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Abstract

Summary

In O&G industry, DAS and DTS systems generate large volumes of data continuously. The data rates can exceed 10 MB per second, leading to over 1 TB of data per day per well. A DAS installation for near-surface monitoring could produce terabytes of data daily. Handling and storing this massive amount of data at scale can be a challenge, particularly for remote locations where infrastructure is limited. Once the data is acquired, the need for having data quality check, data processing, and data analysis in near real-time pose computational challenges that often requires high-performance computing resources.

In this abstract, we will share a scalable solution that provides a secure, convenient, efficient, and cost-effective way to store, retrieve, share, and analyze both unstructured DAS/DTS data and structured processed data.

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/content/papers/10.3997/2214-4609.202475010
2024-08-14
2026-02-11
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References

  1. Mellors, R. and Trabant, C. and the DAS RCN Data Management Working Group: DAS Data Management Challenges and Needs, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6573, https://doi.org/10.5194/egusphere-egu22-6573, 2022.
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