothermal systems modelling. The aim is to model the fractured rock to assess fluid flow or the stability of rock blocks. One important step in fracture network modelling is to estimate the number of fractures and the properties of individual fractures such as their size and orientation. Due to the lack of data and the complexity of the problem, there are significant uncertainties associated with fracture network modelling in practice. Our primary interest is the modelling of fracture networks in geothermal systems and, in this paper, we propose a general stochastic approach to fracture network modelling for this application. We focus on using the seismic point cloud detected during the fracture stimulation of a hot dry rock reservoir to create an enhanced geothermal system; these seismic points are the conditioning data in the modelling process. The seismic points can be used to estimate the geographical extent of the reservoir, the amount of fracturing and the detailed geometries of fractures within the reservoir. The objective is to determine a fracture model from the conditioning data by minimizing the sum of the distances of the points from the fitted fracture model. Fractures are represented as line segments connecting two points in two-dimensional applications or as ellipses in three-dimensional (3D) cases. The novelty of our model is twofold: (1) it comprises a comprehensive fracture modification scheme based on simulated annealing and (2) it introduces new spatial approaches, a goodness-of-fit measure for the fitted fracture model, a measure for fracture similarity and a clustering technique for proposing a locally optimal solution for fracture parameters. We use a simulated dataset to demonstrate the application of the proposed approach followed by a real 3D case study of the Habanero reservoir in the Cooper Basin, Australia.

Fadakar-A Y, Dowd P.A, Xu C, “The RANSAC method for generating fracture networks from micro-seismic event data”

  • Online (Jan 2013)
  • Printed (Feb 2013) Journal of Mathematical Geosciences, 45(2):207-224

Fracture network modeling is an essential part of the design, development and performance assessment of Enhanced Geothermal Systems. These systems are created from geothermal resources, usually located several kilometers below the surface of the Earth, by establishing a network of connected fractures through which fluid can flow. The depth of the reservoir makes it impossible to make direct measurements of fractures and data are collected from indirect measurements such as geophysical surveys. An important source of indirect data is the seismic event point cloud generated by the fracture stimulation process. Locations of these points are estimated from recorded micro-seismic signals generated by fracture initiation, propagation and slip. This point cloud can be expressed as a set of three-dimensional coordinates with attributes, for example Se(ijk) ={(x,y,z);a|x,y,z in R,a in I}. We describe two methods for reconstructing realistic fracture trace lines and planes given the point cloud of seismic events data: Enhanced Brute-Force Search and RANSAC. The methods have been tested on a synthetic data set and on the Habanero data set of Geodynamics’ geothermal project in the Cooper Basin of South Australia. Our results show that the RANSAC method is an efficient and suitable method for the conditional simulation of fracture networks.

Afzal P, Harati H, Fadakar-A Y, Yasrebi A.B, “Application of spectrum-area fractal model to identify of geochemical anomalies based on soil data in Kahang porphyry-type Cu deposit, Iran”

  • Online (2013)
  • Printed (Dec 2013) Journal of Chemie der Erde-Geochemistry, 73(4):533-543

The aim of this study is to identify geochemical anomalies using power spectrum-area (S-A) method based on the grade values of Cu, Mo and Au in 2709 soil samples collected from Kahang porphyry-type Cu deposit, Central Iran. S-A log-log plots indicated that there are three stages of Cu, Mo and Au enrichment. The third enrichment was considered as the main stage for the presence of Cu, Mo and Au at the concentrations above 416 ppm, 23 ppm and 71 ppb, respectively. Elemental anomalies are positively associated with monzo-granite-diorite and breccias units which are in the central and western parts of the deposit. The anomalies are located within the potassic, phyllic and argillic alteration types and also there is the positive correlation between the anomalies and nearing faults in the studied area. The results obtained via fractal model were interpreted accordingly to incorporate the information for the mineralized areas including detailed geological map, structural analysis and alterations. The results show that S-A multifractal modeling is applicable for anomalies delineation based on soil data.

