scholarly journals Rendering Semisynthetic FIB-SEM Images of Rock Samples

2021 ◽  
Author(s):  
Ilia Safonov ◽  
Anton Kornilov ◽  
Iryna Reimers
Keyword(s):  
Focused Ion Beam ◽  
Oil And Gas ◽  
Rock Sample ◽  
Pore Space ◽  
Ion Beam ◽  
Ground Truth ◽  
Fine Tuning ◽  
Back Side ◽  
Sem Images ◽  
Rock Samples

Digital rock analysis is a prospective approach to estimate properties of oil and gas reservoirs. This concept implies constructing a 3D digital twin of a rock sample. Focused Ion Beam - Scanning Electron Microscope (FIB-SEM) allows to obtain a 3D image of a sample at nanoscale. One of the main specific features of FIB-SEM images in case of porous media is pore-back (or shine-through) effect. Since pores are transparent, their back side is visible in the current slice, whereas, in fact, it locates in the following ones. A precise segmentation of pores is a challenging problem. Absence of annotated ground truth complicates fine-tuning the algorithms for processing of FIB-SEM data and prevents successful application of machine- learning-based methods, which require a huge training set. Recently, several synthetic FIB- SEM images based on stochastic structures were created. However, those images strongly differ from images of real samples. We propose fast approaches to render semisynthetic FIB- SEM images, which imply that intensities of voxels of mineral matrix in a milling plane, as well as geometry of pore space, are borrowed from an image of rock sample saturated by epoxy. Intensities of voxels in pores depend on the distance from milling plane to the given voxel along a ray directed at an angle equal to the angle between FIB and SEM columns. The proposed method allows to create very realistic FIB-SEM images of rock samples with precise ground truth. Also, it opens the door for numerical estimation of plenty of algorithms for processing FIB-SEM data.

scholarly journals Two-Stage Alignment of FIB-SEM Images of Rock Samples

2020 ◽  
Vol 6 (10) ◽  
pp. 107
Author(s):  
Iryna Reimers ◽  
Ilia Safonov ◽  
Anton Kornilov ◽  
Ivan Yakimchuk
Keyword(s):  
High Frequency ◽  
Focused Ion Beam ◽  
Pore Space ◽  
Ion Beam ◽  
Affine Transformations ◽  
Sem Images ◽  
Alignment Procedure ◽  
Natural Rock ◽  
Alignment Algorithms ◽  
Frequency Components

Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography provides a stack of images that represent serial slices of the sample. These images are displaced relatively to each other, and an alignment procedure is required. Traditional methods for alignment of a 3D image are based on a comparison of two adjacent slices. However, such algorithms are easily confused by anisotropy in the sample structure or even experiment geometry in the case of porous media. This may lead to significant distortions in the pore space geometry, if there are no stable fiducial marks in the frame. In this paper, we propose a new method, which meaningfully extends existing alignment procedures. Our technique allows the correction of random misalignments between slices and, at the same time, preserves the overall geometrical structure of the specimen. We consider displacements produced by existing alignment algorithms as a signal and decompose it into low and high-frequency components. Final transformations exclude slow variations and contain only high frequency variations that represent random shifts that need to be corrected. The proposed algorithm can operate with not only translations but also with arbitrary affine transformations. We demonstrate the performance of our approach on a synthetic dataset and two real FIB-SEM images of natural rock.

Application of High-Contrast µCT and FIB-SEM for the Improvement in the Permeability Prediction of Tight Rock Samples

2021 ◽  
Author(s):  
Alexander Avdonin ◽  
Mohammad Ebadi ◽  
Vladislav Krutko
Keyword(s):  
Focused Ion Beam ◽  
Pore Space ◽  
Ion Beam ◽  
High Contrast ◽  
Rock Samples ◽  
Digital Rock ◽  
Permeability Prediction ◽  
Permeable Rock ◽  
Rock Analysis

Abstract Digital rock analysis has proven to be useful for the prediction of petrophysical properties of conventional reservoirs, where the pore space is captured well by a modern µCT scanner with a resolution of 1-5 µm. Nevertheless, this resolution is not enough to accurately capture the pore space of tight (low-permeable) rock samples. As a result, derived digital rock models do not reflect the real rock topology, and permeability predictions yield unreliable results. Our approach deploys high-contrast µCT scanning technique and Focused Ion Beam milling combined with Scanning Electron Microscopy to improve the quality of digital rock models and, hence, the permeability prediction. This workflow is successfully applied to a low-permeable rock sample of Achimov deposits. The computed permeability compares well to the experimental value.

