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Record W2089476269 · doi:10.4043/23965-ms

Hydrate Prevention in Subsea Oil Production Dead-Legs

2013· article· en· W2089476269 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOffshore Technology Conference · 2013
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsHusky Energy (Canada)Memorial University of Newfoundland
FundersMitacs
KeywordsSubseaPetroleum engineeringComputational fluid dynamicsFlow (mathematics)Hydraulic fluidMechanicsFlow assuranceHydrateThermalEnvironmental scienceDead zoneMultiphase flowMaterials scienceFlow conditionsClathrate hydrateBubbleChemistryGeologyHydraulic machineryGeotechnical engineeringMechanical engineeringEngineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract A study was conducted to better understand the hydraulic and thermal behaviour of dead-legs within a stacked spool arrangement designed to produce two well streams from a single manifold. The study included scenarios under different rigid spool orientations and active line flow conditions. The ultimate goal of the study was to optimize inhibitor injection procedures with respect to loss of inhibitor and contamination of the production fluids. A Computational Fluid Dynamics (CFD) technique was employed to simulate the flow and thermal conditions within the flow lines and dead-legs. The results of the simulations were validated with two sets of experiments and in two different scales (sizes). The findings of the study suggest that the thermal and/or hydraulic status of the dead-legs during long shut-in periods pose little risk of hydrate formation. Introduction A dead-leg is defined as an inactive portion of the pipe where the flow is stagnant or has very low velocity. This inactive pipe is normally connected to an active pipe that carries the main flowing stream. Due to the low or stagnant flow created in dead-legs, there is a risk of cool-down and hydrate formation. The stagnant conditions within the dead-legs could also promote corrosion. The formation of hydrates is a well known phenomenon in the oil and gas production and processing systems. Hydrates can form under low temperature and high pressure when water is present in contact with gaseous or live crude oil and light liquid hydrocarbons. The fluids present in the well-stream contain a certain amount of gas which is saturated with vaporized water. Free produced or condensed water can collect in the low-points of the pipeline including pipe segments within dead-legs. Hydrates can be formed as a solid block when the line is left inactive and can potentially plug the pipeline. When hydrate formation happens, the hydrate plug in the pipeline may be either removed by depressurization or injection of inhibitor. By depressurizing one or even two sides of the plug, the hydrate plug starts to melt and can potentially move with high velocity, which could cause severe damage to subsea components. The formation of hydrates in the rigid spools connecting the subsea trees to the main subsea production manifolds could result in complex consequences. The manifold-subsea tree interconnecting spool is connected to the manifold from one side and can be relatively easily depressurized; however the tree side of the spool cannot be depressurized readily and may require costly subsea intervention and an extended loss of production. Addition of hydrate inhibitor will reduce the melting temperature and reduce the thermodynamic potential for hydrate formation. Flushing dead-legs with inhibitors such as methanol can protect them from hydrate formation during shut-in periods.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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