MétaCan
Menu
Back to cohort
Record W1970111151 · doi:10.4043/20436-ms

Un-planned Shut-in and Deepwater Gas Hydrate Prevention

2010· article· en· W1970111151 on OpenAlexaff
Shing-Ming Chen

Bibliographic record

VenueOffshore Technology Conference · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsClathrate hydrateWellheadPetroleum engineeringHydrateNatural gas fieldShut downWell controlNatural gasGeologyEnvironmental scienceChemistryWaste managementMaterials scienceDrillingEngineeringProcess engineering

Abstract

fetched live from OpenAlex

Abstract The main objectives of this paper are to (i) investigate key factors affecting gas hydrate formation and (ii) recommend methods for preventing gas hydrate in deepwater flowing and shut-in gas wells. In this paper, key factors affecting gas hydrate formation in deepwater gas wells are discussed. Critical times when gas and water may contact each other at temperatures below the gas hydrate temperature inside the tubing during flow and shut-in periods are examined. For flowing wells, since gas hydrate formation can easily be detected by monitoring the gas rate, pressure and temperature at the wellhead, gas hydrate prevention can be planned and implemented properly if there is a need. For shut-in wells, since there is no real time data available to determine if gas hydrate formation is taking place, preparations for gas hydrate prevention should be made available at all times, especially for wells which may encounter unplanned shut-ins during the operations. In order to assist in illustrating the need for gas hydrate prevention under different circumstances, examples using hypothetical data to represent different field or well cases are presented. Also included in this paper is an example which shows results from a gas hydrate study for a deepwater shadow gas well. Introduction Gas hydrate prevention is one of the big challenges[1-6] when developing a deepwater gas field or testing a deepwater gas well in a cold seabed environment. For a deepwater gas well, when gas flows at a high rate during normal operations, no gas hydrate will form because of the warm reservoir fluid flowing through the wellbore. However, during the well start-up, restart, shut-in, or when a well is flowing at low rate, gas hydrate may form due to the low wellbore temperature if both gas and water exist in the wellbore. As the formation of gas hydrate depends on wellbore conditions and fluids inside the wellbore, it is important to understand the wellbore fluid behavior and heat transfer among fluids and all mediums inside and outside the wellbore such that the possibilities for gas hydrate formation can be predicted and its prevention can be planned. Effect of Water on Gas Hydrate Formation As gas hydrate is mainly caused by the existence of water inside the wellbore, prior to discussing the gas hydrate formation, possible water sources which may contribute to water production while producing a gas well should be identified:Water from water zone:When a gas well is being produced, water may come directly from the perforated zone that contains water or indirectly from the water zone through channeling behind casing due to poor cement bonding.Condensed water from natural gas:Unless the produced gas from the reservoir is completely dry, it is inevitable that some water vapor in the natural gas will condense out when the reservoir gas flows through tubing with temperatures that have declined from their initial values.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.215
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueOffshore Technology ConferenceSame topicMethane Hydrates and Related PhenomenaFrench-language works237,207