Machine-Learning-Assisted Segmentation of Focused Ion Beam-Scanning Electron Microscopy Images with Artifacts for Improved Void-Space Characterization of Tight Reservoir Rocks

SPE Journal ◽  
2021 ◽  
pp. 1-20
Author(s):  
Andrey Kazak ◽  
Kirill Simonov ◽  
Victor Kulikov
Keyword(s):  
Image Segmentation ◽  
Focused Ion Beam ◽  
Pore Space ◽  
Ion Beam ◽  
Reservoir Rock ◽  
Data Sets ◽  
Sem Images ◽  
Reservoir Rocks ◽  
Tight Reservoir

Summary The modern focused ion beam-scanning electron microscopy (FIB-SEM) allows imaging of nanoporous tight reservoir-rock samples in 3D at a resolution up to 3 nm/voxel. Correct porosity determination from FIB-SEM images requires fast and robust segmentation. However, the quality and efficient segmentation of FIB-SEM images is still a complicated and challenging task. Typically, a trained operator spends days or weeks in subjective and semimanual labeling of a single FIB-SEM data set. The presence of FIB-SEM artifacts, such as porebacks, requires developing a new methodology for efficient image segmentation. We have developed a method for simplification of multimodal segmentation of FIB-SEM data sets using machine-learning (ML)-based techniques. We study a collection of rock samples formed according to the petrophysical interpretation of well logs from a complex tight gas reservoir rock of the Berezov Formation (West Siberia, Russia). The core samples were passed through a multiscale imaging workflow for pore-space-structure upscaling from nanometer to log scale. FIB-SEM imaging resolved the finest scale using a dual-beam analytical system. Image segmentation used an architecture derived from a convolutional neural network (CNN) in the DeepUNet (Ronneberger et al. 2015) configuration. We implemented the solution in the Pytorch® (Facebook, Inc., Menlo Park, California, USA) framework in a Linux environment. Computation exploited a high-performance computing system. The acquired data included three 3D FIB-SEM data sets with a physical size of approximately 20 × 15 × 25 µm with a voxel size of 5 nm. A professional geologist manually segmented (labeled) a fraction of slices. We split the labeled slices into training, validation, and test data. We then augmented the training data to increase its size. The developed CNN delivered promising results. The model performed automatic segmentation with the following average quality indicators according to test data: accuracy of 86.66%, precision of 54.93%, recall of 83.76%, and F1 score of 55.10%. We achieved a significant boost in segmentation speed of 14.5 megapixel (MP)/min. Compared with 0.18 to 1.45 MP/min for manual labeling, this yielded an efficiency increase of at least 10 times. The presented research work improves the quality of quantitative petrophysical characterization of complex reservoir rocks using digital rock imaging. The development allows the multiphase segmentation of 3D FIB-SEM data complicated with artifacts. It delivers correct and precise pore-space segmentation, resulting in little turn-around-time saving and increased porosity-data quality. Although image segmentation using CNNs is mainstream in the modern ML world, it is an emerging novel approach for reservoir-characterizationtasks.

scholarly journals Shale fabric and organic nanoporosity in lower Palaeozoic shales, Bornholm, Denmark

2018 ◽  
pp. 17-20 ◽  
Author(s):  
Lucy Malou Henningsen ◽  
Christian Høimann Jensen ◽  
Niels Hemmingsen Schovsbo ◽  
Arne Thorshøj Nielsen ◽  
Gunver Krarup Pedersen
Keyword(s):  
Focused Ion Beam ◽  
Oil And Gas ◽  
Ion Beam ◽  
Mineralogical Composition ◽  
Gas Content ◽  
High Porosity ◽  
Gas Generation ◽  
Sem Images ◽  
Lower Palaeozoic ◽  
Pore Types

In organic-rich shales, pores form during oil and gas genesis within organic matter (OM) domains. The porosity thus differs markedly from that of conventional reservoir lithologies. Here we present the first description of shale fabric and pore types in the lower Palaeozoic shales on Bornholm, Denmark. The pores have been studied using the focused ion beam scanning electron microscope (FIB-SEM) technique, which allows for high resolution SEM images of ion polished surfaces. Shale porosity is influenced by many factors including depositional fabric, mineralogical composition, diagenesis and oil and gas generation (Schieber 2013). Here we discuss some of these factors based on a study of lower Palaeozoic shale samples from the Billegrav-2 borehole on Bornholm (Fig. 1) undertaken by Henningsen & Jensen (2017). The shales are dry gas-mature (2.3% graptolite reflectance; Petersen et al. 2013) and have been extensively used as analogies for the deeply buried Palaeozoic shales elsewhere in Denmark (Schovsbo et al. 2011; Gautier et al. 2014). The Danish lower Palaeozoic shale gas play was tested by the Vendsyssel-1 well drilled in northern Jylland in 2015. Gas was discovered within a c. 70 m thick gas-mature, organicrich succession (Ferrand et al. 2016). However, the licence was subsequently relinquished, due to a too low gas content. The present study confirms a close similarity of pore development between the shales on Bornholm and in the Vendsys sel-1 indicating a high porosity within this stratigraphic level throughout the subsurface of Denmark. However, the rather different development of porosity in the different shale units presents a hitherto neglected aspect of the Palaeozoic gas play in Denmark.

