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Record W2072533777 · doi:10.4043/19957-ms

Marine UXO (UneXploded Ordinance) Identification and Avoidance for a Shallow Water Pipeline Route

2009· article· en· W2072533777 on OpenAlexaff
Sean Halpin, Martin L. Morrison

Bibliographic record

VenueOffshore Technology Conference · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsIntecsea (Canada)
Fundersnot available
KeywordsUnexploded ordnanceSeabedSubmarine pipelinePipeline transportRemote sensingPipeline (software)Environmental scienceMagnetometerGeologyEngineeringOceanographyEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract The oil and gas industry has long dealt with the challenge of UnExploded Ordnance (UXO) in terrestrial and marine environments. As the pace of offshore development continues to accelerate and as greenfield areas become fewer we are seeing expansion into areas that have experienced modern warfare. Modern munitions, unlike pre Cold War ordnance, are frequently comprised of non-ferrous materials, including non-ferrous (hence non-magnetic) metals such as aluminum, exotic alloys and uranium, plastics, and carbon fiber. Passive magnetics, normally used during conventional surveys, are unable to detect non-ferrous UXO and other commercially viable technologies must be explored for detection and characterization. This paper addresses the commercial seabed and subseabed detection and location mapping of non-ferrous metallic UXO through the application of electromagnetic induction (EMI or EM) technology for shallow water marine pipelines. Introduction: Conventional pipeline engineering surveys collect high-density, high-resolution information to characterize the seabed and sub-seabed environment. Typical survey goals include: establish seafloor morphology, establish the seabed and subseabed soil properties and structure, and detect all objects that may prove hazardous to pipeline installation and operation. Survey data are collected by a variety of sensors: multibeam and sidescan sonars, magnetometers and subbottom profilers. In environments where UXO may be present, these sensors are normally sufficient to assess possible target density. However, in marine areas that have been subject to modern conflict, the presence of non-ferrous UXO, may go undetected using conventional survey technology and with the results drastically underestimating the number of potential UXO. Shallow and ultra-shallow (less than 20m) marine environments present unique survey and pipeline installation challenges. Environmental loading severity typically increases as water depth decreases due to the impact of wave energy on the pipeline and surrounding seafloor. Fishing pressure and the potential for interference from shipping traffic (e.g. anchors and dropped objects) tends to be considerably more intense in shallow water than in deep water. In northern latitudes, the formation, presence and movement of ice may contribute a significant loading factor. These environmental concerns must be addressed during concept development (e.g. requirements for pipeline protection) and survey design. Potential UXO in shallow water must be given extra attention as there is a chance that the effects of on-bottom detonation may reach the ocean surface, possibly injuring or killing personnel and damaging assets. Given the extreme severity of the consequences of shallow water on-bottom detonation, every effort must be made to locate and effectively remediate the risk of UXO while keeping the cost of specialist surveys to a manageable level. The successful completion of a UXO survey required rigid adherence to a process (Figure 1) including desktop study of potential UXO in the development area, design and testing of suitable survey systems, careful well documented field operations and then study of the data by persons experienced in the identification of munitions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.250
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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