scholarly journals Improved dynamic imaging of multiphase flow by constrained tomographic reconstruction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Peter Winkel Rasmussen ◽  
Henning Osholm Sørensen ◽  
Stefan Bruns ◽  
Anders Bjorholm Dahl ◽  
Anders Nymark Christensen

AbstractDynamic tomography has become an important technique to study fluid flow processes in porous media. The use of laboratory X-ray tomography instruments is, however, limited by their low X-ray brilliance. The prolonged exposure times, in turn, greatly limit temporal resolution. We have developed a tomographic reconstruction algorithm that maintains high image quality, despite reducing the exposure time and the number of projections significantly. Our approach, based on the Simultaneous Iterative Reconstruction Technique, mitigates the problem of few and noisy exposures by utilising a high-quality scan of the system before the dynamic process is started. We use the high-quality scan to initialise the first time step of the dynamic reconstruction. We further constrain regions of the dynamic reconstruction with a segmentation of the static system. We test the performance of the algorithm by reconstructing the dynamics of fluid separation in a multiphase system. The algorithm is compared quantitatively and qualitatively with several other reconstruction algorithms and we show that it can maintain high image quality using only a fraction of the normally required number of projections and with a substantially larger noise level. By robustly allowing fewer projections and shorter exposure, our algorithm enables the study of faster flow processes using laboratory tomography instrumentation but it can also be used to improve the reconstruction quality of dynamic synchrotron experiments.

2020 ◽  
Vol 64 (2) ◽  
pp. 20503-1-20503-5
Author(s):  
Faiz Wali ◽  
Shenghao Wang ◽  
Ji Li ◽  
Jianheng Huang ◽  
Yaohu Lei ◽  
...  

Abstract Grating-based x-ray phase-contrast imaging has the potential to enhance image quality and provide inner structure details non-destructively. In this work, using grating-based x-ray phase-contrast imaging system and employing integrating-bucket method, the quantitative expressions of signal-to-noise ratios due to photon statistics and mechanical error are analyzed in detail. Photon statistical noise and mechanical error are the main sources affecting the image noise in x-ray grating interferometry. Integrating-bucket method is a new phase extraction method translated to x-ray grating interferometry; hence, its image quality analysis would be of great importance to get high-quality phase image. The authors’ conclusions provide an alternate method to get high-quality refraction signal using grating interferometer, and hence increases applicability of grating interferometry in preclinical and clinical usage.


2021 ◽  
Author(s):  
Khalid Labib Alsamadony ◽  
Ertugrul Umut Yildirim ◽  
Guenther Glatz ◽  
Umair bin Waheed ◽  
Sherif M. Hanafy

Abstract Computed tomography (CT) is an important tool to characterize rock samples allowing quantification of physical properties in 3D and 4D. The accuracy of a property delineated from CT data is strongly correlated with the CT image quality. In general, high-quality, lower noise CT Images mandate greater exposure times. With increasing exposure time, however, more wear is put on the X-Ray tube and longer cooldown periods are required, inevitably limiting the temporal resolution of the particular phenomena under investigation. In this work, we propose a deep convolutional neural network (DCNN) based approach to improve the quality of images collected during reduced exposure time scans. First, we convolve long exposure time images from medical CT scanner with a blur kernel to mimic the degradation caused because of reduced exposure time scanning. Subsequently, utilizing the high- and low-quality scan stacks, we train a DCNN. The trained network enables us to restore any low-quality scan for which high-quality reference is not available. Furthermore, we investigate several factors affecting the DCNN performance such as the number of training images, transfer learning strategies, and loss functions. The results indicate that the number of training images is an important factor since the predictive capability of the DCNN improves as the number of training images increases. We illustrate, however, that the requirement for a large training dataset can be reduced by exploiting transfer learning. In addition, training the DCNN on mean squared error (MSE) as a loss function outperforms both mean absolute error (MAE) and Peak signal-to-noise ratio (PSNR) loss functions with respect to image quality metrics. The presented approach enables the prediction of high-quality images from low exposure CT images. Consequently, this allows for continued scanning without the need for X-Ray tube to cool down, thereby maximizing the temporal resolution. This is of particular value for any core flood experiment seeking to capture the underlying dynamics.


