Scaling Geological Fracture Network from a Micro to a Macro Scale

Abstract Fractures are the prime conduits of flow for hydrocarbons in reservoir rocks. Identification and characterization of the fracture network yields valuable information for accurate reservoir evaluation. This study aims to portray the benefits and limitations for various existing fracture characterization methods and define strategic workflows for automated fracture characterization targeting both conventional and unconventional reservoirs separately. While traditional seismic provides qualitative information of fractures and faults on a macro scale, acoustics and other petrophysical logs provide a more comprehensive picture on a meso and micro level. High resolution image logs, with shallow depth of investigation are considered the industry standard for analysis of fractures. However, it is imperative to understand the framework of fracture in both near and far field. Various reservoir-specific collaborative workflows have been elucidated for a consistent evaluation of fracture network, results of which are further segregated using class-based machine learning techniques. This study embarks on understanding the critical requirements for fracture characterization in different lithological settings. Conventional reservoirs have good intrinsic porosity and permeability, yet presence of fractures further enhances the flow capacity. In clastic reservoirs, fractures provide an additional permeability assist to an already producible reservoir. In carbonate reservoirs, overall reservoir and production quality exclusively depends on presence of extensive fracture network as it quantitatively controls the fluid flow interactions among otherwise isolated vugs. Devoid of intrinsic porosity and permeability, the presence of open-extensive fractures is even more critical in unconventional reservoirs such as basement, shale-gas/oil and coal-bed methane, since it demarcates the reservoir zone and defines the economic viability for hydrocarbon exploration in reservoirs. Different forward modeling approaches using the best of conventional logs, borehole images, acoustic data (anisotropy analysis, borehole reflection survey and stoneley waveforms) and magnetic resonance logs have been presented to provide reservoir-specific fracture characterization. Linking the resolution and depth of investigation of different available techniques is vital for the determination of openness and extent of the fractures into the formation. The key innovative aspect of this project is the emphasis on an end-to-end suitable quantitative analysis of flow contributing fractures in different conventional and unconventional reservoirs. Successful establishment of this approach capturing critical information will be the stepping-stone for developing machine learning techniques for field level assessment.

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Discrete Fracture Network Modelling in Triassic–Jurassic Carbonates of NW Lurestan, Zagros Fold-and-Thrust Belt, Iran

Geosciences ◽

10.3390/geosciences9120496 ◽

2019 ◽

Vol 9 (12) ◽

pp. 496

Author(s):

Luigi Massaro ◽

Amerigo Corradetti ◽

Francesco d’Assisi Tramparulo ◽

Stefano Vitale ◽

Ernesto Paolo Prinzi ◽

...

Keyword(s):

Large Scale ◽

Line Drawing ◽

Fracture Network ◽

Poor Quality ◽

Discrete Fracture Network ◽

Network Modelling ◽

Multi Scale ◽

Fracture Systems ◽

Macro Scale ◽

Discrete Fracture

In this study, discrete fracture network (DFN) modelling was performed for Triassic–Jurassic analogue reservoir units of the NW Lurestan region, Iran. The modelling was elaborated following a multi-scale statistical sampling of the fracture systems characterising the analysed succession. The multi-scale approach was performed at two different observation scales. At the macro-scale, a digital outcrop analysis was carried out by means of a digital line-drawing based on camera-acquired images, focussing on the distribution of major throughgoing fractures; at the meso-scale, the scan line method was applied to investigate the background fractures of the examined formations. The gathered data were statistically analysed in order to estimate the laws governing the statistical distribution of some key fracture set attributes, namely, spacing, aperture, and height. The collected dataset was used for the DFN modelling, allowing the evaluation of the relative connectivity of the fracture systems and, therefore, defining the architecture and the geometries within the fracture network. The performed fracture modelling, confirmed, once again, the crucial impact that large-scale throughgoing fractures have on the decompartmentalization of a reservoir and on the related fluid flow migration processes. The derived petrophysical properties distribution showed in the models, defined the Kurra Chine Fm. and, especially, the Sehkaniyan Fm. as good-quality reservoir units, whereas the Sarki Fm was considered a poor-quality reservoir unit.

