Big data in microstructure analysis: Building a universal orientation system for thin sections

Tikoff, Basil; Chatzaras, Vasileios; Newman, Joseph W.; Roberts, Nicolas

doi:10.1016/j.jsg.2018.09.019

Cited by 7 publications

(13 citation statements)

References 3 publications

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“…Each pixel in the base maps would then contain a unique XYZ position within both the billet and the borehole at-large. A recent study [4] prescribes a universal system for defining the spatial orientation of petrographic thin sections that is primarily based on a robust notching procedure that provides all information required for geometric transformation into 3D billet space (Figure 10). Though the authors did not focus on GIS-based implementation of the framework, they have suggested procedures that would complement spatially explicit map visualizations of 3D billet models and 2D thin section-based data from optical, SEM, and CL image analyses.…”

Section: Discussionmentioning

confidence: 99%

“…J. Geo-Inf. 2021, 10, 332 2 of 16 processes is potentially limited without novel geospatial techniques for integrating various 2D and 3D data sources [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

“…Previous work demonstrates the viability of GIS for multi-source data management and integration [10][11][12], while others have utilized built-in remote sensing tools to extract spatial information from microscopic image data [13][14][15][16][17][18]. Additional studies have developed methods for linking and reorientation of petrographic thin sections to realworld geographic coordinates [4,19,20]. In this respect, the work of Linzmeier et al [21] is particularly informative, creating a framework for spatial registration of multi-source microstructural data from within a single thin section in arbitrary, two-dimensional space.…”

Section: Introductionmentioning

confidence: 99%

“…By using GIS software to integrate raster images from optical and electron microscopes, along with vector point data from secondary ion mass spectrometry (SIMS) and electron probe microanalysis (EPMA), the authors mapped the distribution of structural and chemical characteristics across various crystal grains [21]. Another study that our method expands upon is that of Basil Tikoff et al [4]. They propose a robust framework for defining the orientation of thin sections relative to sampled billets and the entire drill core, providing a tractable spatial registration method for use with both local and geographic coordinate systems.…”

Section: Introductionmentioning

confidence: 99%

“…Figure10. Schematic representation of thin section orientation framework depicting: (A) Definition of billet sectioning planes XY, XZ, and YZ with respect to within-billet foliation plane; and (B) Suggested markings to be placed on physical thin sections for spatial referencing within the local coordinates of billet models (2D section markings in B were adapted after Tickoff et al[4]). …”

mentioning

confidence: 99%

See 4 more Smart Citations

Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples

Holmes

Gaughan

Biddle

et al. 2021

IJGI

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Core samples obtained from scientific drilling could provide large volumes of direct microstructural and compositional data, but generating results via the traditional treatment of such data is often time-consuming and inefficient. Unifying microstructural data within a spatially referenced Geographic Information System (GIS) environment provides an opportunity to readily locate, visualize, correlate, and apply remote sensing techniques to the data. Using 26 core billet samples from the San Andreas Fault Observatory at Depth (SAFOD), this study developed GIS-based procedures for: 1. Spatially referenced visualization and storage of various microstructural data from core billets; 2. 3D modeling of billets and thin section positions within each billet, which serve as a digital record after irreversible fragmentation of the physical billets; and 3. Vector feature creation and unsupervised classification of a multi-generation calcite vein network from cathodluminescence (CL) imagery. Building on existing work which is predominantly limited to the 2D space of single thin sections, our results indicate that a GIS can facilitate spatial treatment of data even at centimeter to nanometer scales, but also revealed challenges involving intensive 3D representations and complex matrix transformations required to create geographically translated forms of the within-billet coordinate systems, which are suggested for consideration in future studies.

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Section: Discussionmentioning

confidence: 99%

“…J. Geo-Inf. 2021, 10, 332 2 of 16 processes is potentially limited without novel geospatial techniques for integrating various 2D and 3D data sources [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples

Holmes

Gaughan

Biddle

et al. 2021

IJGI

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A closer look into slickensides: Deformation on and under fault surfaces

Ortega-Arroyo

Peč

2023

Journal of Structural Geology

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StraboSpot data system for structural geology

et al. 2019

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StraboSpot is a geologic data system that allows researchers to digitally collect, store, and share both field and laboratory data. StraboSpot is based on how geologists actually work to collect field data; although initially developed for the structural geology research community, the approach is easily extensible to other disciplines. The data system uses two main concepts to organize data: spots and tags. A spot is any observation that characterizes a specific area, a concept applicable at any spatial scale from regional to microscopic. Spots are related in a purely spatial manner, and consequently, one spot can enclose multiple other spots that themselves contain other spots. In contrast, tags provide conceptual grouping of spots, allowing linkages between spots that are independent of their spatial position. The StraboSpot data system uses a graph database, rather than a relational database approach, to increase flexibility and to track geologically complex relationships. StraboSpot operates on two different platform types: (1) a field-based application that runs on iOS and Android mobile devices, which can function in either Internet-connected or disconnected environments; and (2) a web application that runs only in Internet-connected settings. We are presently engaged in incorporating microstructural data into StraboSpot, as well as expanding to include additional field-based (sedimentology, petrology) and lab-based (experimental rock deformation) data. The StraboSpot database will be linked to other existing and future databases in order to provide integration with other digital efforts in the geological sciences and allow researchers to do types of science that were not possible without easy access to digital data.

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Big data in microstructure analysis: Building a universal orientation system for thin sections

Cited by 7 publications

References 3 publications

Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples

Geospatial Management and Analysis of Microstructural Data from San Andreas Fault Observatory at Depth (SAFOD) Core Samples

A closer look into slickensides: Deformation on and under fault surfaces

StraboSpot data system for structural geology

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