Thermal Effect on Formation Stability Due to Heterogeneity

2021 ◽  
Author(s):  
Sameeh Batarseh ◽  
Damian San Roman Alerigi ◽  
Abdullah Al Harith ◽  
Wisam Assiri
Keyword(s):  
Machine Learning ◽  
Statistical Analysis ◽  
High Speed ◽  
Advanced Characterization ◽  
Heat Propagation ◽  
Thermal Recovery ◽  
Heat Sources ◽  
X Ray ◽  
Rock Heterogeneity ◽  
Micro Cracks

Abstract This study evaluates physical and chemical changes induced by high thermal gradients on the formation and their impact to the stability. The heat sources that effect the formation’s stability are varied, including drilling (due to drilling bit friction), perforation, electromagnetic heating (laser or microwave), and thermal recovery or stimulation (steam, resistive heating, combustion, microwave, etc.). This study uses an integrated approach to characterize rock heterogeneity and mapping heat propagation from different heat sources. The information obtained from the study is vital to accurately design and enhance well completion and stimulation This is an integrated analysis approach combining different advanced characterization and visualization techniques to map heat propagation in the formation. Advanced statistical analysis is also used to determine the key parameters and build fundamental prediction algorithms. Characterization on the samples was performed before, during, and after the exposure to thermal sources; it comprised thin-section, high speed infrared thermography (IR), differential thermal analysis and thermogravimetric analyzer (DTA/TGA), scanning electron microscope (SEM), X-ray diffraction (XRD), X-ray fluorescence (XRF), uniaxial stress, and autoscan (provide hardness, composition, velocity, and spectral absorption). The results are integrated, and machine learning is used to derive a predictive algorithm of heat propagation and mapping in the formation with reference to the key formation variables and heterogeneity distribution. Rock heterogeneity affects the rate and patterns of heat propagation into the formation. Within the rock sample, minerals, laminations, and cementations lead to a heterogeneous, and sometimes anisotropic, distribution of thermal properties (thermal conductivity, heat capacity, diffusivity, etc.). These properties are also affected by the rock structure (porosity, micro-cracks, and fractures) and saturation distribution. The results showed the impact of heat on the mechanical properties of the rocks are due to clays dehydration, mineral dissociations, and micro cracks. High speed thermal imaging provides a unique visualization of heat propagation in heterogeneous rocks. Statistical analysis identified key parameters and their impact on thermal propagation; the output was used to build a machine learning algorithm to predict heat distributions in core samples and near-wellbore. Characterizing rock properties and understanding how heterogeneity modifies heat propagation in rocks enables the design of optimal completion and stimulation strategies. This paper discusses how advanced characterization and analysis, combined with novel algorithms, can improve this understanding, and unleash innovation and optimization. The data and information gathered are critical to develop numerical models for field-scale applications.

scholarly journals Laser processing quality monitoring by combining acoustic emission and machine learning: a high-speed X-ray imaging approach

Procedia CIRP ◽  
2018 ◽  
Vol 74 ◽  
pp. 654-658 ◽  
Author(s):  
K. Wasmer ◽  
T. Le-Quang ◽  
B. Meylan ◽  
F. Vakili-Farahani ◽  
M.P. Olbinado ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acoustic Emission ◽  
Laser Processing ◽  
High Speed ◽  
Quality Monitoring ◽  
Processing Quality ◽  
X Ray ◽  
X Ray Imaging ◽  
Imaging Approach

scholarly journals LLAMA: a robust and scalable machine learning pipeline for analysis of large scale 4D microscopy data: analysis of cell ruffles and filopodia

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
James G. Lefevre ◽  
Yvette W. H. Koh ◽  
Adam A. Wall ◽  
Nicholas D. Condon ◽  
Jennifer L. Stow ◽  
...  
Keyword(s):  
Machine Learning ◽  
Statistical Analysis ◽  
High Speed ◽  
High Performance ◽  
Large Scale ◽  
Immune Surveillance ◽  
Complex Surface ◽  
Semantic Segmentation ◽  
Systematic Analysis ◽  
4D Microscopy