2017 ◽  
Vol 23 (5) ◽  
pp. 938-944
Author(s):  
Shengkun Yao ◽  
Yunbing Zong ◽  
Jiadong Fan ◽  
Zhibin Sun ◽  
Jianhua Zhang ◽  
...  

AbstractRing artifacts are undesirable and complicate the analysis and interpretation of microstructures in synchrotron X-ray microtomography. Here, we propose a new method to improve the image quality of an object by removing the ring artifacts and investigate the efficiency of this process with tomographic images of a dried Tenebrio molitor. In this method, before the tomographic reconstruction, ring artifacts were identified and located in the sinograms as line artifacts. Then, the identified line artifacts were corrected as single point noise via image processing of the original projections. Eventually, the corresponding line artifacts were removed, resulting in reduced ring artifacts in the reconstructed tomographic images. Simulations verified the efficiency of the proposed method. This method was successfully applied for the structural analysis of the insect T. molitor, showing superior performance in reducing ring artifacts in the tomographic image without noticeable loss of structural information.


2018 ◽  
Vol 25 (5) ◽  
pp. 1450-1459 ◽  
Author(s):  
Yuqing Zhao ◽  
Mengyu Sun ◽  
Dongjiang Ji ◽  
Changhong Cong ◽  
Wenjuan Lv ◽  
...  

In-line X-ray phase-contrast computed tomography (IL-PCCT) can reveal fine inner structures for low-Z materials (e.g. biological soft tissues), and shows high potential to become clinically applicable. Typically, IL-PCCT utilizes filtered back-projection (FBP) as the standard reconstruction algorithm. However, the FBP algorithm requires a large amount of projection data, and subsequently a large radiation dose is needed to reconstruct a high-quality image, which hampers its clinical application in IL-PCCT. In this study, an iterative reconstruction algorithm for IL-PCCT was proposed by combining the simultaneous algebraic reconstruction technique (SART) with eight-neighbour forward and backward (FAB8) diffusion filtering, and the reconstruction was performed using the Shepp–Logan phantom simulation and a real synchrotron IL-PCCT experiment. The results showed that the proposed algorithm was able to produce high-quality computed tomography images from few-view projections while improving the convergence rate of the computed tomography reconstruction, indicating that the proposed algorithm is an effective method of dose reduction for IL-PCCT.


SPE Journal ◽  
2019 ◽  
Vol 25 (01) ◽  
pp. 226-241
Author(s):  
Alexander Katsevich ◽  
Michael Frenkel ◽  
Qiushi Sun ◽  
Shannon L. Eichmann ◽  
Victor Prieto

Summary Microcomputed tomography (microCT) of cores yields valuable information about rock and fluid properties at pore scale for conventional rock and at rock heterogeneity scale for unconventionals. High levels of uncorrected X-ray scatter in computed tomography (CT) data lead to strong image artifacts and erroneous Hounsfield unit (HU) values, making reconstructed images unsuitable for accurate digital rock (DR) characterization (e.g., segmentation, material decomposition, and others). MicroCT scanners do not include scatter correction techniques. To fill this gap, we developed a new methodology to measure and remove the scatter component from raw projection microCT data collected during rock core scans, and ultimately improving the image quality of scanned cores. Widely used approaches for scatter estimation, based on Monte Carlo (MC) simulations and simplified analytical models, are time-consuming and may lose accuracy when imaging complex unconventional shale cores. In this paper, we propose a more practical approach to perform scatter correction from direct scatter measurements, an approach that is based on the beam-stop array (BSA) method. The BSA method works as follows: The radiation scattered by the core sample is emitted in random directions. By placing an array of small, highly absorbing beads between the source and the core, the primary X-ray signal through the beads is blocked, but the overall object scatter signal is not affected. The observed values in the beads’ shadows on the detector are assumed to be scatter signal. Performing interpolation of the scatter signal between the shadowed by beads pixels on the detector gives an estimate of the scatter signal at every pixel on the detector. Subtracting scatter from projection data yields scatter-corrected data used for 3D CT core image reconstruction. To develop the core scatter correction methodology, we executed the following three tasks: (1) performed modeling of primary and scattered signals to optimize the BSA design (beads size and layout) and scan parameters; (2) developed and implemented an accurate scatter correction algorithm into our 3D microCT image reconstruction workflow; and (3) tested the proposed methodology using four shale core samples from the United States and the Middle East. To better assess the impact of scatter, all experiments with shale core plugs presented in this paper were conducted using source energy of 160 kVp. Our results demonstrated that in many cases, especially with higher attenuating cores, failing to correct for X-ray scatter may result in significant loss of image reconstruction accuracy. We also showed that the developed methodology allows for accurate estimation and removal of scatter from the raw (projection) CT data, enabling reconstruction of high-quality core images that are required for performing DR analysis. To assess the impact of X-ray scatter on the accuracy of DR segmentation, we compared the amount of resolved air-filled space using a stack of image slices by thresholding for the air regions. Our results showed that the amount of detected air-filled space may increase significantly when scatter correction is applied. The presented scatter correction methodology is general and can be used with any microCT scanner used by the petroleum industry to improve image quality and derive accurate HU values. This is of significant importance for quantitative characterization of highly heterogeneous rock with fine structural changes, as is the case for shale. Ultimately, this methodology should expand the operational envelope and value of microCT imaging in the exploration and production workflows.


Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.


Author(s):  
Wenbing Yun ◽  
Steve Wang ◽  
David Scott ◽  
Kenneth W. Nill ◽  
Waleed S. Haddad

Abstract A high-resolution table-sized x-ray nanotomography (XRMT) tool has been constructed that shows the promise of nondestructively imaging the internal structure of a full IC stack with a spatial resolution better than 100 nm. Such a tool can be used to detect, localize, and characterize buried defects in the IC. By collecting a set of X-ray projections through the full IC (which may include tens of micrometers of silicon substrate and several layers of Cu interconnects) and applying tomographic reconstruction algorithms to these projections, a 3D volumetric reconstruction can be obtained, and analyzed for defects using 3D visualization software. XRMT is a powerful technique that will find use in failure analysis and IC process development, and may facilitate or supplant investigations using SEM, TEM, and FIB tools, which generally require destructive sample preparation and a vacuum environment.


Author(s):  
Koji INAKA ◽  
Saori ICHIMIZU ◽  
Izumi YOSHIZAKI ◽  
Kiyohito KIHIRA ◽  
Elena G. LAVRENKO ◽  
...  

A series of space experiments aboard the International Space Station (ISS) associated with high-quality Protein Crystal Growth (PCG) in microgravity conditions can be considered as a unique and one of the best examples of fruitful collaboration between Japanese and Russian scientists and engineers in space, which includes also other ISS International Partners. X-ray diffraction is still the most powerful tool to determine the protein three dimensional structure necessary for Structure based drug design (SBDD). The major purpose of the experiment is to grow high quality protein crystals in microgravity for X-ray diffraction on Earth. Within one and a half decade, Japan and Russia have established an efficient process over PCG in space to support latest developments over drug design and structural biology. One of the keys for success of the experiment lies in how precisely pre-launch preparations are made. Japanese party provides flight equipment for crystallization and ensures the required environment to support the experiment aboard of the ISS’s Kibo module, and also mainly takes part of the experiment ground support such as protein sample characterization, purification, crystallization screening, and solution optimization for microgravity experiment. Russian party is responsible for integration of the flight items equipped with proteins and precipitants on board Russian transportation space vehicles (Soyuz or Progress), for delivery them at the ISS, transfer to Kibo module, and returning the experiments’ results back on Earth aboard Soyuz manned capsule. Due to close cooperation of the parties and solid organizational structure, samples can be launched at the ISS every half a year if the ground preparation goes smoothly. The samples are crystallized using counter diffusion method at 20 degree C for 1–2.5 months. After samples return, the crystals are carefully taken out from the capillary, and frozen for X-ray diffraction at SPring8 facility in Japan. Extensive support of researchers from both countries is also a part of this process. The paper analyses details of the PCG experiment scheme, unique and reliable technology of its execution, and contains examples of the application. Key words: International Space Station, Protein crystals, Microgravity, International collaboration.


Sign in / Sign up

Export Citation Format

Share Document