scholarly journals In Situ Delineation Etch Reveals Subtle Detail in SEM Images of Ion Milled Cross Sections Enabling In-Fab 3-D Metrology and Characterization

2000 ◽  
Vol 8 (2) ◽  
pp. 36-39
Author(s):  
Clive Chandler
Keyword(s):  
Sample Preparation ◽  
Cross Sections ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Automated System ◽  
Sem Images ◽  
Difficult Time ◽  
Device Structures ◽  
Wet Etch ◽  
Conventional Sample

Control of layer thickness is critically important in the manufacture of semiconductor devices. Cross-sectioning exposes device structures for direct examination but conventional sample preparation procedures are difficult, time consuming, and grossly destructive. Cross sections created by focused ion beam (FIB) milling are easier, faster, and less destructive but have not offered the clear layer delineation provided by etching in the conventional sample preparation process. A new gas etch capability (Delineation Etch™ from FEI Company) offers results that are equivalent to conventional wet-etch preparations in a fraction of the time from a single, automated system in the fab without destroying the wafer. The new etch process also has application in milling high-aspect-ratio holes to create contacts to buried metal layers, and in deprocessing devices to reveal silicon and polysilicon structures.

scholarly journals Artifacts from manganese reduction in rock samples prepared by focused ion beam (FIB) slicing for X-ray microspectroscopy

2019 ◽  
Vol 8 (1) ◽  
pp. 97-111
Author(s):  
Dorothea S. Macholdt ◽  
Jan-David Förster ◽  
Maren Müller ◽  
Bettina Weber ◽  
Michael Kappl ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Oxidation States ◽  
X Ray ◽  
Scientific Debate ◽  
Rock Samples ◽  
Valence States ◽  
Scanning Transmission ◽  
Visualization Techniques

Abstract. The spatial distribution of transition metal valence states is of broad interest in the microanalysis of geological and environmental samples. An example is rock varnish, a natural manganese (Mn)-rich rock coating, whose genesis mechanism remains a subject of scientific debate. We conducted scanning transmission X-ray microscopy with near-edge X-ray absorption fine-structure spectroscopy (STXM-NEXAFS) measurements of the abundance and spatial distribution of different Mn oxidation states within the nano- to micrometer thick varnish crusts. Such microanalytical measurements of thin and hard rock crusts require sample preparation with minimal contamination risk. Focused ion beam (FIB) slicing was used to obtain ∼100–1000 nm thin wedge-shaped slices of the samples for STXM, using standard parameters. However, while this preparation is suitable for investigating element distributions and structures in rock samples, we observed artifactual modifications of the Mn oxidation states at the surfaces of the FIB slices. Our results suggest that the preparation causes a reduction of Mn4+ to Mn2+. We draw attention to this issue, since FIB slicing, scanning electron microscopy (SEM) imaging, and other preparation and visualization techniques operating in the kilo-electron-volt range are well-established in geosciences, but researchers are often unaware of the potential for the reduction of Mn and possibly other elements in the samples.

scholarly journals Carbonate oil and gas source rocks wettability alteration due to influence of polymer-colloidal drilling mud

2021 ◽  
pp. 17-27
Author(s):  
N. A. Skibitskaya ◽  
◽  
I. O. Burkhanova ◽  
M. N. Bolshakov ◽  
V. A. Kuzmin ◽  
...  
Keyword(s):  
Surface Properties ◽  
Oil And Gas ◽  
Pore Space ◽  
Space Structure ◽  
Source Rocks ◽  
Wettability Alteration ◽  
Drilling Mud ◽  
Rock Samples ◽  
Gas Saturation ◽  
Gas Source

Evaluation of rock wettability is an important task, since this parameter determines the distribution of water and oil in the reservoirs and their relative and phase permeability. The reliability of evaluation the wettability of rock samples depends on the drilling-in conditions during core sampling and core sample preparation methods. The investigation of the surface properties of the core from the Orenburg oil and gas condensate field showed that using of polymer-colloidal drilling mud leads to hydrophilization of the samples' surface. To obtain information on the actual wettability values of rock samples taken from wells drilled with polymer-colloidal drilling mud a method for estimating the relative (predominant) wettability of rocks based on petrophysical and lithological studies data is proposed. The authors suggest that the extraction of oil and gas source rock samples leads to irreversible changes in surface properties that cannot be restored. Keywords: selective wettability; relative wettability; predominant wettability; polymer-colloidal drilling mud; residual gas saturation; trapped gas saturation; pore space structure; extraction.