Abstract Background With recent advances in microscopy, recordings of cell behaviour can result in terabyte-size datasets. The lattice light sheet microscope (LLSM) images cells at high speed and high 3D resolution, accumulating data at 100 frames/second over hours, presenting a major challenge for interrogating these datasets. The surfaces of vertebrate cells can rapidly deform to create projections that interact with the microenvironment. Such surface projections include spike-like filopodia and wave-like ruffles on the surface of macrophages as they engage in immune surveillance. LLSM imaging has provided new insights into the complex surface behaviours of immune cells, including revealing new types of ruffles. However, full use of these data requires systematic and quantitative analysis of thousands of projections over hundreds of time steps, and an effective system for analysis of individual structures at this scale requires efficient and robust methods with minimal user intervention. Results We present LLAMA, a platform to enable systematic analysis of terabyte-scale 4D microscopy datasets. We use a machine learning method for semantic segmentation, followed by a robust and configurable object separation and tracking algorithm, generating detailed object level statistics. Our system is designed to run on high-performance computing to achieve high throughput, with outputs suitable for visualisation and statistical analysis. Advanced visualisation is a key element of LLAMA: we provide a specialised tool which supports interactive quality control, optimisation, and output visualisation processes to complement the processing pipeline. LLAMA is demonstrated in an analysis of macrophage surface projections, in which it is used to i) discriminate ruffles induced by lipopolysaccharide (LPS) and macrophage colony stimulating factor (CSF-1) and ii) determine the autonomy of ruffle morphologies. Conclusions LLAMA provides an effective open source tool for running a cell microscopy analysis pipeline based on semantic segmentation, object analysis and tracking. Detailed numerical and visual outputs enable effective statistical analysis, identifying distinct patterns of increased activity under the two interventions considered in our example analysis. Our system provides the capacity to screen large datasets for specific structural configurations. LLAMA identified distinct features of LPS and CSF-1 induced ruffles and it identified a continuity of behaviour between tent pole ruffling, wave-like ruffling and filopodia deployment.

Scanning x-ray fluorescence microscopy and principal component analysis

1992 ◽  
Vol 50 (2) ◽  
pp. 1752-1753
Author(s):  
Brian Cross
Keyword(s):  
Principal Component Analysis ◽  
Fluorescence Microscopy ◽  
Spatial Resolution ◽  
High Speed ◽  
Image Acquisition ◽  
Principal Component ◽  
Fluorescence Microscope ◽  
Acquisition Rate ◽  
X Ray ◽  
Speed Up

A relatively new entry, in the field of microscopy, is the Scanning X-Ray Fluorescence Microscope (SXRFM). Using this type of instrument (e.g. Kevex Omicron X-ray Microprobe), one can obtain multiple elemental x-ray images, from the analysis of materials which show heterogeneity. The SXRFM obtains images by collimating an x-ray beam (e.g. 100 μm diameter), and then scanning the sample with a high-speed x-y stage. To speed up the image acquisition, data is acquired "on-the-fly" by slew-scanning the stage along the x-axis, like a TV or SEM scan. To reduce the overhead from "fly-back," the images can be acquired by bi-directional scanning of the x-axis. This results in very little overhead with the re-positioning of the sample stage. The image acquisition rate is dominated by the x-ray acquisition rate. Therefore, the total x-ray image acquisition rate, using the SXRFM, is very comparable to an SEM. Although the x-ray spatial resolution of the SXRFM is worse than an SEM (say 100 vs. 2 μm), there are several other advantages.

PHAX-SCAN: Functional integration of a Scanning Electron Microscope and an energy-dispersive x-ray analyser

1989 ◽  
Vol 47 ◽  
pp. 56-57
Author(s):  
Marc H. Peeters ◽  
Max T. Otten
Keyword(s):  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
High Speed ◽  
High Performance ◽  
Functional Integration ◽  
Energy Dispersive ◽  
X Rays ◽  
X Ray ◽  
High Speed Analysis ◽  
Scanning Electron

