Simulation of the meso-macro-scale fracture network development law of coal water injection based on a SEM reconstruction fracture COHESIVE model

Fuel ◽  
2021 ◽  
Vol 287 ◽  
pp. 119475
Author(s):  
Jian Chen ◽  
Weimin Cheng ◽  
Gang Wang
Keyword(s):  
Water Injection ◽  
Fracture Network ◽  
Network Development ◽  
Cohesive Model ◽  
Macro Scale

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.

A Leap into Automation for Advanced Fracture Characterization

2021 ◽  
Author(s):  
Radhika Patro ◽  
Manas Mishra ◽  
Hemlata Chawla ◽  
Sambhaji Devkar ◽  
Mrinal Sinha ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fracture Network ◽  
Unconventional Reservoirs ◽  
Machine Learning Techniques ◽  
Coal Bed ◽  
Fracture Characterization ◽  
Learning Techniques ◽  
Macro Scale ◽  
Porosity And Permeability ◽  
Depth Of Investigation

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.

The Role of Micro-Proppants in Conductive Fracture Network Development

2019 ◽  
Author(s):  
Dharmendra Kumar ◽  
Ruben A. Gonzalez ◽  
Ahmad Ghassemi
Keyword(s):  
Fracture Network ◽  
Network Development

Modes and timing of fracture network development in poly-deformed carbonate reservoir analogues, Mt. Chianello, southern Italy

2012 ◽  
Vol 37 ◽  
pp. 223-235 ◽  
Author(s):  
Stefano Vitale ◽  
Francesco Dati ◽  
Stefano Mazzoli ◽  
Sabatino Ciarcia ◽  
Vincenzo Guerriero ◽  
...  
Keyword(s):  
Southern Italy ◽  
Fracture Network ◽  
Carbonate Reservoir ◽  
Network Development

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.

ENHANCING THE RESERVOIR PERFORMANCE BY ACCESSING THE RESERVOIR SWEET SPOTS GUIDED BY FAR-FIELD SONIC IMAGING: AN INTEGRATED CASE STUDY FROM THE NORWEGIAN NORTH SEA

2021 ◽  
Author(s):  
Harish Datir ◽  
◽  
Knut Arne Birkedal ◽  
Sachin Kriplani ◽  
Hege Porten ◽  
...  
Keyword(s):  
Field Data ◽  
Near Field ◽  
Water Injection ◽  
Fracture Network ◽  
Borehole Wall ◽  
Frequency Effect ◽  
Surface Image ◽  
Baseline Assumption ◽  
Core Permeability

The gas present in the Valhall overburden crest area interferes with the seismic data and obscures the fault detection (minor faults). Spatially resolving fractures and fracture network is essential for subsurface understanding and future well placement in this field, and it is a critical input to the dynamic reservoir model. Additionally, mapping the fracture network in poor permeable reservoir formation beyond the wellbore is crucial to identify completion intervals to maximize productivity/injectivity, and hence field value. The well 2/8-F-18 A was drilled on the crest of the Valhall field as a pilot water injector in Lower Hod formation, where core and data analysis formed the foundation for a future potential 11 well development. The well is placed in the southern section of the Valhall crest, and no major faults or strong amplitude features were mapped out in the overburden via surface seismic before drilling. In this case study, an integrated workflow is proposed and tested within the reservoir formation to identify “sweet” (permeable and fractured) zones beyond the wellbore. This is achieved using borehole acoustic data combined with image and ultrasonic imaging to characterize fracture networks beyond the borehole wall. The sonic imaging workflow identifies reflection events from fractures and faults and provides the true dip, azimuth, and location in 3-dimensions. This data is complemented by nuclear magnetic resonance (NMR), dielectric and spectroscopy data to understand reservoir petrophysics. NMR-derived permeability has also been evaluated for identifying high permeable zone in this formation, which primarily focuses on intergranular permeability of the formation a few inches away from the borehole wall. Reservoir textural heterogeneity and fractures beyond the wellbore wall make this method difficult to estimate or enhance the effective permeability estimate. The baseline assumption for the NMR permeability estimation is also not valid in Hod formation; the Timur and SDR equation needs significant change to match core permeability. Hence, the primary aim is to identify a fracture network that will help support water injection and maximize hydrocarbons production through them. The goal is to establish a workflow from the learnings of this study, performed on the pilot well, validate its findings with the near-field data (core, imaging, and ultrasonic), and optimize it if needed (described in the methodology section). The developed workflow is then intended to be used to optimize the placement of future wells. The results achieved from the integrated workflow identified a key fault and mapped it approximately 23 meters away on each side of the borehole. It also captures acoustic anomalies (high amplitudes), validated based on near-field data, resulting from a fracture network potentially filled with hydrocarbons. The final results show the sub-seismic resolution of the fracture and fault network not visible on surface seismic due to the gas cloud above the reservoir and frequency effect on the surface seismic when compared to borehole sonic data. Evidently enhancing the blurred surface image, which helps enhance the structural and dynamic model of the reservoir.

scholarly journals Scaling Geological Fracture Network from a Micro to a Macro Scale

