Zhang Zhang, Zhoumo Zeng, Xiaocen Wang, Shili Chen, Yang Liu
Acoustic logging is a vital branch of geophysical logging and is a geophysical logging method for downhole measurement of rock acoustic properties of formation profiles and evaluation of wellbore formation properties. In this paper, we propose a novel approach based on machine learning to tackle the mapping challenge from time-series data to spatial images in the field of geophysical logging, that is, using a fully connected neural network (FCNN) to reconstruct the slowness model from wellbore data. Specifically, forward modeling is to study borehole acoustic signals using finite-difference time-domain method, and generate training and test data sets. The relevant research results indicate that the inversion in borehole imaging based on FCNN approach has a good effect in terms of structure detection and interlayer information presentation, and can also recover detailed slowness information between different layers of the wellbore. And the inversion results are more consistent with the target in terms of slowness values, downhole structures, as well as geological interfaces. Besides, we also optimize the image quality by using bilateral filtering method.
{"title":"Structures Inversion and Optimization in Cased-Wells Based on Deep Learning","authors":"Zhang Zhang, Zhoumo Zeng, Xiaocen Wang, Shili Chen, Yang Liu","doi":"10.1115/qnde2022-98591","DOIUrl":"https://doi.org/10.1115/qnde2022-98591","url":null,"abstract":"\u0000 Acoustic logging is a vital branch of geophysical logging and is a geophysical logging method for downhole measurement of rock acoustic properties of formation profiles and evaluation of wellbore formation properties. In this paper, we propose a novel approach based on machine learning to tackle the mapping challenge from time-series data to spatial images in the field of geophysical logging, that is, using a fully connected neural network (FCNN) to reconstruct the slowness model from wellbore data. Specifically, forward modeling is to study borehole acoustic signals using finite-difference time-domain method, and generate training and test data sets. The relevant research results indicate that the inversion in borehole imaging based on FCNN approach has a good effect in terms of structure detection and interlayer information presentation, and can also recover detailed slowness information between different layers of the wellbore. And the inversion results are more consistent with the target in terms of slowness values, downhole structures, as well as geological interfaces. Besides, we also optimize the image quality by using bilateral filtering method.","PeriodicalId":276311,"journal":{"name":"2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"80 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131274679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guided wave ultrasound is used to monitor continuously welded rail track in a system which transmits guided wave ultrasound between alternate transmit and receive stations along the rail and triggers an alarm if the signal is not received. During field testing, a section of rail was encountered where transmission through one rail was poor. Visual inspection showed that there was considerable flank wear and numerous gauge corner cracks. These cracks, while small, occurred roughly every 5 mm over a length of a few meters so the total number of cracks would be of the order of 1000 cracks. The scattering from the numerous small cracks was investigated using the hybrid 3D finite element - semi-analytical finite element technique. A substructuring approach was used, with reduction of internal degrees of freedom, to enable the analysis of a long section of rail with numerous cracks. The numerical analysis was used to investigate the transmission coefficient of the operational mode used in the monitoring system to determine if the presence of the small cracks could cause the observed poor transmission. It was found that significant transmission loss can occur but the transmission coefficient did not decrease monotonically with increasing number of cracks. This unexpected behavior requires further investigation.
{"title":"Numerical Analysis of Guided Wave Transmission Through a Rail Containing Numerous Small Cracks","authors":"P. Loveday","doi":"10.1115/qnde2022-98277","DOIUrl":"https://doi.org/10.1115/qnde2022-98277","url":null,"abstract":"\u0000 Guided wave ultrasound is used to monitor continuously welded rail track in a system which transmits guided wave ultrasound between alternate transmit and receive stations along the rail and triggers an alarm if the signal is not received. During field testing, a section of rail was encountered where transmission through one rail was poor. Visual inspection showed that there was considerable flank wear and numerous gauge corner cracks. These cracks, while small, occurred roughly every 5 mm over a length of a few meters so the total number of cracks would be of the order of 1000 cracks. The scattering from the numerous small cracks was investigated using the hybrid 3D finite element - semi-analytical finite element technique. A substructuring approach was used, with reduction of internal degrees of freedom, to enable the analysis of a long section of rail with numerous cracks. The numerical analysis was used to investigate the transmission coefficient of the operational mode used in the monitoring system to determine if the presence of the small cracks could cause the observed poor transmission. It was found that significant transmission loss can occur but the transmission coefficient did not decrease monotonically with increasing number of cracks. This unexpected behavior requires further investigation.","PeriodicalId":276311,"journal":{"name":"2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122776992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ross McMillan, M. Tabatabaeipour, K. Tzaferis, William Jackson, Rachel S. Edwards, O. Trushkevych, C. Macleod, G. Dobie, A. Gachagan
This paper presents an update on the progress of developing a crawler-based automated non-contact ultrasonic inspection system for the evaluation of large structural assets. The system presented is a significant improvement on current robotic NDT crawlers and aims to greatly reduce the time of inspection by creating an internal feature map of the subject in a Simultaneous Localisation And Mapping (SLAM) style method instead of using a lawnmower scanning style where all areas are scanned regardless if they contain features or are featureless. This map will be generated through rapid automated path planning and scanning and will show the location of potential areas of interest, where then, the appropriate method of inspection can be used for a high detailed evaluation. Current and ongoing work presented is as follows; the use of guided waves as the sensory input of an occupancy grid map; evaluating guided wave modes to find the mode most appropriate for this system; minimum thickness estimation using machine learning; improving the transducer setup using a unidirectional transmitter.
