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Abstract

Summary

Master Target Lists (MTLs) are critical in offshore and subsea operations, serving as a consolidated view of all identified anomalies or points of interest detected across various survey methods. To avoid the manual labour, and unsystematic human errors often related to this, a Master Target List approach has been developed, which provides a centralized, accurate, and repeatable method to aggregate, correlate, and manage targets derived from multiple geophysical datasets. The abstract describes the background, development approach and core functionalities of the automated master target list approach. The approach as it is today has allready a lot of benefits, but there is still room for improvement, as a more in-depth evaluation & recognition of the targets. The end-goal is to be able to create those listings in near-real-time, directly or indirectly coupled to the acquisition system.

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/content/papers/10.3997/2214-4609.202521171
2025-10-27
2026-01-13
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References

  1. Wahead, Raheem, Mohialden, & Hussien (2022). A Review of the Implementation of NumPy and SciPy Packages in Science and Math. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 13(3): 663.
    [Google Scholar]
  2. Shreemati, Senthilkumar, Sujithra & Praisoodi (2024). Mastering Geospatial Analysis With Python: Understanding Geopandas, GDAL, Fiona, Matplotlib, Data Integration, and GIS Tools. Ethics, Machine Learning, and Python in Geospatial Analysis, 20–149.
    [Google Scholar]
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