2019 ◽  
Vol 14 (51) ◽  
pp. 71-80
Author(s):  
Rouhollah Basirat ◽  
Kamran Goshtasbi ◽  
Morteza Ahmadi
Keyword(s):  
Fracture Network ◽  
Macro Scale

scholarly journals Predicting fracture network development in crystalline rocks

2021 ◽  
Author(s):  
Jessica McBeck ◽  
John Mark Aiken ◽  
Ben Cordonnier ◽  
Yehuda Ben-Zion ◽  
Francois Renard
Keyword(s):  
Triaxial Compression ◽  
Local Stress ◽  
Fracture Network ◽  
Network Development ◽  
Network Characteristics ◽  
Fracture Length ◽  
Rock Cores ◽  
Fracture Development ◽  
The Relationship

<p>The geometric properties of fractures influence whether they propagate, arrest and coalesce with other fractures. Thus, quantifying the relationship between fracture network characteristics may help predict fracture network development, and hence precursors to catastrophic failure. To constrain the relationship and predictability of fracture characteristics, we deform eight rock cores under triaxial compression while acquiring in situ X-ray tomograms. The tomograms reveal precise measurements of the fracture network characteristics above 6.5 microns. We develop machine learning models to predict the value of each characteristic using the other characteristics, and excluding the macroscopic stress or strain imposed on the rock. The models predict fracture development more accurately in the experiments performed on granite and monzonite, than the experiments on marble. Fracture network development may be more predictable in these igneous rocks because their microstructure is more mechanically homogeneous than the marble, producing more systematic fracture development that is not strongly impeded by grain contacts and cleavage planes. The varying performance of the models suggest that fracture volume, length, and aperture are the most predictable of the characteristics, while fracture orientation is the least predictable. Orientation does not correlate with length, as suggested by the idea that the orientation evolves with increasing differential stress and thus fracture length. This difference between the observed and expected predictability of orientation highlights the significant influence of local stress perturbations on fracture growth within brittle material in laboratory-scale systems with many propagating and interacting fractures.</p>

Revisiting the Eland Field Lodgepole Mound Complex (Stark County, North Dakota) Twenty Years after its Discovery

2016 ◽  
Vol 53 (1) ◽  
pp. 29-70 ◽  
Author(s):  
Mark Longman ◽  
Stephen Cumella
Keyword(s):  
North Dakota ◽  
Black Shale ◽  
Water Injection ◽  
Oil Production ◽  
Fracture Network ◽  
Williston Basin ◽  
Injection Wells ◽  
Reservoir Rocks ◽  
Type Area ◽  
Central Montana

Eland Field, the most prolific Lower Mississippian Lodgepole mound complex found to date in the Williston Basin, covers an area of about 6 mi2 and has produced more than 29 MMBO from 16 wells in the 20 years since the field was discovered. Three of the field’s updip wells have each produced more than 4 MMBO from mounds more than 250 ft thick although generally only the top 20 to 30 ft of the mound is perforated. The lower Lodgepole reservoir rocks are commonly called Waulsortian mounds, but they are Waulsortian in age only and not the micrite-rich mudmounds found in the type area of Waulsort, Belgium. Instead of being mudmounds, they are composed mainly of marine-cemented microbial boundstones and skeletal grainstones with local stromatactis structures. The edges of the mounds dip as steeply as 40 to 60 degrees. Such steep dips would be impossible in a typical micrite-rich Waulsortian mound. In addition to the abundant microbial and marine cementation that lithified the Eland Field mound complex penecontemporaneously, organisms such as stalked crinoids, fenestrate bryozoans, and articulated brachiopods and ostracods thrived on the hard substrate provided by the mounds. However, these organisms were themselves incapable of forming a true reef framework. Unusual inward dip of the Upper Bakken black shale and significant thickening of the “Extra Bakken Shale” from zero up to about 40 ft immediately beneath the oil-producing lower Lodgepole mounds both support the idea that something structurally significant such as salt dissolution helped localize mound development. We conclude that dissolution of the Lower Devonian Prairie salt created a fracture network during and immediately after deposition of the upper Bakken black shale that allowed compaction-water expulsion-vents and/or warm springs to initiate formation of carbonate “towers” that localized formation of the Lodgepole mounds. The discovery well for Eland Field, the Knopik #1-11 (NW NW Sec. 11, T139N, R97W), was completed in January 1995 for 2707 BOPD and 1550 MCFGPD with no water. The field was developed over the next few years with up to 16 producing wells and 7 water injection wells. Waterflooding of Eland Field began in 1997 and climbed to over 500,000 barrels per month in just two months. Through September 2015, more than 95 MMBW had been injected into the field, but it has produced over 29.6 MMBO, doubling the 1996 estimated ultimate recovery of 12 to 15 MMBO. The field continues to produce with about a 5.5% oil cut. In terms of total cumulative oil production in the U.S. portion of the Williston Basin, Eland Field contains 3 of the top 10 wells, and other nearby Lodgepole producing fields contain 4 additional top 10 wells. This excellent oil production leads to the question: Is it possible that the only productive Lodgepole mound reservoirs in the Williston Basin, eight of which have been discovered to date (with all but one discovered in the mid-1990s) are limited to a small atoll-like area about 7 miles in diameter in northern Stark County, North Dakota? Certainly the presence of similar Lodgepole mounds in outcrops in central Montana (e.g., Bridger Range and Big Snowy and Little Belt mountains) and in the subsurface of the western Williston Basin suggests that other Lodgepole mound-type reservoirs could occur across much of the basin. The most promising areas in which to search for other Lodgepole mound reservoirs will be those where the Upper Bakken black shale is well developed and thermally mature because it is the source for the oil in the Lodgepole reservoirs in the Eland Field area.

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

Geosciences ◽  
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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