Afzal P, Fadakar-A Y, Moarefvand P, Rashidnejad-O N, Asadi-H H “Application of power-spectrum-volume fractal method for detecting hypogene, supergene enrichment, leached and barren zones in Kahang Cu porphyry deposit, Central Iran”

  • Online (2012)
  • Printed (Jan 2012) Journal of Geochemical Exploration, 112:131-138

The aim of this study was to identify various mineralization zones especially supergene enrichment and hypogene zones in Kahang Cu porphyry deposit by higher than 60 million tonnes of sulfide ore with an average grade of 0.6% Cu and 70 ppm Mo, which is situated in central Iran, based on analyzing the subsurface data using a proposed power spectrum-volume (P-V) fractal method. P-V method is used in frequency domain provided by application of Fourier series transformation on assay data. Straight lines fitted through log-log plots, showing P-V relations for Cu, were employed to separate supergene enrichment and hypogene zones from leached zone and barren host rock in the deposit. In the proposed P-V fractal method, the identification of mineralization zones is based on power-law relationship within power spectrum field (S) and the rock volume hosting Cu mineralization at different grades by applying a V(=S)?S-2/ß multifractal model. The subsurface data from deposit was analyzed by P-V fractal method and the results have been compared with geological models which included alteration and mineralogical models. The comparison shows that the interpreted zones based on the P-V fractal method have noticeable consistency to the geological models. The proposed P-V method is its either new approach to define zones in a mineral deposit and there was no professional software available to perform the relevant calculations; therefore, Fractal Power Spectrum-Volume (FPSV) software was programmed by the authors to achieve this goal.

Meshkani S.A, Mehrabi B, Yaghubpur A, Fadakar-A Y, “The application of geochemical pattern recognition to regional prospecting: A case study of the Sanandaj-Sirjan metallogenic zone, Iran”

  • Online (2011)
  • Printed (Mar 2011) Journal of Geochemical Exploration, 118(3):183-195

In regional exploration programs, the distribution of elements in known mineral deposits can be used as a guide for the classification of deposits, search for new prospects and modeling ore deposit patterns. The Sanandaj-Sirjan Zone (SSZ) is a major metallogenic zone in Iran, containing lead and zinc, iron, gold, copper deposits. In the central part of the SSZ, lead and zinc mineralization is widespread and hitherto exploration has been based on geological criteria. In this study, we used clustering techniques applied to element distribution for classification lead and zinc deposits in the central part of the SSZ. The hierarchical clustering technique was used to characterize the elemental pattern. Elements associated with lead and zinc deposits were separated into four clusters, encompassing both ore elements and their host rock-forming elements. It is shown that lead and zinc deposits in the central SSZ belong to two genetic groups: a MVT type hosted by limestone and dolomites and a SEDEX type hosted by shale, volcanic rocks and sandstone. The results of elemental clustering were used for pattern recognition by the K-means method and the respective deposits were classified into four distinct categories. K-means clustering also reveals that the elemental associations and spatial distribution of the lead and zinc deposits exhibit zoning in the central part of the SSZ. The ratios of ore-forming elements (Sb, Cd, and Zn) vs. (Pb and Ag) show zoning along an E-W trend, while host rock-forming elements (Mn, Ca, and Mg) vs. (Ba and Sr) show a zoning along a SE-NW trend. Large and medium deposits occur mainly in the center of the studied area, which justify further exploration around occurrences and abandoned mines in this area. The application of a pattern recognition method based on geochemical data from known mineralization in the central SSZ, and the classification derived from it, uncover elemental zoning, identify key elemental associations for further geochemical exploration and the potential to discover possible target areas for large to medium size ore deposits. This methodology can be applied in a similar way to search for new ore deposits in a wide range of known metallogenic zones.