FIB Micro-Pillar Sampling of Si Devices and its 3D Observation

2003 ◽  
Author(s):  
T. Yaguchi ◽  
T. Kamino ◽  
T. Ohnishi ◽  
T. Hashimoto ◽  
K. Umemura ◽  
...  
Keyword(s):  
Focused Ion Beam ◽  
Ion Beam ◽  
Three Dimensional ◽  
Sampling Technique ◽  
Scanning Transmission Electron Microscope ◽  
Dark Field ◽  
Limiting Factor ◽  
Sem Images ◽  
Cross Sectional ◽  
Scanning Transmission

Abstract A novel technique for three-dimensional structural and elemental analyses using a dedicated focused ion beam (FIB) and scanning transmission electron microscope (STEM) has been developed. The system employs an FIB-STEM compatible sample holder with sample stage rotation mechanism. A piece of sample (micro sample) is extracted from the area to be characterized by the micro-sampling technique [1-3]. The micro sample is then transferred onto the tip of the stage (needle stage) and bonded by FIB assisted metal deposition. STEM observation of the micro sample is carried out after trimming the sample into a micro-pillar 2-5 micron squared in cross-section and 10 -15 micron in length (micro-pillar sample). High angle annular dark field (HAADF) STEM, bright field STEM and secondary electron microscopy (SEM) images are obtained at 200kV resulting in threedimensional and cross sectional representations of the microsample. The geometry of the sample and the needle stage allows observation of the sample from all directions. The specific site can be located for further FIB milling whenever it is required. Since the operator can choose materials for the needle stage, the geometry of the original specimen is not a limiting factor for quantitative energy dispersive X-ray (EDX) analysis.

FIB Micro-Surgery on Flip-Chips from the Backside

1998 ◽  
Author(s):  
Raymond Lee ◽  
Nicholas Antoniou
Keyword(s):  
Flip Chip ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Back Side ◽  
Bulk Silicon ◽  
Front Side ◽  
Large Hole ◽  
Area Of Interest ◽  
Flip Chip Packaging ◽  
Micro Surgery

Abstract The increasing use of flip-chip packaging is challenging the ability of conventional Focused Ion Beam (FIB) systems to perform even the most basic device modification and debug work. The inability to access the front side of the circuit has severely reduced the usefulness of tradhional micro-surgery. Advancements in FIB technology and its application now allow access to the circuitry from the backside through the bulk silicon. In order to overcome the problem of imaging through thick silicon, a microscope with Infra Red (IR) capability has been integrated into the FIB system. Navigation can now be achieved using the IR microscope in conjunction with CAD. The integration of a laser interferometer stage enables blind navigation and milling with sub-micron accuracy. To optimize the process, some sample preparation is recommended. Thinning the sample to a thickness of about 100 µm to 200 µm is ideal. Once the sample is thinned, it is then dated in the FIB and the area of interest is identified using the IR microscope. A large hole is milled using the FIB to remove most of the silicon covering the area of interest. At this point the application is very similar to more traditional FIB usage since there is a small amount of silicon to be removed in order to expose a node, cut it or reconnect it. The main differences from front-side applications are that the material being milled is conductive silicon (instead of dielectric) and its feature-less and therefore invisible to a scanned ion beam. In this paper we discuss in detail the method of back-side micro-surgery and its eflkcton device performance. Failure Analysis (FA) is another area that has been severely limited by flip-chip packaging. Localized thinning of the bulk silicon using FIB technology oflkrs access to diagnosing fdures in flip-chip assembled parts.

Scanning Electron Microscopy Observation of Interface Between Single Neurons and Conductive Surfaces

2016 ◽  
Vol 16 (4) ◽  
pp. 3383-3387 ◽  
Author(s):  
Toichiro Goto ◽  
Nahoko Kasai ◽  
Rick Lu ◽  
Roxana Filip ◽  
Koji Sumitomo
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Indium Tin Oxide ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Single Neurons ◽  
Sem Images ◽  
Cross Sectional ◽  
Integrated Devices ◽  
Scanning Electron

Interfaces between single neurons and conductive substrates were investigated using focused ion beam (FIB) milling and subsequent scanning electron microscopy (SEM) observation. The interfaces play an important role in controlling neuronal growth when we fabricate neuron-nanostructure integrated devices. Cross sectional images of cultivated neurons obtained with an FIB/SEM dual system show the clear affinity of the neurons for the substrates. Very few neurons attached themselves to indium tin oxide (ITO) and this repulsion yielded a wide interspace at the neuron-ITO interface. A neuron-gold interface exhibited partial adhesion. On the other hand, a neuron-titanium interface showed good adhesion and small interspaces were observed. These results are consistent with an assessment made using fluorescence microscopy. We expect the much higher spatial resolution of SEM images to provide us with more detailed information. Our study shows that the interface between a single neuron and a substrate offers useful information as regards improving surface properties and establishing neuron-nanostructure integrated devices.

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