Now you see me... : Impact of sample representativity in fracture network characterization.

2021 ◽  
Author(s):  
Fatemeh Nazari Vanani ◽  
Oscar Fernandez
Keyword(s):  
Network Connectivity ◽  
Sampling Bias ◽  
Fracture Network ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Borehole Data ◽  
Fracture Frequency ◽  
Hard Data ◽  
Volume Measurements ◽  
Synthetic Datasets

<p>Adequately characterizing the properties of a fracture network is the first step in accurately modelling its behavior, be it mechanically or hydraulically. Characterizing fracture networks requires determining fracture frequency, orientation, connectivity, and fracture properties. This becomes particularly challenging in subsurface systems, where hard data on fracture networks comes mainly from boreholes, that are samples of very limited volume in relation to the fracture network. Because of this scale relationship between sample dimension and the dimension of natural fracture networks, boreholes capture a very partial picture of the fracture network. This is particularly relevant when attempting to estimate fracture frequency and network connectivity from borehole data. Corrections are normally used to account for sampling bias related to fracture size and orientation. Whereas these corrections are valid for the sample itself, the topology and heterogeneity of fracture networks means that measurements obtained in any given borehole are not necessarily representative of the broader fracture network.</p><p>To determine how “wrong” single-borehole analyses can be, we have conducted experiments on synthetic datasets to quantify how representative borehole samples are of entire fracture networks. Results show that properties that have an impact on the anisotropy of the fracture network (orientation, number of fracture sets) can be accurately resolved even in low data-density scenarios. On the contrary, accurately determining fracture frequency (which also impacts connectivity) for the entire fracture network is strongly dependent on the ratio between fracture frequency and the sampled volume. Measurements of fracture frequency in individual boreholes indicate that it frequency easily be overestimated or underestimated by a factor of 2 relative to the real network’s fracture frequency. The application of sampling bias corrections has a limited impact on reducing this error.</p><p>Based on the results from our experiments, we present methods to assess how representative of a fracture network a single borehole is. Representativity can be translated into uncertainty in fracture frequency, a metric that can be used in fracture modelling.</p>

Numerical Simulation of Complex Fracture Network Development by Hydraulic Fracturing in Naturally Fractured Ultratight Formations

2013 ◽  
Author(s):  
Hannes Hofmann ◽  
Tayfun Babadagli ◽  
Günter Zimmermann
Keyword(s):  
Fracture Network ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Network Development ◽  
Complex Fracture ◽  
Fracture Patterns ◽  
Fracture Systems ◽  
Fracture Development ◽  
Complex Fracture Network ◽  
Treatment Designs

The creation of large complex fracture networks by hydraulic fracturing is imperative for enhanced oil recovery from tight sand or shale reservoirs, tight gas extraction, and Hot-Dry-Rock (HDR) geothermal systems to improve the contact area to the rock matrix. Although conventional fracturing treatments may result in bi-wing fractures, there is evidence by microseismic mapping that fracture networks can develop in many unconventional reservoirs, especially when natural fracture systems are present and the differences between the principle stresses are low. However, not much insight is gained about fracture development as well as fluid and proppant transport in naturally fractured tight formations. In order to clarify the relationship between rock and treatment parameters, and resulting fracture properties, numerical simulations were performed using a commercial Discrete Fracture Network (DFN) simulator. A comprehensive sensitivity analysis is presented to identify typical fracture network patterns resulting from massive water fracturing treatments in different geological conditions. It is shown how the treatment parameters influence the fracture development and what type of fracture patterns may result from different treatment designs. The focus of this study is on complex fracture network development in different natural fracture systems. Additionally, the applicability of the DFN simulator for modeling shale gas stimulation and HDR stimulation is critically discussed. The approach stated above gives an insight into the relationships between rock properties (specifically matrix properties and characteristics of natural fracture systems) and the properties of developed fracture networks. Various simulated scenarios show typical conditions under which different complex fracture patterns can develop and prescribe efficient treatment designs to generate these fracture systems. Hydraulic stimulation is essential for the production of oil, gas, or heat from ultratight formations like shales and basement rocks (mainly granite). If natural fracture systems are present, the fracturing process becomes more complex to simulate. Our simulation results reveal valuable information about main parameters influencing fracture network properties, major factors leading to complex fracture network development, and differences between HDR and shale gas/oil shale stimulations.

