{"title":"Sensitivity Analysis and Comparative Study for Different Detection Modes of Logging-While-Drilling Ultradeep Azimuthal Electromagnetic Tools","authors":"Yubo Hu, Guozhong Gao","doi":"10.2118/219479-pa","DOIUrl":null,"url":null,"abstract":"<p>The logging-while-drilling (LWD) ultradeep azimuthal electromagnetic tool plays a pivotal role in real-time drilling optimization operations. Established tool designs include arrays of coaxial and tilted coils that, during drilling operations, can be processed to a multicomponent magnetic induction data. These data can then be combined into different detection modes, which accentuate sensitivity to particular geological features. Leveraging the established coil design and definitions of various detection modes for an electromagnetic look-ahead (EMLA) tool, this study undertakes a comprehensive exploration of the disparities in detection performance and characterization of subsurface parameters. Through sensitivity analysis, the varying degrees of sensitivity exhibited by these detection modes concerning parameters such as subsurface formation resistivity, formation inclination, and electrical anisotropy have been investigated. The ensuing conclusions derived from an in-depth analysis are as follows: Detection Mode I exhibits remarkable prowess in delineating subsurface boundaries. Optimal exploration distances can be achieved through the judicious selection of source-receiver distances and frequencies. Detection Mode II displays heightened sensitivity to wellbore inclination and anisotropy, effectively elucidating subsurface resistivity anisotropy. This sensitivity is particularly pronounced at wellbore inclinations approaching 60°. Detection Mode III, while lacking directional capability, nonetheless furnishes fundamental insights into subsurface resistivity. Detection Mode IV demonstrates exceptional sensitivity to electrical anisotropy, particularly at higher wellbore inclinations, manifesting a conspicuous response to subsurface resistivity anisotropy. In summary, the diverse detection modes within the realm of ultradeep azimuthal electromagnetic technology each offer distinctive attributes, facilitating optimal mode selection to attain superior outcomes as per specific requisites. This research contributes significantly to an enhanced comprehension of the performance and applicability of the ultradeep azimuthal electromagnetic tool in the field of optimal drilling.</p>","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.2000,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPE Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.2118/219479-pa","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, PETROLEUM","Score":null,"Total":0}
引用次数: 0
Abstract
The logging-while-drilling (LWD) ultradeep azimuthal electromagnetic tool plays a pivotal role in real-time drilling optimization operations. Established tool designs include arrays of coaxial and tilted coils that, during drilling operations, can be processed to a multicomponent magnetic induction data. These data can then be combined into different detection modes, which accentuate sensitivity to particular geological features. Leveraging the established coil design and definitions of various detection modes for an electromagnetic look-ahead (EMLA) tool, this study undertakes a comprehensive exploration of the disparities in detection performance and characterization of subsurface parameters. Through sensitivity analysis, the varying degrees of sensitivity exhibited by these detection modes concerning parameters such as subsurface formation resistivity, formation inclination, and electrical anisotropy have been investigated. The ensuing conclusions derived from an in-depth analysis are as follows: Detection Mode I exhibits remarkable prowess in delineating subsurface boundaries. Optimal exploration distances can be achieved through the judicious selection of source-receiver distances and frequencies. Detection Mode II displays heightened sensitivity to wellbore inclination and anisotropy, effectively elucidating subsurface resistivity anisotropy. This sensitivity is particularly pronounced at wellbore inclinations approaching 60°. Detection Mode III, while lacking directional capability, nonetheless furnishes fundamental insights into subsurface resistivity. Detection Mode IV demonstrates exceptional sensitivity to electrical anisotropy, particularly at higher wellbore inclinations, manifesting a conspicuous response to subsurface resistivity anisotropy. In summary, the diverse detection modes within the realm of ultradeep azimuthal electromagnetic technology each offer distinctive attributes, facilitating optimal mode selection to attain superior outcomes as per specific requisites. This research contributes significantly to an enhanced comprehension of the performance and applicability of the ultradeep azimuthal electromagnetic tool in the field of optimal drilling.
边钻井边测井(LWD)超深方位电磁工具在实时钻井优化作业中发挥着举足轻重的作用。成熟的工具设计包括同轴和倾斜线圈阵列,在钻井作业期间,可将这些线圈处理为多分量磁感应数据。这些数据可以组合成不同的探测模式,从而提高对特定地质特征的灵敏度。本研究利用电磁前视(EMLA)工具的既定线圈设计和各种探测模式的定义,对探测性能和地下参数特征的差异进行了全面探索。通过灵敏度分析,研究了这些探测模式对地下地层电阻率、地层倾角和电各向异性等参数的不同灵敏度。深入分析得出的结论如下:探测模式 I 在划定地下边界方面表现突出。通过明智地选择信号源-接收器的距离和频率,可以达到最佳探测距离。探测模式 II 对井筒倾角和各向异性表现出更高的灵敏度,可有效阐明地下电阻率各向异性。这种灵敏度在井筒倾角接近 60° 时尤为明显。探测模式 III 虽然缺乏定向能力,但仍能提供有关地下电阻率的基本信息。探测模式 IV 对电各向异性特别敏感,尤其是在井筒倾角较大的情况下,对地下电阻率各向异性有明显的反应。总之,超深层方位电磁技术领域的各种探测模式各具特色,有利于根据具体要求选择最佳模式,以取得优异的成果。这项研究对提高对超深方位电磁工具在优化钻井领域的性能和适用性的理解大有裨益。
期刊介绍:
Covers theories and emerging concepts spanning all aspects of engineering for oil and gas exploration and production, including reservoir characterization, multiphase flow, drilling dynamics, well architecture, gas well deliverability, numerical simulation, enhanced oil recovery, CO2 sequestration, and benchmarking and performance indicators.