Real-Time Method and Implementation of Head-Wave Extraction for Ultrasonic Imaging While Drilling

被引:0
|
作者
Zhang, Liangchen [1 ,2 ]
Lu, Junqiang [3 ]
Wu, Jinping [1 ,2 ]
Men, Baiyong [3 ]
Xie, Chao [3 ]
Zong, Yanbo [1 ,2 ]
Yang, Shubo [1 ,2 ]
Ni, Weining [1 ,2 ]
机构
[1] Sinopec Res Inst Petr Engn Co Ltd, Sinopec Key Lab Ultradeep Well Drilling Engn Techn, Beijing 102206, Peoples R China
[2] State Energy Key Lab Carbonate Oil & Gas, Beijing 102206, Peoples R China
[3] China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing 102249, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 12期
关键词
ultrasonic imaging; logging while drilling; circuit; head wave extraction; FPGA; logging tool; P-WAVE; DEEP; PICKING;
D O I
10.3390/app14125292
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Extracting head waves and subsequently uploading their results from the downhole to the surface system in real time could improve the real-time guidance of ultrasonic imaging logging while drilling (UILWD) for drilling operations. To realize the downhole real-time extraction of head waves in this logging, three aspects were explored in this study. First, an improved energy ratio head-wave arrival extraction algorithm based on the weighting coefficients and characteristic functions, along with an amplitude detection method relying on peak-to-peak values, was proposed. Second, an echo reception pre-processing analog circuit and a digital signal processing circuit based on FPGA were designed. A pipeline algorithm was developed in FPGA to extract the arrival time and amplitude of the head wave. Finally, software simulations, laboratory tests, and field experiments related to this method were conducted. Our results showed that the real-time head-wave extraction method demonstrated a strong anti-noise ability in real time. The maximum relative error of the arrival time was less than 5%. The relative error of the amplitude was acceptable, and 90% of this value was within 5%. Through the measurement, the time of processing a single-channel waveform by a downhole algorithm was less than 15 ms, thus meeting the requirements for the real-time processing of downholes.
引用
收藏
页数:15
相关论文
共 50 条
  • [41] Real-time optical imaging of individual microbubbles in an ultrasonic field
    Postema, M
    Bouakaz, A
    Chin, CT
    de Jong, N
    2001 IEEE ULTRASONICS SYMPOSIUM PROCEEDINGS, VOLS 1 AND 2, 2001, : 1679 - 1682
  • [42] REAL-TIME ULTRASONIC IMAGING OF SOFT-TISSUE STRUCTURES
    HEVEZI, JM
    ZERMENO, A
    DODD, GD
    BRENDEN, BB
    MARSH, LM
    PHYSICS IN MEDICINE AND BIOLOGY, 1972, 17 (06): : 875 - &
  • [43] An open high performance system for real-time ultrasonic imaging
    Nocetti, DFG
    González, JS
    Moreno, E
    Sotomayor, A
    MICROPROCESSORS AND MICROSYSTEMS, 1999, 23 (06) : 357 - 363
  • [44] Optical imaging system-based real-time image saliency extraction method
    Zhao, Jufeng
    Gao, Xiumin
    Chen, Yueting
    Feng, Huajun
    OPTICAL ENGINEERING, 2015, 54 (04)
  • [45] Real-time three dimensional ultrasonic computer imaging for the brain
    Furuhata, H
    Tokunaga, S
    STROKE, 1996, 27 (04) : 799 - 799
  • [46] REAL-TIME ULTRASONIC-IMAGING METHODOLOGY IN NONDESTRUCTIVE TESTING
    KNOLLMAN, GC
    WEAVER, JL
    HARTOG, JJ
    BELLIN, JL
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 1975, 58 (02): : 455 - 470
  • [47] Real-time ultrasonic imaging using CCD camera techniques
    Davis, WR
    Lasser, B
    NONDESTRUCTIVE CHARACTERIZATION OF MATERIALS XI, 2003, : 135 - 140
  • [48] High-performance computing in real-time ultrasonic imaging
    Nocetti, DFG
    González, JS
    Casique, MFV
    Ramirez, RO
    Hernández, EM
    ACOUSTICAL IMAGING, VOL 24, 2000, 24 : 113 - 120
  • [49] Backpropagation neural network method in data processing of ultrasonic imaging logging-while-drilling
    Zhao Jian
    Lu Jun-Qiang
    Wu Jin-Ping
    Men Bai-Yong
    Chen Hong-Zhi
    APPLIED GEOPHYSICS, 2021, 18 (02) : 159 - 170
  • [50] Backpropagation neural network method in data processing of ultrasonic imaging logging-while-drilling
    Jian Zhao
    Jun-Qiang Lu
    Jin-Ping Wu
    Bai-Yong Men
    Hong-Zhi Chen
    Applied Geophysics, 2021, 18 : 159 - 170