Modelling large-scale fractured reservoirs efficiently for geothermal energy and groundwater flow

2020 ◽  
Author(s):  
Simon Oldfield ◽  
Mikael Lüthje ◽  
Michael Welch ◽  
Florian Smit
Keyword(s):  
Fluid Flow ◽  
Geothermal Energy ◽  
Large Scale ◽  
Fractured Reservoirs ◽  
Fracture Network ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Persistent Problem ◽  
Fracture Evolution ◽  
Rapid Generation

<p>Large scale modelling of fractured reservoirs is a persistent problem in representing fluid flow in the subsurface. Considering a geothermal energy prospect beneath the Drenthe Aa area, we demonstrate application of a recently developed approach to efficiently predict fracture network geometry across an area of several square kilometres.</p><p>Using a strain based method to mechanically model fracture nucleation and propagation, we generate a discretely modelled fracture network consisting of individual failure planes, opening parallel and perpendicular to the orientation of maximum and minimum strain. Fracture orientation, length and interactions vary following expected trends, forming a connected fracture network featuring population statistics and size distributions comparable to outcrop examples.</p><p>Modelled fracture networks appear visually similar to natural fracture networks with spatial variation in fracture clustering and the dominance of major and minor fracture trends.</p><p>Using a network topology approach, we demonstrate that the predicted fracture network shares greater geometric similarity with natural networks. Considering fluid flow through the model, we demonstrate that hydraulic conductivity and flow anisotropy are strongly dependent on the geometric connection of fracture sets.</p><p>Modelling fracture evolution mechanically allows improved representation of geometric aspects of fracture networks to which fluid flow is particularly sensitive. This method enables rapid generation of discretely modelled fractures over large areas and extraction of suitable summary statistics for reservoir simulation. Visual similarity of the output models improves our ability to compare between our model and natural analogues to consider model validation.</p>

scholarly journals Clustering, Connectivity and Flow Responses of Deterministic Fractal-Fracture Networks

2020 ◽  
Vol 54 ◽  
pp. 149-156
Author(s):  
Ajay K. Sahu ◽  
Ankur Roy
Keyword(s):  
Fractal Dimension ◽  
Spatial Clustering ◽  
Flow Behavior ◽  
Flow Simulation ◽  
Fractal Dimensions ◽  
Fracture Network ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Fracture Models ◽  
Fractal Fracture

Abstract. It is well known that fracture networks display self-similarity in many cases and the connectivity and flow behavior of such networks are influenced by their respective fractal dimensions. In the past, the concept of lacunarity, a parameter that quantifies spatial clustering, has been implemented by one of the authors in order to demonstrate that a set of seven nested natural fracture maps belonging to a single fractal system, but of different visual appearances, have different clustering attributes. Any scale-dependency in the clustering of fractures will also likely have significant implications for flow processes that depend on fracture connectivity. It is therefore important to address the question as to whether the fractal dimension alone serves as a reasonable proxy for the connectivity of a fractal-fracture network and hence, its flow response or, if it is the lacunarity, a measure of scale-dependent clustering, that may be used instead. The present study attempts to address this issue by exploring possible relationships between the fractal dimension, lacunarity and connectivity of fractal-fracture networks. It also endeavors to study the relationship between lacunarity and fluid flow in such fractal-fracture networks. A set of deterministic fractal-fracture models generated at different iterations and, that have the same theoretical fractal dimension are used for this purpose. The results indicate that such deterministic synthetic fractal-fracture networks with the same theoretical fractal dimension have differences in their connectivity and that the latter is fairly correlated with lacunarity. Additionally, the flow simulation results imply that lacunarity influences flow patterns in fracture networks. Therefore, it may be concluded that at least in synthetic fractal-fracture networks, rather than fractal dimension, it is the lacunarity or scale-dependent clustering attribute that controls the connectivity and hence the flow behavior.

Clustering, Connectivity and Flow in Naturally Fractured Reservoir Analogs

2021 ◽  
Author(s):  
Ajay K. Sahu ◽  
Ankur Roy
Keyword(s):  
Fractal Dimension ◽  
Oil And Gas ◽  
Flow Behavior ◽  
Oil And Gas Industry ◽  
Fracture Network ◽  
Natural Fracture ◽  
Fractured Reservoir ◽  
Fracture Networks ◽  
Gas Industry ◽  
Network Geometry

