Synchrotron tomographic quantification of strain and fracture during simulated thermal maturation of an organic‐rich shale, UK Kimmeridge Clay

Pilz, Fernando Figueroa; Dowey, Patrick J.; Fauchille, Anne‐Laure; Courtois, Loïc; Bay, Brian K.; Ma, Lin; Taylor, Kevin G.; Mecklenburgh, Julian; Lee, Peter

doi:10.1002/2016jb013874

Cited by 33 publications

(26 citation statements)

References 42 publications

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“…4 ). The geometry of pores is expected to affect significantly the propagation of induced fractures and porous flow behaviours 10 , 35 , 36 , but it has not been possible to evaluate these influences in many other models. The pore geometry and networking demonstrated here has the potential to provide higher accuracy and applicability to petrophysical modelling than an approach based solely on pore-throat sizes.…”

Section: Discussionmentioning

confidence: 99%

“…The key properties of shales that underpin commercial viability and minimize environmental impact, such as permeability, storativity, elastic properties and electrical conductivity, are directly related to pore-size distribution, pore geometry and the connectivity of the pore network 8 , 9 . For example, the location of nano-pores associated with organic matter or phyllosilicate minerals are pivotal not only for understanding pore generation and evolution during maturation and fracturing 10 , but also in controlling and influencing gas transport and storage 11 .…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical integration of porosity in shales

Slater

Dowey

et al. 2018

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Pore characterization in shales is challenging owing to the wide range of pore sizes and types present. Haynesville-Bossier shale (USA) was sampled as a typical clay-bearing siliceous, organic-rich, gas-mature shale and characterized over pore diameters ranging 2 nm to 3000 nm. Three advanced imaging techniques were utilized correlatively, including the application of Xe+ plasma focused ion beam scanning electron microscopy (plasma FIB or PFIB), complemented by the Ga+ FIB method which is now frequently used to characterise porosity and organic/inorganic phases, together with transmission electron microscope tomography of the nano-scale pores (voxel size 0.6 nm; resolution 1–2 nm). The three pore-size scales each contribute differently to the pore network. Those <10 nm (greatest number), 10 nm to 100 nm (best-connected hence controls transport properties), and >100 nm (greatest total volume hence determines fluid storativity). Four distinct pore types were found: intra-organic, organic-mineral interface, inter-mineral and intra-mineral pores were recognized, with characteristic geometries. The whole pore network comprises a globally-connected system between phyllosilicate mineral grains (diameter: 6–50 nm), and locally-clustered connected pores within porous organic matter (diameter: 200–800 nm). Integrated predictions of pore geometry, connectivity, and roles in controlling petrophysical properties were verified through experimental permeability measurements.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hierarchical integration of porosity in shales

Slater

Dowey

et al. 2018

Sci Rep

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“…Cracking induced by accelerated (i.e., ex-situ) desiccation of a cement paste containing glass beads was quantified via DVC [101]. Similarly, accelerated maturation of Kimmeridge clay was monitored in-situ up to 380°C [63] with 2-min acquisitions of 1800 radiographs. Sintering of copper was monitored in-situ at 1050°C.…”

Section: Introductionmentioning

confidence: 99%

Digital Volume Correlation: Review of Progress and Challenges

et al. 2018

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3D imaging has become popular for analyzing material microstructures. When time lapse series of 3D pictures are acquired during a single experiment, it is possible to measure displacement fields via digital volume correlation (DVC), thereby leading to 4D results. Such ForewordThe present paper aims at reviewing the major developments in Digital Volume Correlation (DVC) over the past ten years. It follows the first review on DVC that was published in 2008 by its pioneer [11]. In the latter, the interested reader will find all the general principles associated with what is now called local DVC. They will not be recalled hereafter. In such approaches the region of interest is subdivided into small subvolumes that are independently registered. In addition to its wider use with local approaches, DVC has been extended to global approaches in which the displacement field is defined in a dense way over the region of interest. Kinematic bases using finite element discretizations have been selected. To further add mechanical content, elastic regularization has been introduced. Last, integrated approaches use kinematic fields that are constructed from finite element simulations with chosen constitutive equations. The material parameters (and/or boundary conditions) then become the quantities of interest.These various implementations assume different degrees of integration of mechanical knowledge about the analyzed experiment. First and foremost, DVC can be considered as a stand-alone technique, which has seen its field of applications grow over the last ten years. In this case the measured displacement fields and post-processed strain fields are reported. With the introduction of finite element based DVC, the measured displacement field is continuous. It is also a standalone technique. However, given the fact that it shares common kinematic bases with numerical simulations, it can be easily combined with the latter. One route is to require local satisfaction of equilibrium via mechanical regularization. Another route is to fully merge DVC analyses and numerical simulations via integrated approaches. Different examples will illustrate how these various integration steps can be tailored and what are the current challenges associated with various approaches.

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“…Microstructural heterogeneities such as variations of grain size, shape, mineralogy, elasticity, anisotropy and stiffness, together with preexisting defects can create local stress concentrations. Such stress concentrations influence the initiation and behavior of fractures in shales, such as hydraulic fractures (Keneti and Wong 2010), mechanical fractures (Van de DRAFT Feb 2018 -5 Steen et al, 2003) and desiccation fractures (Hedan et al, 2012;Fauchille et al, 2016;Figueroa Pilz et al, 2017) in response to the local stress field. In a general sense, Sone and Zoback (2013) and Amann et al, (2014) have shown how significantly the microstructure can impact upon the mechanical properties of shale.…”

Section: Introductionmentioning

confidence: 99%