Afzal P, Fadakar-A Y, Khakzad A, Moarefvand P, Rashidnejad-O N, “Delineation of mineralization zones in porphyry Cu deposits by fractal concentration-volume modeling”

  • Online (2011)
  • Printed (Mar 2011) Journal of Geochemical Exploration, 108(3):220-232

The purpose of this study was to identify the various mineralization zones especially supergene enrichment and hypogene in two different Iranian porphyry Cu deposits, based on subsurface data and by using the proposed concentration-volume (C-V) fractal method. The Sungun and Chah-Firuzeh porphyry Cu deposits, which are situated in NW and SE Iran, respectively, were selected for this study. Straight lines fitted through log-log plots showing C-V relations for Cu were employed to separate supergene enrichment and hypogene zones from oxidation zones and barren host rocks in the two deposits and to distinguish a skarn mineralized zone from the hypogene zone in Sungun deposit. In the proposed C-V fractal method, the identification of mineralization zones is based on power-law relationships between Cu concentrations and the volume of rocks hosting porphyry Cu mineralization. Separate subsurface data from the two deposits were analyzed by C-V fractal method and the results have been compared with geological models which included alteration and mineralogical models. The comparison shows that the interpreted zones based on the C-V fractal method are consistent with the geological models. The proposed C-V method is a new approach to defining zones in a mineral deposit and there was no commercial software available to perform the relevant calculations; therefore, a fractal concentration-volume (FCV) software was designed by the authors to achieve this goal.

Afzal P, Khakzad A, Moarefvand P, Rashidnejad-O N, Fadakar-A Y, “Introduction to New Concentration-Volume Fractal Method for Separation Zones in Porphyry Deposits”

  • Online (2009)
  • Printed (Oct 2009) Journal of Geosciences Scientific Quarterly, 78

Determination of different zones in porphyry deposits is on of important goals in their exploration because this operation especially determination supergene zone is important for economical study in these deposits. Traditional methods based on alterations and mineralogical studies are not proper in many cases because these methods are based on petrogaraphical and mineralographical studies, only. Later methods were introduced basis fluid inclusions and isotopes are indirect methods and applied for alterations separation. Fractal methods are applicable in surface geological and geochemical studies for many reasons such as using all data, according to spatial distribution and anomalies geometrical shapes. In this research, concentration-volume method entitled new fractal method is introduced for separation of supergene, hypogene, oxidant and host rock based on major element grade in porphyry deposits. Mathematical base of this method by using of power-law function and partition function for fractal and multifractal modeling, concentration-volume is used for zones separation in Chah-Firuzeh Cu porphyry deposit in Shahrbabak in Kerman province. First, Cu distribution in this deposit was evaluated by geostatistical methods and concentration-volume logarithmic diagram that break points show grade boundaries of different zones and boundary between mineralization and host rock. Also, alteration, mineralogical and zonation models were constructed based on geological observation and compared by results from concentration-volume fractal method. Separated zones by this fractal method are smaller and near to fact and correlated by geological models. Usage of grade parameter that is most important direct and quality parameter constructed reality results.

Afzal P, Fadakar-A Y, Khakzad A, Moarefvand P, Rashidnejad-O N, “Application of power spectrum-area fractal model to separate anomalies from background in Kahang Cu-Mo porphyry system, Central Iran”

  • Online (2010)
  • Printed (Dec 2010) Journal of Archives of Mining Sciences, 55(3):389-401

The aim of this research was the application of power spectrum-area (P-A) fractal model to separate geochemical anomalies for Cu, Mo and Au as a case study for Kahang porphyry Cu-Mo deposit, central Iran. Scaling distinctions (scaling range and power-law exponent) can be detected from the power spectrum field (S) by applying a A(=S)8S-2,/ßl (Spectrum-Area) multifractal model. Multiple scaling properties (bi-fractal properties as a special case) were observed from lithogeochemical data from Kahang porphyry deposit Central Iran. The power spectrum in the range of S>100 reflects the elemental background in Cu-Mo porphyry mineralization and the exponent 2/beta=2 indicates high intensity anomalies of thoese elements, whereas the depicted anomalies were correlated with geological including lithological units, alterations and faults. High intensity of elemental anomalies is located in central parts of the deposit and lower anomalies are situated in eastern and western parts.