Abstract A previous study by the authors on synthetic fractal-fracture networks showed that lacunarity, a parameter that quantifies scale-dependent clustering in patterns, can be used as a proxy for connectivity and also, is an indicator of fluid flow in such model networks. In this research, we apply the concepts thus developed to the study of fractured reservoir analogs and seek solutions to more practical problems faced by modelers in the oil and gas industry. A set of seven nested fracture networks from the Devonian Sandstone of Hornelen Basin, Norway that have the same fractal-dimension but are mapped at different scales and resolutions is considered. We compare these seven natural fracture maps in terms of their lacunarity and connectivity values to test whether the former is a reasonable indicator of the latter. Additionally, these maps are also flow simulated by implementing a fracture continuum model and using a streamline simulator, TRACE3D. The values of lacunarity, connectivity and fluid recovery thus obtained are pairwise correlated with one another to look for possible relationships. The results indicate that while fracture maps that have the same fractal dimension show almost similar connectivity values, there exist subtle differences such that both the connectivity and clustering values change systematically with the scale at which the fracture networks are mapped. It is further noted that there appears to be a very good correlation between clustering, connectivity, and fluid recovery values for these fracture networks that belong to the same fractal system. The overall results indicate that while the fractal dimension is an important parameter for characterizing a specific type of fracture network geometry, it is the lacunarity or scale-dependent clustering attribute that controls connectivity in fracture maps and hence the flow properties. This research may prove helpful in quickly evaluating connectivity of fracture networks based on the lacunarity parameter. This parameter can therefore, be used for calibrating Discrete Fracture Network (DFN) models with respect to connectivity of reservoir analogs and can possibly replace the fractal dimension which is more commonly used in software that model DFNs. Additionally, while lacunarity has been mostly used for understanding network geometry in terms of clustering, we, for the first time, show how this may be directly used for understanding the potential flow behavior of fracture networks.

Clustering and Connectivity of Fractal-Fracture Networks: Are they related?

2020 ◽  
Author(s):  
Ajay Kumar Sahu ◽  
Ankur Roy
Keyword(s):  
Fractal Dimension ◽  
Spatial Clustering ◽  
Flow Behavior ◽  
Fractal Dimensions ◽  
Fracture Network ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Fractal System ◽  
Clustering Behavior ◽  
Fractal Fracture

<p>It well known that fracture networks display self-similarity in many cases and the connectivity and flow behavior of such networks are influenced by their respective fractal dimensions. One of the authors have previously implemented the concept of lacunarity, a parameter that quantifies spatial clustering, to demonstrate that a set of 7 nested natural fracture maps belonging to a single fractal system, but different visual appearances have different clustering attributes. Any scale-dependency in the clustering of fractures will also likely have significant implications for flow processes that depend upon fracture connectivity. It is therefore important to address the question as to whether the fractal dimension serves as a reasonable proxy  for the connectivity of a fractal-fracture network or is it the lacunarity parameter that may be used instead. The present study attempts to address this issue by studying the clustering behavior (lacunarity) and connectivity of fractal-fracture patterns. We compare the set of 7 nested fracture maps mentioned earlier which belong to a single fractal system, in terms of their lacunarity and connectivity values. The results indicate that while the maps that have the same fractal dimension have almost similar connectivity values, there exist subtle differences such that both the connectivity and clustering change systematically with the scale at which the networks are mapped. It is further noted that there appears to be an exact correlation between clustering and connectivity values. Therefore, it may be concluded that rather than fractal dimension, it is the lacunarity or scale-dependent clustering attribute that control connectivity in fracture networks.</p>

scholarly journals Numerical Simulation of Hydraulic Fracture Propagation in Coal Seams with Discontinuous Natural Fracture Networks

Processes ◽  
2018 ◽  
Vol 6 (8) ◽  
pp. 113 ◽  
Author(s):  
Shen Wang ◽  
Huamin Li ◽  
Dongyin Li
Keyword(s):  
Hydraulic Fracture ◽  
Fracture Propagation ◽  
Fracture Network ◽  
Natural Fracture ◽  
Cohesive Element ◽  
Natural Fractures ◽  
Fracture Networks ◽  
Coal Seams ◽  
Hydraulic Fracture Network ◽  
Hydraulic Fracture Propagation

