Parameters Affecting the Interaction Among Closely Spaced Hydraulic Fractures

Bunger, Andrew P.; Zhang, Xi; Jeffrey, Robert G.

doi:10.2118/140426-pa

Cited by 142 publications

(86 citation statements)

References 19 publications

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“…When modelling fracture growth, previous studies (Olson and Taleghani 2009;Bunger et al 2012;Wu and Olson 2015;Peirce and Bunger 2015) mostly assume that the fluid leakoff is negligible. The effect of the leakoff on the hydraulic fracturing of a single fracture has been shown in many studies (Carrier and Granet, 2012;Salimzadeh and Khalili, 2015;Salimzadeh et al, 2016).…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Effect of Poroelasticity on Hydraulic Fracture Interactions

et al. 2017

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This study investigates, by performing finite element-based simulations, the influence of fluid leak-off and poroelasticity on growth of multiple hydraulic fractures that initiate from a single horizontal well. In this research, poroelastic deformation of the matrix is coupled with fluid flow in the fractures, and fluid flow in the rock matrix, in three dimensions. Effects of the fluid leakoff and poroelasticity on the propagation of the neighboring fractures are studied by varying the matrix permeability, and the Biot coefficient. Simulation results show that the stress induced by the opening of the fractures, and the stress induced by the fluid leak-off, each have the effect of locally altering the magnitudes and orientations of the principal stresses, hence altering the propagation direction of the fractures. The stress induced by the opening of the fractures tends to propagate both of the fractures away from each other in a curved trajectory, whereas the effects of fluid leak-off and poroelasticity (i.e., a higher Biot coefficient) tend to straighten the curved trajectory.

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Section: Simulation Results and Analysismentioning

confidence: 99%

Effect of Poroelasticity on Hydraulic Fracture Interactions

et al. 2017

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“…For example, the higher occurrence of underground mine collapses and a few rock falls reported in the NWZ may be related to human-induced slope disturbance associated with mining activities. Excavation exposes weak bedding planes and the toe unloading on the cut slope, leading to repeated gravitational instabilities of cut slope due to reduction in normal stress and the increase in shear stress along the bedding planes [56]. In Africa, Che et al [57] documented landslide events in Limbe town on the slopes of Cameroon Mountain and observed that most landslide events in this area are accelerated by anthropogenic activities and triggered by high intensity rainfall.…”

Section: Triggering Factors For Landslide Occurrencementioning

confidence: 99%

Review of Spatial and Temporal Distribution of Landslides in Tanzania

Ja¹,

Kervyn²

2017

J Ecosyst Ecogr

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This paper intended to inventorize the occurrence of landslides in Tanzania in temporal and spatial terms. Specifically, the inventory focused on identifying areas in Tanzania which are prone to landslides, identifying the frequency of landslide occurrence in the country, identifying the underlying and triggering factors for landslides, the socio-economic impacts of landslides and assessing the people's perception of landslides in Tanzania. Identification and mapping of landslide was achieved through the use primary and secondary sources of information. Primary data was acquired through exploratory field visit to the 5 landslide scars in the north and south Pare Mountains in the northern highlands of Tanzania. Short discussion with local people in the areas was made to gain insights into their perception of landslides. Secondary data was acquired through the review of achieved sources. This review was made in respect of the landslides that were not covered by the aforementioned exploratory field visit. The EM-DAT was also used to provide information on the number of landslide events, fatalities and socio-economic impacts. Google Earth™ search and image interpretation were used to located and describe landslides in other regions of the country that were not covered by the aforementioned exploratory field study. A 90 m resolution Digital Elevation Model (DEM) from USGS for Tanzania was used to map the landslide scars identified through Google Earth search. Google Earth search and image interpretation were supported by secondary information from archived sources. The inventory noted that landslides in Tanzania have received relatively limited attention both in the literature and in government disaster management plans. With exception of studies conducted in Uluguru Mountain in 1970s, no formal landslide research has been made in recent years. Despite extensive web searches, no landslide inventory has been made in Tanzania. This may presumably be due to existing assumption that landslides in Tanzania have low frequency of occurrence and are localized compared to other disasters such as floods, epidemics and drought, whose occurrence affect many more people, drawing more community, government and media attention. This has thus, affected the way landslide events are reported and managed in the country. This assertion however, does not preclude the fact that one/few landslide events, depending on their magnitude, where they occur and nature of elements at risk, can affect significant number of people and vice versa. This inventory has also documented cultural perspectives on landslides. Care must be taken to incorporate appropriate indigenous knowledge and people's perception pertaining to landslides and other disasters as these are critical in designing and implementing culturallyinformed and low cost disaster management strategies. This may, in turn, obviate the need or reduce cost for early warning systems. Landslide information provided by some reviewed sources is limited in time and space. Most of the visi...

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“…The effect of fracture size and data uncertainties on fractured-rock permeability was analyzed by Sagar et al [1]; the parameters influencing the interaction among closely spaced hydraulic fractures were reported by Bunger [2]; the hydraulic conductivity of rough fracture surface was studied by References [3][4][5]. It is well known that the flow in fractures is influenced by many factors [6], such as: (1) flow behavior through single fractures, (2) fracture network pattern, and (3) in situ stress system.…”

Section: Introductionmentioning

confidence: 99%

Flow Simulation of Artificially Induced Microfractures Using Digital Rock and Lattice Boltzmann Methods

Yang

Liu

et al. 2018

Energies

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Abstract:Microfractures have great significance in the study of reservoir development because they are an effective reserving space and main contributor to permeability in a large amount of reservoirs. Usually, microfractures are divided into natural microfractures and induced microfractures. Artificially induced rough microfractures are our research objects, the existence of which will affect the fluid-flow system (expand the production radius of production wells), and act as a flow path for the leakage of fluids injected to the wells, and even facilitate depletion in tight reservoirs. Therefore, the characteristic of the flow in artificially induced fractures is of great significance. The Lattice Boltzmann Method (LBM) was used to calculate the equivalent permeability of artificially induced three-dimensional (3D) fractures. The 3D box fractal dimensions and porosity of artificially induced fractures in Berea sandstone were calculated based on the fractal theory and image-segmentation method, respectively. The geometrical parameters (surface roughness, minimum fracture aperture, and mean fracture aperture), were also calculated on the base of digital cores of fractures. According to the results, the permeability lies between 0.071-3.759 (dimensionless LB units) in artificially induced fractures. The wide range of permeability indicates that artificially induced fractures have complex structures and connectivity. It was also found that 3D fractal dimensions of artificially induced fractures in Berea sandstone are between 2.247 and 2.367, which shows that the artificially induced fractures have the characteristics of self-similarity. Finally, the following relations were studied: (a) exponentially increasing permeability with increasing 3D box fractal dimension, (b) linearly increasing permeability with increasing square of mean fracture aperture, (c) indistinct relationship between permeability and surface roughness, and (d) linearly increasing 3D box fractal dimension with increasing porosity.

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Parameters Affecting the Interaction Among Closely Spaced Hydraulic Fractures

Cited by 142 publications

References 19 publications

Effect of Poroelasticity on Hydraulic Fracture Interactions

Effect of Poroelasticity on Hydraulic Fracture Interactions

Review of Spatial and Temporal Distribution of Landslides in Tanzania

Flow Simulation of Artificially Induced Microfractures Using Digital Rock and Lattice Boltzmann Methods

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