Afzal P, Khakzad A, Moarefvand P, Rashidnejad-O N, Esfandiari B, Fadakar-A Y, “Geochemical anomaly separation by multifractal modeling in Kahang (Gor Gor) porphyry system, Central Iran”

  • Online (2010)
  • Printed (Jan-Feb 2010) Journal of Geochemical Exploration, 104(1-2):34-46

Geochemical anomaly separation using the concentration-area (C-A) method at Kahang (Gor Gor) porphyry system in Central Iran is studied in this work. Lithogeochemical data sets were used in this geochemical survey which was conducted for the exploration for Cu mineralization in dioritic and andesitic units at Kahang Cu-Mo porphyry system. Similar surveys were also carried out for Mo and Au exploration in these rock units. The obtained results have been interpreted using rather extensive set of information available for each mineralized area, consists of detailed geological mapping, structural interpretation and alteration data. Anomalous threshold values for the mineralized zone were computed and compared with the statistical methods based on the data obtained from chemical analysis of samples for the lithological units. Several anomalies at a local scale were identified for Cu (224 ppm), Mo (63 ppm), and Au (31 ppb), and the obtained results suggests existence of local Cu anomalies whose magnitude generally is above 1000 ppm. The correlation between these threshold values and ore grades is clearly interpreted in this investigation. Also, the log-log plots show existence of three stages of Cu enrichment, and two enrichment stages for Mo and Au. The third and most important mineralization event is responsible for the presence of Cu at grades above 1995 ppm. The identified anomalies in Kahang porphyry system, and distribution of the rock types, are mainly monzodiorite and andesitic units, do have special correlation with Cu and monzonitic and dioritic rocks, especially monzodioritic type, which is of considerable emphasis. The threshold values obtained for each element are always lower than their mean content in the rocks. The study shows threshold values for Cu is clearly above the mean rock content, being a consequence of the occurrence of anomalous accumulations of phyllic, argillic and propyllitic alterations within the monzonitic and dioritic rocks especially in monzodioritic type. The obtained results were compared with fault distribution patterns which reveal a positive direct correlation between mineralization in anomalous areas and the faults present in the mineralized system.

Afzal P, Fadakar-A Y, Khakzad A, Moarefvand P, Rashidnejad-O N, Esfandiari B, “Mine evaluation by application of power-spectrum-area analysis”

  • Online (2009)
  • Printed (Dec 2009) Iranian Quarterly Journal of Earth and Resources, 2(1):9-20

{ In Persian; Visit the above link }

Fadakar-A Y, Elmo D, “Application of Graph Theory for Robust and Efficient Rock Bridge Analysis”

  • Online (Jun 2018) {DFNE2018}
  • Download from: {Alghalandis Computing @}
  • Proceedings (2018) {DFNE2018} June 20-22, 2018 | Seattle, WA, USA, DFNE 18-733.

Rock bridge analysis is a fundamental task in numerical modeling of rock slope failure, and other rock stability analyses. However, the question of what constitutes a rock bridge is quite complex and it depends on whether a definition is given based on a geometrical characterization of the fracture network, or whether the definition is given to also incorporate an analysis of failure mechanisms. The former is the focus of this paper. From a geometrical perspective, rock bridges could be defined as the shortest distance between two existing fractures; however, for a fractured rock mass even this simple definition would yield multiple complex critical paths. In the literature, several probabilistic limit equilibrium methods exist incorporating step-path analysis into rock slope design. In this paper, a novel and efficient method is presented that analyzes the rock mass in any complexity for all potential rock bridges. The output is not limited to the optimum pathway, rather it includes a detailed analysis of the network connectivity by considering multiple pathways. By using Graph theory models and tools, the proposed approach provides significant flexibility to incorporate multiple scenarios such as weighted rock bridges and classes of rock bridges.