To investigate the mechanism of hydraulic fracture propagation in coal seams with discontinuous natural fractures, an innovative finite element meshing scheme for modeling hydraulic fracturing was proposed. Hydraulic fracture propagation and interaction with discontinuous natural fracture networks in coal seams were modeled based on the cohesive element method. The hydraulic fracture network characteristics, the growth process of the secondary hydraulic fractures, the pore pressure distribution and the variation of bottomhole pressure were analyzed. The improved cohesive element method, which considers the leak-off and seepage behaviors of fracturing liquid, is capable of modeling hydraulic fracturing in naturally fractured formations. The results indicate that under high stress difference conditions, the hydraulic fracture network is spindle-shaped, and shows a multi-level branch structure. The ratio of secondary fracture total length to main fracture total length was 2.11~3.62, suggesting that the secondary fractures are an important part of the hydraulic fracture network in coal seams. In deep coal seams, the break pressure of discontinuous natural fractures mainly depends on the in-situ stress field and the direction of natural fractures. The mechanism of hydraulic fracture propagation in deep coal seams is significantly different from that in hard and tight rock layers.

scholarly journals The Propagation Behavior of Hydraulic Fracture in Rock Mass with Cemented Joints

Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Yongxiang Zheng ◽  
Jianjun Liu ◽  
Yun Lei
Keyword(s):  
Hydraulic Fracturing ◽  
Univariate Analysis ◽  
Fracture Propagation ◽  
Fracture Network ◽  
Parameter Analysis ◽  
Natural Fracture ◽  
Hydraulic Fractures ◽  
Fracture Networks ◽  
Form Complex ◽  
Propagation Behavior

The formation of the fracture network in shale hydraulic fracturing is the key to the successful development of shale gas. In order to analyze the mechanism of hydraulic fracturing fracture propagation in cemented fractured formations, a numerical simulation about fracture behavior in cemented joints was conducted based firstly on the block discrete element. And the critical pressure of three fracture propagation modes under the intersection of hydraulic fracturing fracture and closed natural fracture is derived, and the parameter analysis is carried out by univariate analysis and the response surface method (RSM). The results show that at a low intersecting angle, hydraulic fractures will turn and move forward at the same time, forming intersecting fractures. At medium angles, the cracks only turn. At high angles, the crack will expand directly forward without turning. In conclusion, low-angle intersecting fractures are more likely to form complex fracture networks, followed by medium-angle intersecting fractures, and high-angle intersecting fractures have more difficulty in forming fracture networks. The research results have important theoretical guiding significance for the hydraulic fracturing design.

Numerical Simulation of Complex Fracture Network Development by Hydraulic Fracturing in Naturally Fractured Ultratight Formations

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
Hannes Hofmann ◽  
Tayfun Babadagli ◽  
Günter Zimmermann
Keyword(s):  
Fracture Network ◽  
Natural Fracture ◽  
Fracture Networks ◽  
Network Development ◽  
Complex Fracture ◽  
Fracture Patterns ◽  
Fracture Systems ◽  
Fracture Development ◽  
Complex Fracture Network ◽  
Treatment Designs

The creation of large complex fracture networks by hydraulic fracturing is imperative for enhanced oil recovery from tight sand or shale reservoirs, tight gas extraction, and hot-dry-rock (HDR) geothermal systems to improve the contact area to the rock matrix. Although conventional fracturing treatments may result in biwing fractures, there is evidence by microseismic mapping that fracture networks can develop in many unconventional reservoirs, especially when natural fracture systems are present and the differences between the principle stresses are low. However, not much insight is gained about fracture development as well as fluid and proppant transport in naturally fractured tight formations. In order to clarify the relationship between rock and treatment parameters, and resulting fracture properties, numerical simulations were performed using a commercial discrete fracture network (DFN) simulator. A comprehensive sensitivity analysis is presented to identify typical fracture network patterns resulting from massive water fracturing treatments in different geological conditions. It is shown how the treatment parameters influence the fracture development and what type of fracture patterns may result from different treatment designs. The focus of this study is on complex fracture network development in different natural fracture systems. Additionally, the applicability of the DFN simulator for modeling shale gas stimulation and HDR stimulation is critically discussed. The approach stated above gives an insight into the relationships between rock properties (specifically matrix properties and characteristics of natural fracture systems) and the properties of developed fracture networks. Various simulated scenarios show typical conditions under which different complex fracture patterns can develop and prescribe efficient treatment designs to generate these fracture systems. Hydraulic stimulation is essential for the production of oil, gas, or heat from ultratight formations like shales and basement rocks (mainly granite). If natural fracture systems are present, the fracturing process becomes more complex to simulate. Our simulations suggest that stress state, in situ fracture networks, and fluid type are the main parameters influencing hydraulic fracture network development. Major factors leading to more complex fracture networks are an extensive pre-existing natural fracture network, small fracture spacings, low differences between the principle stresses, well contained formations, high tensile strength, high Young’s modulus, low viscosity fracturing fluid, and large fluid volumes. The differences between 5 km deep granitic HDR and 2.5 km deep shale gas stimulations are the following: (1) the reservoir temperature in granites is higher, (2) the pressures and stresses in granites are higher, (3) surface treatment pressures in granites are higher, (4) the fluid leak-off in granites is less, and (5) the mechanical parameters tensile strength and Young’s modulus of granites are usually higher than those of shales.

