Seafloor seismic acquisition using autonomous underwater vehicles

被引:2
|
作者
Tsingas, Constantinos [1 ]
Brizard, Thierry [2 ]
Al Muhaidib, Abdulaziz [1 ]
机构
[1] Saudi Aramco, EXPEC Adv Res Ctr, Dhahran, Saudi Arabia
[2] Seabed GeoSolut, Houston, TX USA
关键词
Automation; Robotics; Autonomous Underwater Vehicles; Acoustic Positioning;
D O I
10.1111/1365-2478.12670
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Although narrow-azimuth towed-streamer data provide good image quality for structural interpretation, it is generally accepted that for wide-azimuth marine surveys seabed receivers deliver superior seismic reflection measurements and seismically derived reservoir attributes. However, seabed surveys are not widely used due to the higher acquisition costs when compared to streamer acquisition. In recent years, there have been significant engineering efforts to automate receiver deployment and retrieval in order to minimize the cost differential and conduct cost-efficient seabed receiver seismic surveys. These engineering efforts include industrially engineered nodes, nodes on a rope deployment schemes and even robotic nodes, which swim to and from the deployment location. This move to automation is inevitable, leading to robotization of seismic data acquisition for exploration and development activities in the oil and gas industry. We are developing a robotic-based technology, which utilizes autonomous underwater vehicles as seismic sensors without the need of using a remotely operated vehicle for deployment and retrieval. In this paper, we describe the autonomous underwater vehicle evolution throughout the project years from initial heavy and bulky nodes to fully autonomous light and flexible underwater receivers. Results obtained from two field pilot tests using different generations of autonomous underwater vehicles indicate that the seismic coupling, and navigation based on underwater acoustics are very reliable and robust.
引用
收藏
页码:1557 / 1570
页数:14
相关论文
共 50 条
  • [1] Cooperative Underwater Mission: Offshore Seismic Data Acquisition Using Multiple Autonomous Underwater Vehicles
    Essaouari, Youssef
    Turetta, Alessio
    [J]. 2016 IEEE/OES AUTONOMOUS UNDERWATER VEHICLES (AUV), 2016, : 435 - 438
  • [2] Toward Wide Seafloor Surveys Using Multiple Autonomous Underwater Vehicles
    Matsuda, Takumi
    Maki, Toshihiro
    Sakamaki, Takashi
    Ura, Tamaki
    [J]. 2013 IEEE INTERNATIONAL UNDERWATER TECHNOLOGY SYMPOSIUM (UT), 2013,
  • [3] Landing method of autonomous underwater vehicles for seafloor surveying
    Matsuda, Takumi
    Takizawa, Ryota
    Sakamaki, Takashi
    Maki, Toshihiro
    [J]. APPLIED OCEAN RESEARCH, 2020, 101
  • [4] Landing method of autonomous underwater vehicles for seafloor surveying
    Matsuda, Takumi
    Takizawa, Ryota
    Sakamaki, Takashi
    Maki, Toshihiro
    [J]. Applied Ocean Research, 2020, 101
  • [5] Seafloor Cable Based Navigation and Monitoring with Autonomous Underwater Vehicles
    Littlefield, Robin H.
    Soenen, Karen
    Packard, Greg
    Kaeli, Jeff
    [J]. OCEANS 2019 MTS/IEEE SEATTLE, 2019,
  • [6] State Estimation of Multiple Autonomous Underwater Vehicles for Wide Area Survey of Seafloor
    Matsuda, Takumi
    Maki, Toshihiro
    Sakamaki, Takashi
    Ura, Tamaki
    [J]. 2013 MTS/IEEE OCEANS - BERGEN, 2013,
  • [7] A Path Planning Strategy for Data Acquisition Task using Multiple Autonomous Underwater Vehicles
    Wang Zhuo
    Jiang Longjie
    Guo Hongmei
    Feng Xiaoning
    [J]. OCEANS 2016 - SHANGHAI, 2016,
  • [8] Underwater pipeline and cable inspection using autonomous underwater vehicles
    Jacobi, Marco
    Karimanzira, Divas
    [J]. 2013 MTS/IEEE OCEANS - BERGEN, 2013,
  • [9] Autonomous underwater vehicles
    Gracanin, D
    Valavanis, KP
    [J]. IEEE ROBOTICS & AUTOMATION MAGAZINE, 1999, 6 (02) : 4 - +
  • [10] Mapping of Seafloor Gravity Anomalies by Underwater Gravity Measurement System Using Autonomous Underwater Vehicle for Exploration of Seafloor Deposits
    Shinohara, Masanao
    Ishihara, Takemi
    Araya, Akito
    Yamada, Tomoaki
    Fujimoto, Hiromi
    Mochizuk, Masashi
    Uehirai, Kenji
    Kanazawa, Toshihiko
    Omika, Shinobu
    Tsukioka, Satoshi
    [J]. OCEANS 2017 - ANCHORAGE, 2017,