Fadakar-A Y, Xu C, “A New Hybrid Mesh-Pipe Method for Flow Modeling in 3D Discrete Fracture Networks”

  • Online (Jun 2018) {DFNE2018}
  • Download from: {Alghalandis Computing @}
  • Proceedings (2018) {DFNE2018} June 20-22, 2018 | Seattle, WA, USA, DFNE 18-742.

Flow characteristics of fracture networks are of great interest in applications in reservoir engineering. Assessing these characteristics requires in general significant efforts in conducting finite element analysis and then adapting the results by means of upscaling techniques to the entire reservoir. The use of commercial or other proprietary software for modeling these characteristics has been widely reported in the literature. While well developed, researchers might find the difficulty of access to the software or to the source codes. We aimed to address these difficulties by proposing a simple solution for modeling fluid flow through fractures in two and three-dimensional DFN models implemented in an open source package, built on a new hybrid mesh-pipe model. It is demonstrated that the proposed method is accurate and efficient. The application of our proposed method for the directional permeability analysis of DFN models is also discussed.

Fadakar-A Y, Dowd P.A, Xu C, “A Connectivity-Graph Approach to Optimising Well Locations in Geothermal Reservoirs”

  • Online (Nov 2013)
  • Download from: {Alghalandis Computing @}
  • Proceedings (2013) Australian Geothermal Energy Conference (AGEC2013), Brisbane, Australia

In this work we address the problem of optimal location of injection and production wells in fractured-based geothermal reservoirs. The optimisation is based on a distance distribution function, and the length and aperture of pathways between the two wells. The initial locations of the two candidate wells are chosen at random and the fracture pathways between the wells are determined using graph theory concepts. The weighted shortest pathway incorporates the equivalent aperture and total length of pathway elements (i.e., linked fractures). The method is efficient and effective for generating final optimal well locations (as coordinates) and also provides a map of optimality for any given fracture network. The sampling scheme used can incorporate any constraint including technical, topographical and or design. Furthermore, stochastic modelling of fracture networks can be used to extend the use of the proposed method to deal with the uncertainty involved in estimated or simulated fracture networks.

Fadakar-A Y, Xu C, Dowd P.A, “Connectivity Index and Connectivity Field towards fluid flow in fracture-based geothermal reservoirs”

  • Online (Feb 2013)
  • Download from: {Alghalandis Computing @}
  • Proceedings (2013) Stanford Geothermal Workshop Conference (SGW2013), Stanford, USA

Connectivity measures, such as the connectivity index and the connectivity field, are useful for determining preferential flow directions and flow pathways through fracture networks. However, the current implementation of these measures does not consider the hydraulic properties of the fracture network, which is the issue addressed in this work. We demonstrate that Darcy’s law can be incorporated into the evaluation of these measures using the persistence and aperture properties of fractures in the fracture network. We show that this incorporation can help determine more reliable and accurate flow pathways in the fracture network for three forms of aperture distributions: (i) constant aperture for each fracture cluster (pathway), (ii) variable aperture for each cluster and (iii) variable aperture for each fracture. We also introduce a new concept for the classification of pathways based on the reliability of their assessment, which enhances the understanding of the flow behaviour of fracture-based reservoirs as a result of fracture network expansion processes such as hydraulic stimulation.

Fadakar-A Y, Xu C, Dowd P.A, “A general framework for fracture intersection analysis: algorithms and practical applications”

  • Online (Nov 2011)
  • Download from: {Alghalandis Computing @}
  • Proceedings (2011) Australian Geothermal Energy Conference (AGEC2011), Melbourne, Australia

