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Feasibility Analysis of Early Gas Monitoring at the Bottom of Marine Riser in Deepwater Drilling

2018· article· en· W3101552229 on OpenAlexaff
Xiangyu Wang, Zhichuan Guan, Yangyang Tian, Shiqian Xu

Bibliographic record

VenueJournal of Applied Science and Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWellheadPetroleum engineeringDrillingWellborePermeability (electromagnetism)Deepwater drillingGeologyEnvironmental scienceMarine engineeringPetrologyEngineeringChemistryMechanical engineering

Abstract

fetched live from OpenAlex

ABSTRACT Gas influx is a phenomenon which causes serious outcome, and consequently the early and accurate detection of gas influx is crucial for deepwater drilling operation security. The detection method outside marine riser (DMOMR) is widely utilized in deepwater drilling as a complement of the traditional wellhead detection method (WDM). In this study, an extended two-fluid model (TFM) is developed to describe the gas-liquid two-phase flow when gas influx occurs and to compare the advantages of the DMOMR and the WDM in marine riser. By comparing the simulation results with the measured data of a well in the Bohai Sea, China, it is demonstrated that this model provides an excellent description for the gas-liquid two-phase flow in marine riser. The tip gas position, overflow and detection time are predicted using this model, and parameters such as water depth, wellbore depth, and formation permeability and equivalent density are controlled to vary respectively. The comparisons present that the DMOMR can detect gas influx in advance than the WDM under most conditions, and the lead time of the DMOMR increases by the increasing water depth and reducing wellbore depth. Moreover, the simulation results agree that the DMOMR has a great advantage in low or medium permeability (< 300 mD) formation and lower pressure formation. With the increase of formation permeability and formation equivalent density, the advantage of the DMOMR weakens compared with the WDM.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.010
GPT teacher head0.215
Teacher spread0.206 · 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 designSimulation or modeling
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

Citations1
Published2018
Admission routes1
Has abstractyes

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