scholarly journals The growth of faults and fracture networks in a mechanically evolving, mechanically stratified rock mass: a case study from Spireslack Surface Coal Mine, Scotland

Solid Earth ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 2119-2140
Author(s):  
Billy James Andrews ◽  
Zoe Kai Shipton ◽  
Richard Lord ◽  
Lucy McKay
Keyword(s):  
Rock Mass ◽  
Coal Mine ◽  
Hydraulic Properties ◽  
Network Connectivity ◽  
Fracture Network ◽  
Network Evolution ◽  
Fracture Density ◽  
Fracture Networks ◽  
Surface Coal Mine ◽  
Lens Formation

Abstract. Fault architecture and fracture network evolution (and resulting bulk hydraulic properties) are highly dependent on the mechanical properties of the rocks at the time the structures developed. This paper investigates the role of mechanical layering and pre-existing structures on the evolution of strike–slip faults and fracture networks. Detailed mapping of exceptionally well exposed fluvial–deltaic lithologies at Spireslack Surface Coal Mine, Scotland, reveals two phases of faulting with an initial sinistral and later dextral sense of shear with ongoing pre-faulting, syn-faulting, and post-faulting joint sets. We find fault zone internal structure depends on whether the fault is self-juxtaposing or cuts multiple lithologies, the presence of shale layers that promote bed-rotation and fault-core lens formation, and the orientation of joints and coal cleats at the time of faulting. During ongoing deformation, cementation of fractures is concentrated where the fracture network is most connected. This leads to the counter-intuitive result that the highest-fracture-density part of the network often has the lowest open fracture connectivity. To evaluate the final bulk hydraulic properties of a deformed rock mass, it is crucial to appreciate the relative timing of deformation events, concurrent or subsequent cementation, and the interlinked effects on overall network connectivity.

Predicting Well Performance in Naturally Fractured Reservoir

2013 ◽  
Author(s):  
Yunsuk Hwang ◽  
Jiajing Lin ◽  
David Schechter ◽  
Ding Zhu
Keyword(s):  
Hydraulic Fracture ◽  
Fracture Network ◽  
Darcy Flow ◽  
Natural Fracture ◽  
Hydraulic Fractures ◽  
Natural Fractures ◽  
Well Performance ◽  
Fracture Networks ◽  
Complex Fracture ◽  
Complex Fracture Network

Multiple hydraulic fracture treatments in reservoirs with natural fractures create complex fracture networks. Predicting well performance in such a complex fracture network system is an extreme challenge. The statistical nature of natural fracture networks changes the flow characteristics from that of a single linear fracture. Simply using single linear fracture models for individual fractures, and then summing the flow from each fracture as the total flow rate for the network could introduce significant error. In this paper we present a semi-analytical model by a source method to estimate well performance in a complex fracture network system. The method simulates complex fracture systems in a more reasonable approach. The natural fracture system we used is fractal discrete fracture network model. We then added multiple dominating hydraulic fractures to the natural fracture system. Each of the hydraulic fractures is connected to the horizontal wellbore, and some of the natural fractures are connected to the hydraulic fractures through the network description. Each fracture, natural or hydraulically induced, is treated as a series of slab sources. The analytical solution of superposed slab sources provides the base of the approach, and the overall flow from each fracture and the effect between the fractures are modeled by applying the superposition principle to all of the fractures. The fluid inside the natural fractures flows into the hydraulic fractures, and the fluid of the hydraulic fracture from both the reservoir and the natural fractures flows to the wellbore. This paper also shows that non-Darcy flow effects have an impact on the performance of fractured horizontal wells. In hydraulic fracture calculation, non-Darcy flow can be treated as the reduction of permeability in the fracture to a considerably smaller effective permeability. The reduction is about 2% to 20%, due to non-Darcy flow that can result in a low rate. The semi-analytical solution presented can be used to efficiently calculate the flow rate of multistage-fractured wells. Examples are used to illustrate the application of the model to evaluate well performance in reservoirs that contain complex fracture networks.

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