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Attributing Sensor Deviations to Degradation, Weather, or Attack in Oilfield Digital Twins: A Simulation Study of Probabilistic Attribution and Cost-Based Decisions — arXiv:2609.31973

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.31973
License (as archived): CC0-1.0
Archived: 2026-10-07T20:49:04.765Z
SHA-256 of the archived text: d04034caed37569773cd45f892b701fdace783911c0158dce10c4e5233a333e7
Stable URL of this page: https://metraipolis.com/documento/dc_fa5fdecff547

How to cite

Attributing Sensor Deviations to Degradation, Weather, or Attack in Oilfield Digital Twins: A Simulation Study of Probabilistic Attribution and Cost-Based Decisions — arXiv:2609.31973 — arXiv (en), https://arxiv.org/abs/2609.31973 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_fa5fdecff547 (Metraipolis archive dc_fa5fdecff547, sha256 d04034caed37569773cd45f892b701fdace783911c0158dce10c4e5233a333e7)

BibTeX

@misc{dcfa5fdecff547,
  title = {Attributing Sensor Deviations to Degradation, Weather, or Attack in Oilfield Digital Twins: A Simulation Study of Probabilistic Attribution and Cost-Based Decisions — arXiv:2609.31973},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.31973},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_fa5fdecff547; sha256 d04034caed37569773cd45f892b701fdace783911c0158dce10c4e5233a333e7},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.31973. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

When an oilfield digital twin disagrees with its instruments, the operator must decide whether the cause is hardware degradation, harsh-weather effects, or malicious data manipulation. Existing digital-twin work appears to treat these causes separately: sensor-validation architectures target faults, and attack-focused twins have been evaluated on water-sector testbeds. We study joint cause attribution on a simulated four-well wellpad with 15 coupled instruments, legitimate operating transients, and weather. A physics-informed twin, identified from normal data only, produces analytical-redundancy residuals; windowed features feed a gradient-boosted classifier whose posterior drives an alarm gate with a fixed false-alarm rate and a cost-based decision rule that may defer to an analyst. On three independently generated sites, the classifier reaches macro-F1 of 0.818 on windows where the injected deviation is observable (0.723 when latent post-onset windows are included at the primary site). The physics twin accounts for essentially all of this: removing the data-driven twin changes macro-F1 by less than 0.01, whereas removing all twins drops it to about 0.58. Attacks are detected quickly (median 1.7 h) but attributed correctly at alarm time only 42% of the time, rising to 73% six hours later. A cost-aware policy that defers ambiguous cases had the lowest expected cost among all policies in every one of 144 cost and prior settings tested, sometimes by a small margin; the result depends on illustrative costs and on analysts resolving deferred cases. A twin-aware attacker was detected in 45% of episodes yet almost never attributed to attack. These results are conditional on the simulator's generative assumptions and have not been validated on field data.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-09-30 in eess.SY).
Categorie arXiv: Cryptography and Security (cs.CR) ; Systems and Control (eess.SY).
Pagina del lavoro: https://arxiv.org/abs/2609.31973 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T20:07:11.942Z dalla pagina https://arxiv.org/catchup/eess.SY/2026-09-30?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).