The modelling and simulation of fracture networks is a critical component of the assessment of hot dry rock (HDR) geothermal resources and of the design and creation of enhanced geothermal systems (EGS). The production of geothermal energy from an EGS depends on fluid pathways through the HDR and thus connectivity of fractures is essential. One way of assessing and modelling fracture connectivity is by intersection analysis. There is a notable lack of research in this area reported in the published literature probably because of the extreme complexity of three-dimensional fractures in HDR especially with respect to their geometrical characteristics i.e., shapes and orientations and spatial inter-relationships in the fracture network.
In this paper we present a framework for three-dimensional intersection analysis of fracture networks. The framework includes several robust algorithms for three-dimensional geometrical operations on various data structure configurations. We present two case studies to demonstrate the framework.
The first case study is a stochastic fracture network model generated by Monte Carlo sampling of marked point processes that incorporate the most significant fracture characteristics: location, orientation and shape. The second case study is a database of real measurements of fracture parameters. The proposed framework demonstrates the potential to accommodate any amount of complexity e.g., complicated intersections in a fracture network such as varying intensity, varying geometry and numbers of fractures. The resulting fracture intersection databases can be used for further applications such as statistical and spatial analysis of intersections and connectivity analysis.

Fadakar-A Y, Dowd PA, Xu C, “Application of Connectivity Measures in Enhanced Geothermal Systems”

  • Download from: {Alghalandis Computing @ }
  • Proceedings (2012) Australian Geothermal Energy Conference (AGEC2012), Sydney, Australia

The three major determinant factors for the productivity of hot dry rock geothermal reservoirs are fractures, fluid and heat. Fractures create an interconnected network that provides the pathways for fluid flow, which in turn facilitates heat exchange from the rock masses. The connection between fractures is therefore a critical characteristic of a successful heat producing geothermal system. Connectivity analysis is also an important component in the design, assessment and development of fracture-based reservoirs particularly enhanced geothermal systems. In this paper, we evaluate the application of two connectivity measures: the connectivity field and the connectivity index, of a fracture network. Both measures are well suited to stochastic modelling, which provides a means of incorporating the uncertainty due to lack of data. We demonstrate the effectiveness of both measures in the determination of preferential pathways through the fracture network. We also demonstrate the use of the connectivity field in determining the optimal location of an injection or production well so as to maximise the reservoir performance. The two measures show good correlation with other established connectivity measures such as Xf and P21 (P32). They are also shown to be useful in the evaluation of percolation state of a fractured rock mass.

Fadakar-A Y, Afzal P, “Important considerations on the application of IDW interpolation method”

  • Online (2010)
  • Proceedings (2010) 2nd Conference of Mine and Industry, Tehran, Iran


Fadakar-A Y, Amirnejad Mojdehi S, “Geostatistical Analysis Software Package”

  • Proceedings (2006) 5th Mining Engineering Student Conference, Esfahan University of Technology, Iran

Geostatistics is a branch of statistics which takes into account specific characteristics (spatial variation) of data and is widely used in statistical analysis of data in geosciences such as geology, geotechnics, geochemistry, etc. Merits and distinctive qualities of geostatistical methods have been widely accepted. however, there are few professional geostatistical analysis software packages and they have numerous limitations. increasing demand for such software, both in academic and industrial sectors, has been the main motivation for development of an new geostatistical software package. this paper introduces the software, giving its main features including algorithms of fitting experimental variogram by an optimized theoretical model. functionality and ease of use, together with its capability is compared to other existing software. snapshots of the environment and output figures and tables are also presented. the software is designed using .NET platform and Visual Basic.

Fadakar-A Y, “Application of Fractal Power Spectrum Method in Anomaly Separation from Background”

  • Proceedings (2005) Iranian Mining Engineering Conference, 31 Jan-2 Feb, Tarbiat Modares University, Iran

Fadakar-A Y, “IDW or Kriging Interpolation? That’s the Question.”

  • Proceedings (2011) 1st Conference of Spatial Statistics, 23-25 March, Enschede, The Netherlands

Fadakar-A Y, “GEONES: Software for Statistical Processing of Surface and Underground Geochemical Data”

  • Proceedings (2002) 3rd Mining Engineering Student Conference, Polytechnics Tehran, Iran