From Qualitative to Quantitative – How Visual Data Analytics has Transformed Downhole Video Diagnostic Services

T. Tymons, Glyn Roberts, Christopher Scott
{"title":"From Qualitative to Quantitative – How Visual Data Analytics has Transformed Downhole Video Diagnostic Services","authors":"T. Tymons, Glyn Roberts, Christopher Scott","doi":"10.2118/195797-MS","DOIUrl":null,"url":null,"abstract":"\n Video images have traditionally provided intuitive visual analysis in a wide range of wellbore diagnostic situations. Step changes in computer vision techniques and image processing have led to the ability to make measurements from images (visual analytics). This paper demonstrates several applications where the application of this new data analytics source, combined with state-of-the-art acquisition technology, have further improved understanding of complex well issues while reducing operational time, risk and cost. Examples include hydraulic fracturing, well integrity, erosion, restrictions and leaks.\n The paper will describe the methods and process of this visual analytics technique through discussion of the three main work flow stages from data acquisition to final analytical product, including the innovative developments in sensor, system and computer vision applications that support each step:Acquisition of full circumferential, depth-synchronized video data of the wellbore. An array of four orthogonally positioned cameras, pointing directly at the pipe wall, concurrently record overlapping images, enabling a continuous full-well video dataset to be obtained.The four depth-matched video streams are synchronized and \"stitched\" together through the application of computer vision algorithms to provide a continuous 360° map of the wellbore with submillimeter pixel density.Calibration and measurement of the acquired images before new and unique diagnostic enhancing data analysis methods are applied.\n The paper will provide real-world examples, presented as case studies, for applications including well integrity evaluation, screen condition assessment, and analysis of perforations. Each case study will demonstrate how visual data analytics used to quantify downhole features, combined with the ability to capture a complete, high definition view of the pipe wall, provides detailed and highly intuitive information that leads to an enhanced understanding of the well and the factors affecting its performance.\n We will demonstrate that the application of this visual analytic method, together with the latest generation imaging system, exceeds the limits of conventional logging technologies for multiple industry challenges, such as:Hydraulic fracturing: confirmation and measurement of uniformity of proppant placement to cluster-level and perforation-levelWell integrity: identify corrosion or erosion events, assess their severity and quantify changes with respect to timeWellbore restrictions: understanding of obstructions and their root cause, time-lapse quantification of their extent and progress made with their removal.\n The paper will demonstrate that data analytics when applied to images from the latest generation of downhole video imaging systems has enabled the development of new diagnostics methods that provide unique insight on high value operational issues. This step change in information empowers decision-making leading to improved economics and reduced operational risk.","PeriodicalId":113290,"journal":{"name":"Day 2 Wed, September 04, 2019","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Wed, September 04, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/195797-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Video images have traditionally provided intuitive visual analysis in a wide range of wellbore diagnostic situations. Step changes in computer vision techniques and image processing have led to the ability to make measurements from images (visual analytics). This paper demonstrates several applications where the application of this new data analytics source, combined with state-of-the-art acquisition technology, have further improved understanding of complex well issues while reducing operational time, risk and cost. Examples include hydraulic fracturing, well integrity, erosion, restrictions and leaks. The paper will describe the methods and process of this visual analytics technique through discussion of the three main work flow stages from data acquisition to final analytical product, including the innovative developments in sensor, system and computer vision applications that support each step:Acquisition of full circumferential, depth-synchronized video data of the wellbore. An array of four orthogonally positioned cameras, pointing directly at the pipe wall, concurrently record overlapping images, enabling a continuous full-well video dataset to be obtained.The four depth-matched video streams are synchronized and "stitched" together through the application of computer vision algorithms to provide a continuous 360° map of the wellbore with submillimeter pixel density.Calibration and measurement of the acquired images before new and unique diagnostic enhancing data analysis methods are applied. The paper will provide real-world examples, presented as case studies, for applications including well integrity evaluation, screen condition assessment, and analysis of perforations. Each case study will demonstrate how visual data analytics used to quantify downhole features, combined with the ability to capture a complete, high definition view of the pipe wall, provides detailed and highly intuitive information that leads to an enhanced understanding of the well and the factors affecting its performance. We will demonstrate that the application of this visual analytic method, together with the latest generation imaging system, exceeds the limits of conventional logging technologies for multiple industry challenges, such as:Hydraulic fracturing: confirmation and measurement of uniformity of proppant placement to cluster-level and perforation-levelWell integrity: identify corrosion or erosion events, assess their severity and quantify changes with respect to timeWellbore restrictions: understanding of obstructions and their root cause, time-lapse quantification of their extent and progress made with their removal. The paper will demonstrate that data analytics when applied to images from the latest generation of downhole video imaging systems has enabled the development of new diagnostics methods that provide unique insight on high value operational issues. This step change in information empowers decision-making leading to improved economics and reduced operational risk.
从定性到定量——可视化数据分析如何改变井下视频诊断服务
传统上,视频图像在广泛的井筒诊断情况下提供了直观的视觉分析。计算机视觉技术和图像处理的阶段性变化导致了从图像进行测量的能力(视觉分析)。本文展示了几种应用,在这些应用中,这种新的数据分析源与最先进的采集技术相结合,进一步提高了对复杂井问题的理解,同时减少了操作时间、风险和成本。例如水力压裂、井完整性、侵蚀、限制和泄漏。本文将通过讨论从数据采集到最终分析产品的三个主要工作流程阶段来描述这种可视化分析技术的方法和过程,包括支持每个步骤的传感器、系统和计算机视觉应用的创新发展:获取井筒的全周向、深度同步视频数据。四个垂直定位的摄像机阵列,直接指向管壁,同时记录重叠图像,从而获得连续的全井视频数据集。通过应用计算机视觉算法,将四个深度匹配的视频流同步并“拼接”在一起,以亚毫米像素密度提供连续的360°井筒图。在应用新的和独特的诊断增强数据分析方法之前,对获取的图像进行校准和测量。本文将提供实际案例,作为案例研究,用于井完整性评估、筛管状态评估和射孔分析等应用。每个案例研究都将展示如何使用可视化数据分析来量化井下特征,并结合捕获管壁完整、高清视图的能力,提供详细且高度直观的信息,从而增强对井及其性能影响因素的理解。我们将证明,这种可视化分析方法与最新一代成像系统的应用,超越了传统测井技术的极限,可以应对多种行业挑战,例如:水力压裂;确认和测量支撑剂在簇级和射孔级的均匀性;识别腐蚀或侵蚀事件,评估其严重程度,并量化井筒限制时间的变化;了解障碍及其根本原因,对障碍的程度和消除障碍的进展进行延时量化。本文将证明,将数据分析应用于最新一代井下视频成像系统的图像,可以开发出新的诊断方法,为高价值的作业问题提供独特的见解。信息的这一步骤变化增强了决策能力,从而提高了经济效益,降低了运营风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信