1887

Abstract

Summary

Safety, efficiency, scalability repeatability and data quality continue to drive advancements in Ocean Bottom Node (OBN) technology. Nodes are differentiated by operating depth and method of deployment and retrieval. Deepwater nodes are large, delivered to the seafloor with a high-speed loader, and subsequently transferred to a remotely operated vehicle (ROV) for deployment on a pre-planned grid designed to meet the survey's imaging objectives. In shallow water, smaller nodes are deployed to the seafloor and retrieved using an acoustically monitored passive rope.

The demand for larger, exploration style OBN surveys and the need for deepwater reservoir surveillance has led to the development of two new OBN designs. ZXPLR is a hybrid nodal system capable of dual mode deployment by passive rope in shallow water or by remotely operated vehicle in deep water. In either case, the new system improves operational efficiency, safety and flexibility while maintaining accessibility and repeatability in shallow or deep water. ZXPLR's new deployment methods combined with technologies such as blended source acquisition will allow for exploration scale OBN surveys in deep or shallow water.

ZLoF is a new type of node that extends proven OBN technology to semi-permanent reservoir monitoring in deep water (depths>500 m). Semi-permanent means the nodes are deployed once and then multiple surveys are acquired over an extended period of time. The enabling technology is a proprietary high speed underwater optical communications link, whereby, data download is performed in situ on the seafloor.

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/content/papers/10.3997/2214-4609.201800624
2018-05-14
2024-03-28
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References

  1. Hays, D., Thompson, J., and Morris, M.
    , [2016] A new method of semi-permanent reservoir monitoring in Deep Water using ocean bottom nodes. Offshore Technology Conference Abstracts 2016 OTC-26933-MS
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  2. Van Gestel, J., Roberts, M., Davis, S. and Ariston, p.
    [2013] Atlantis ocean bottom nodes time-lapse observations. SEG Technical Program Expanded Abstracts 2013, 4954–4959
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