{"title":"Crawler-Based Automated Non-Contact Ultrasonic Inspection of Large Structural Assets","authors":"Ross McMillan, M. Tabatabaeipour, K. Tzaferis, William Jackson, Rachel S. Edwards, O. Trushkevych, C. Macleod, G. Dobie, A. Gachagan","doi":"10.1115/qnde2022-97910","DOIUrl":"https://doi.org/10.1115/qnde2022-97910","url":null,"abstract":"\u0000 This paper presents an update on the progress of developing a crawler-based automated non-contact ultrasonic inspection system for the evaluation of large structural assets. The system presented is a significant improvement on current robotic NDT crawlers and aims to greatly reduce the time of inspection by creating an internal feature map of the subject in a Simultaneous Localisation And Mapping (SLAM) style method instead of using a lawnmower scanning style where all areas are scanned regardless if they contain features or are featureless. This map will be generated through rapid automated path planning and scanning and will show the location of potential areas of interest, where then, the appropriate method of inspection can be used for a high detailed evaluation. Current and ongoing work presented is as follows; the use of guided waves as the sensory input of an occupancy grid map; evaluating guided wave modes to find the mode most appropriate for this system; minimum thickness estimation using machine learning; improving the transducer setup using a unidirectional transmitter.","PeriodicalId":276311,"journal":{"name":"2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132165184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Loheshwaran Chandran, Mohamed Subair Syed Akbar Ali, Abhishek Saini, Z. Fan, P. Rajagopal
Recently there is much interest in metamaterial based super resolution imaging. Several demonstrations have been reported using sources or slits as targets for imaging. However, in the context of non-destructive evaluation, imaging of defects and discontinuities within a sample are of more interest. Such defects, unlike sources or slits, induce wave scattering which could potentially impact image generation. This paper studies the effects of wave scattering by subwavelength spaced defects in holey structured metamaterial based super resolution imaging using numerical (finite element) models. In these models, the ultrasonic waves are assumed to impinge on the defects in a normal incidence through transmission configuration, and a line-scan image at the receiver location is generated based on the captured waves past the metamaterial. The influence of defect position within the specimen sample (object plane) and the receiver location (image plane) with respect to the metamaterial on the output images are investigated. The results show that the defect-induced wave scattering processes produce intensity and spatial artefacts that have a signature on imaging. For various parametric cases, the changes in the output images are quantified and discussed in the context of metamaterial based super resolution imaging in the field of non-destructive evaluation and non-invasive diagnostics.
{"title":"A Study on the Influence of Wave Scattering in Metamaterial-Based Super-Resolution Imaging of Defects in Materials","authors":"Loheshwaran Chandran, Mohamed Subair Syed Akbar Ali, Abhishek Saini, Z. Fan, P. Rajagopal","doi":"10.1115/qnde2022-98345","DOIUrl":"https://doi.org/10.1115/qnde2022-98345","url":null,"abstract":"\u0000 Recently there is much interest in metamaterial based super resolution imaging. Several demonstrations have been reported using sources or slits as targets for imaging. However, in the context of non-destructive evaluation, imaging of defects and discontinuities within a sample are of more interest. Such defects, unlike sources or slits, induce wave scattering which could potentially impact image generation. This paper studies the effects of wave scattering by subwavelength spaced defects in holey structured metamaterial based super resolution imaging using numerical (finite element) models. In these models, the ultrasonic waves are assumed to impinge on the defects in a normal incidence through transmission configuration, and a line-scan image at the receiver location is generated based on the captured waves past the metamaterial. The influence of defect position within the specimen sample (object plane) and the receiver location (image plane) with respect to the metamaterial on the output images are investigated. The results show that the defect-induced wave scattering processes produce intensity and spatial artefacts that have a signature on imaging. For various parametric cases, the changes in the output images are quantified and discussed in the context of metamaterial based super resolution imaging in the field of non-destructive evaluation and non-invasive diagnostics.","PeriodicalId":276311,"journal":{"name":"2022 49th Annual Review of Progress in Quantitative Nondestructive Evaluation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116703078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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