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Influence of local splitting behavior at intersections on infiltration in an unsaturated fracture network

10.5194/egusphere-egu21-3663 ◽

2021 ◽

Author(s):

Song Xue ◽

Zhibing Yang ◽

Yi-Feng Chen

Keyword(s):

Large Scale ◽

Preferential Flow ◽

Unsaturated Flow ◽

Flow Characteristics ◽

Fracture Network ◽

Liquid Volume ◽

Complex Flow ◽

Local Flow ◽

Divergent Flow ◽

Macro Scale

<p>Understanding and predicting the macro-scale flow characteristics in the fractured vadose zone is of great importance for subsurface hydrological applications. Here we develop a network model to study infiltration in unsaturated fracture networks. We consider an idealized honeycomb-like fracture network composed of a series of Y-shaped and inverted Y-shaped intersections. At the scale of intersections, liquid storage/release and splitting/convergence behaviors are modeled according to local splitting relationships obtained from detailed laboratory work and numerical simulations. By varying the splitting relationships, the influence of local flow behaviors on large scale flow structures is systematically investigated. We find that when the water split tends to split equally at the intersection, a divergent flow structure forms in the network. Conversely, unequal splitting leads to preferential pathways. We also find that an avalanche infiltration mode, i.e., sudden release of a large amount of water from the network, emerges spontaneously, and is modulated by the local splitting behavior. The pathways of preferential flow is controlled by the liquid volume triggered by avalanches and the network structure. The improved understanding from this study may shed new light on the complex flow dynamics for unsaturated flow in fractured media.</p>

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Comparison of DFN Modelled Microfracture Systems with Petrophysical Data in Excavation Damaged Zone

Applied Sciences ◽

10.3390/app11072899 ◽

2021 ◽

Vol 11 (7) ◽

pp. 2899

Author(s):

Risto Kiuru ◽

Dorka Király ◽

Gergely Dabi ◽

Lars Jacobsson

Keyword(s):

Geophysical Methods ◽

Fracture Network ◽

Rock Types ◽

Excavation Damaged Zone ◽

Macro Scale ◽

Damaged Zone ◽

Discrete Fracture ◽

Disturbed Layer ◽

The Difference ◽

Excavation Damage

Physical and petrographic properties of drill core specimens were determined as a part of investigations into excavation damage in the dedicated study area in the ONKALO® research facility in Olkiluoto, Western Finland. Microfractures in 16 specimens from two drillholes were analysed and used as a basis for fractal geometry-based discrete fracture network (DFN) modelling. It was concluded that the difference in resistivity between pegmatoid granite (PGR) and veined gneiss (VGN) specimens of similar porosity was likely due to differences in the types of microfractures. This hypothesis was confirmed from microfracture analysis and simulation: fractures in gneiss were short and mostly in one preferred orientation, whereas the fractures in granite were longer and had two preferred orientations. This may be due to microstructure differences of the rock types or could suggests that gneiss and granite may suffer different types of excavation damage. No dependencies on depth from the excavated surface were observed in the geometric parameters of the microfractures. This suggests that the excavation damaged zone cannot be identified based on the changes in the parameters of the microfracture networks, and that the disturbed layer observed by geophysical methods may be caused by macro-scale fractures.

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Tailoring microstructures of materials through biomimetics

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100148332 ◽

1993 ◽

Vol 51 ◽

pp. 500-501

Author(s):

Mehmet Sarikaya ◽

Ilhan A. Aksay

Keyword(s):

Chemical Properties ◽

Design And Synthesis ◽

Structure Sensitive ◽

Macro Scale ◽

Methods Of Synthesis ◽

Successive Level ◽

Engineering Materials ◽

Physical And Chemical ◽

And Chemical Properties ◽

Synthesis Of Materials

Biomimetics involves investigation of structure, function, and methods of synthesis of biological composite materials. The goal is to apply this information to the design and synthesis of materials for engineering applications.Properties of engineering materials are structure sensitive through the whole spectrum of dimensions from nanometer to macro scale. The goal in designing and processing of technological materials, therefore, is to control microstructural evolution at each of these dimensions so as to achieve predictable physical and chemical properties. Control at each successive level of dimension, however, is a major challenge as is the retention of integrity between successive levels. Engineering materials are rarely fabricated to achieve more than a few of the desired properties and the synthesis techniques usually involve high temperature or low pressure conditions that are energy inefficient and environmentally damaging.In contrast to human-made materials, organisms synthesize composites whose intricate structures are more controlled at each scale and hierarchical order.

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