An Introduction to SEM Operational Principles and Geologic Applications for Shale Hydrocarbon Reservoirs

Huang, Jason; Cavanaugh, Timothy; Nur, Boaz

doi:10.1306/13391699m1023580

Cited by 8 publications

(3 citation statements)

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“…In the case of SEM, a very well-focused electron beam is used whereas in the case of FIB, a highly accelerated ion beam is used to do the work. The ion beam is used to slice the selected area whereas the SEM scans the sliced sample simultaneously [46]. Figure 1 (H1 and H2) (Adopted from Wierzbicki et al [47]) shows the sliced 3 T3 fibroblast cell.…”

Section: History and Instrumentationmentioning

confidence: 99%

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Focused Ion Beam Tomography

Hassan¹,

Amin²,

Solangi³

et al. 2020

Ion Beam Techniques and Applications

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To study the fundamental effect of shape and morphology of any material on its properties, it is very essential to know and study its morphology. Focused ion beam (FIB) tomography is a 3D chemical and structural relationship studying technique. The instrumentation of FIB looks like that of the scanning electron microscopy (SEM), but there is a major difference in the beam used for scanning. For SEM, a beam of electrons is used with scanning medium whereas in FIB, a much focused beam of ions is used for scanning. FIB can be used for lithography and ablation purposes, but due to advancements and high-energy focused beam, it is nowadays being used as a tomographic technique. Tomography is defined as imaging by sectoring or cross-sectioning any desired area. The hyphenation of FIB with energydispersive spectrometry or secondary ion mass spectrometry can give us elemental analysis with very high-resolution 3D images for a sample. This technique contributes to acquaintance of qualitative and quantitative analyses, 3D volume creations, and image processing. In this chapter, we will discuss the advancements in FIB instrumentation and its use as 3D imaging tool for different samples ranging from nanometer (nm)-sized materials to micrometer (μm)-sized biological samples.

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Section: History and Instrumentationmentioning

confidence: 99%

“…Then there is the last lens that focuses the beam onto the sample surface. There is a backscattered electron detector at the vent, which catches the backscattered electrons; these electrons give information about the chemical composition and crystal structure of the sample [46].…”

Section: History and Instrumentationmentioning

confidence: 99%

Focused Ion Beam Tomography

Hassan¹,

Amin²,

Solangi³

et al. 2020

Ion Beam Techniques and Applications

View full text Add to dashboard Cite

show abstract

“…The scattered electrons from the sample are captured by detectors to create an image of the sample. The advantage of SEM is that it provides an image with high magnification and better resolution compared to the optical microscope [125,126].…”

Section: Scanning Electron Microscopymentioning

confidence: 99%

Preparation and characterization of biopolymeric microparticles for surface-enhanced Raman spectroscopy and fluorescent microscopy imaging

Mahmood

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Spectroscopy is an interesting research field because of its wide applications areas. Therefore, in my doctoral thesis, I was centering on the preparation and laser spectroscopic characterization of polymeric microparticles for different applications. Firstly, I prepared microparticles and estimated their optimal preparation conditions, then developed them to fabricate fluorescent microparticles to be used in imaging. Secondly, I obtained a new composite of polymer microparticles covered with gold nanoparticles to be used in surface-enhanced Raman spectroscopic applications to detect certain biomolecules. The first step of my doctoral research work was to study the reaction kinetics of DEGDMA monomer in different solvents upon gamma irradiation with different doses and to determine the dose dependence of the degree of conversion with Raman spectroscopy and mass difference measurements. Both methods showed good agreement in the DC, therefore, the Raman method was found to be an excellent method of choice to determine the conversion rate of the polymer by a non-contact, non-destructive and, in terms of realization, simple manner, having the potential for real-time remote monitoring in the irradiation chamber. The results were fitted using the Avrami equation, and the observed variations in reaction rate were attributed to the fact that the DEGDMA polymerization process behaves differently in alcohols and other solvents, as determined by their solubility values. In the second phase, I synthesized polymeric microparticles of DEGDMA monomer with ethyl propionate solvent by gamma radiation-initiated precipitation polymerization firstly, then FITC dye was incorporated into the polymer matrix to form luminescent FITC/DEGDMA microparticles. The morphology, size, bonding configuration, and emission properties of the microparticles were investigated by using SEM, Raman, PL spectroscopy, and LSFM, respectively. It was found that the structure of the FITC was preserved after the irradiation and the obtained microparticles have good emission properties. In the last part of my study, I have developed the method to synthesize SERS enhanced substrate by attaching gold nanoparticles to polymeric microparticles prepared by gamma radiation-initiated polymerization. Firstly, I fabricated poly(DEGDMA)/AuNPs composite and investigated their enhancement efficiency as a SERS substrate using R6G the common fluorescent probe dye. Secondly, the practical applications of proposed SERS substrates were tested by DNA strand-specific to the parasite Giardia lamblia (the β-giardin gene).

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Machine-learning-based object detection in images for reservoir characterization: A case study of fracture detection in shales

Tian

Daigle

2018

The Leading Edge

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Imaging tools are widely used in the petroleum industry to investigate structural features of reservoir rocks directly at multiple scales. Quantitative image analysis is often used to determine various rock properties, but it requires significant time and effort, particularly to analyze a large number of samples. Automated object detection represents a potential solution to this efficiency problem. This method uses computers to efficiently provide quantitative information for thousands of images. Automated fracture detection in scanning electron microscope (SEM) images is presented as an example to show the workflow of using advanced deep-learning tools for quantitative rock characterization. First, an automatic object-detection method is presented for fast identification and characterization of microfractures in shales. Using this approach, we analyzed 100 SEM images obtained from deformed and intact samples of a carbonate-rich shale and a siliceous shale with the goal of analyzing the abundance and characteristics of microfractures generated during hydraulic fracturing. Most of the fractures are detected with about 90% success rate relative to manual picking. Second, we obtained statistics of length and areal porosities of these fractures. The experimentally deformed samples had slightly more detectable microfractures (1.8 fractures/image on average compared to 1.6 fractures/image), and the microfractures induced by shear deformation tend to be short (<50 μm) in the Eagle Ford and long in the siliceous samples, presumably because of differences in rock fabric. In future work, this approach will be applied to characterize the shape and size of mineral grains and to analyze relationships between fractures and minerals.

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An Introduction to SEM Operational Principles and Geologic Applications for Shale Hydrocarbon Reservoirs

Cited by 8 publications

References 0 publications

Focused Ion Beam Tomography

Focused Ion Beam Tomography

Preparation and characterization of biopolymeric microparticles for surface-enhanced Raman spectroscopy and fluorescent microscopy imaging

Machine-learning-based object detection in images for reservoir characterization: A case study of fracture detection in shales

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