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Record W2067067407 · doi:10.2118/149477-ms

Investigation of Liquid Loading in Tight Gas Horizontal Wells with a Transient Multiphase Flow Simulator

2011· article· en· W2067067407 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.

Bibliographic record

VenueCanadian Unconventional Resources Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMultiphase flowTransient (computer programming)Petroleum engineeringSlug flowInflowMechanicsFlow (mathematics)DrillingVolumetric flow rateGeologyTwo-phase flowMaterials scienceEnvironmental scienceGeotechnical engineeringSimulationEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract Liquid loading occurs when gas production declines to a rate that is insufficient to lift the associated liquids to surface. At lower rates, gas production becomes intermittent and eventually stops entirely. However, liquid holdup in the horizontal section may impair production before loading in the production tubing becomes evident. Holdup in the horizontal section can lead to slug flow from the horizontal wellbore to the tubing and to an earlier onset of liquid loading in the tubing. This paper presents liquid holdup data from a single onshore horizontal tight gas well, obtained through video-logging. A transient multiphase flow model is then used to match the observed conditions. The results from the transient multiphase flow model were found to be consistent with the measured data acquired from the video-logging. Sensitivity analyses were performed with normalized trajectories representing toe-up, toe-down, undulating, and complex drilling profiles. Sensitivities to variations in the liquid-gas ratio and the distribution of the reservoir inflow were also investigated. The results of the transient multiphase flow modelling support the conclusion that complex trajectories are more prone to production losses caused by liquid holdup. The implications of this conclusion for trajectory optimization and tubing landing depth selection are explored. Modelling liquid holdup can lead to improvements in planning new drilling projects, mitigating the impact of liquid loading on long-term performance.

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 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 score0.013
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
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.215
Teacher spread0.181 · 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