Over the past decades, the combination of energy-dispersive analysis of X-rays and scanning electron microscopy has proved to be a powerful tool for fast and reliable elemental characterization of a large variety of specimens. The technique has evolved rapidly from a purely qualitative characterization method to a reliable quantitative way of analysis. In the last 5 years, an increasing need for automation is observed, whereby energy-dispersive analysers control the beam and stage movement of the scanning electron microscope in order to collect digital X-ray images and perform unattended point analysis over multiple locations.The Philips High-speed Analysis of X-rays system (PHAX-Scan) makes use of the high performance dual-processor structure of the EDAX PV9900 analyser and the databus structure of the Philips series 500 scanning electron microscope to provide a highly automated, user-friendly and extremely fast microanalysis system. The software that runs on the hardware described above was specifically designed to provide the ultimate attainable speed on the system.

Utilisation of High-Energy Heat Sources in Magnesium Alloy Surface Layer Treatment

2013 ◽  
Vol 58 (2) ◽  
pp. 619-624 ◽  
Author(s):  
M. Szafarska ◽  
J. Iwaszko ◽  
K. Kudła ◽  
I. Łegowik
Keyword(s):  
Surface Layer ◽  
Magnesium Alloy ◽  
Physicochemical Properties ◽  
Treatment Effectiveness ◽  
High Energy ◽  
Alloy Surface ◽  
Heat Sources ◽  
X Ray ◽  
Additional Equipment ◽  
Alloy Surface Layer

The main aim of the study was the evaluation of magnesium alloy surface treatment effectiveness using high-energy heat sources, i.e. a Yb-YAG Disk Laser and the GTAW method. The AZ91 and AM60 commercial magnesium alloys were subject to surface layer modification. Because of the physicochemical properties of the materials studied in case of the GTAW method, it was necessary to provide the welding stand with additional equipment. A novel two-torch set with torches operating in tandem was developed within the experiment. The effectiveness of specimen remelting using a laser and the GTAW method was verified based on macro- and microscopic examinations as well as in X-ray phase analysis and hardness measurements. In addition, the remelting parameters were optimised. The proposed treatment methodology enabled the achieving of the intended result and effective modification of a magnesium alloy surface layer.

Growth Mechanisms of Faceted Al 3Fe Intermetallic Revealed by High-Speed Synchrotron X-Ray Quantification

2020 ◽  
Author(s):  
Zihan Song ◽  
Oxana Magdysyuk ◽  
Lei Tang ◽  
Tay Sparks ◽  
Biao Cai
Keyword(s):  
High Speed ◽  
Growth Mechanisms ◽  
X Ray

scholarly journals X-ray Determination of Compressive Residual Stresses in Spring Steel Generated by High-Speed Water Quenching

Materials ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1154
Author(s):  
Diego E. Lozano ◽  
George E. Totten ◽  
Yaneth Bedolla-Gil ◽  
Martha Guerrero-Mata ◽  
Marcel Carpio ◽  
...  
Keyword(s):  
Heat Treatment ◽  
Residual Stresses ◽  
High Speed ◽  
Spring Steel ◽  
X Ray Diffraction ◽  
Laboratory Equipment ◽  
X Ray ◽  
Water Chamber ◽  
Hardened Case ◽  
Compressive Residual Stresses

Automotive components manufacturers use the 5160 steel in leaf and coil springs. The industrial heat treatment process consists in austenitizing followed by the oil quenching and tempering process. Typically, compressive residual stresses are induced by shot peening on the surface of automotive springs to bestow compressive residual stresses that improve the fatigue resistance and increase the service life of the parts after heat treatment. In this work, a high-speed quenching was used to achieve compressive residual stresses on the surface of AISI/SAE 5160 steel samples by producing high thermal gradients and interrupting the cooling in order to generate a case-core microstructure. A special laboratory equipment was designed and built, which uses water as the quenching media in a high-speed water chamber. The severity of the cooling was characterized with embedded thermocouples to obtain the cooling curves at different depths from the surface. Samples were cooled for various times to produce different hardened case depths. The microstructure of specimens was observed with a scanning electron microscope (SEM). X-ray diffraction (XRD) was used to estimate the magnitude of residual stresses on the surface of the specimens. Compressive residual stresses at the surface and sub-surface of about −700 MPa were obtained.

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