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Record W1974536892 · doi:10.2118/91692-ms

Benefits and Challenges Associated with CRA Injection Tubing in Corrosive Gas Wells

2004· article· en· W1974536892 on OpenAlexaff
R. xsB. Sullivan, Debra Hinson, David E. Hendrix

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2004
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsHendrix Genetics (Canada)
Fundersnot available
KeywordsWeldingMetallurgyCorrosionDrillingCrackingPetroleum engineeringMaterials scienceGeologyComposite material

Abstract

fetched live from OpenAlex

Abstract The use of chemical injection (1/4" capillary) strings has gained tremendous popularity in the oilfield during the last few years. Application of these duplex stainless steel strings are now routinely used not only for corrosion chemical injection but also for injecting fresh water where downhole salt precipitation is present, as well as injection of foamer to address water loading issues. This paper describes an exhaustive investigation into the repetitive failure of these orbital welded duplex stainless steel strings due to environmental cracking in Anadarko's prolific Bossier play. Anadarko currently is very active with 12 drilling rigs running in Freestone County, Texas. The Bossier formation is encountered at a depth of 13,000 ft with a bottom hole temperature of 300 deg F. The gas stream typically contains 3% CO2, 3-5 ppm H2S, and the produced water is saturated with chlorides. Failures have occurred in numerous wells throughout the field. The paper details the root cause failure analysis investigation conducted, and the influence of well environment, tubing manufacturing process, and tubing material properties in failure. A risk-based approach was used in an attempt to predict tubing failure based on well conditions and material properties. The risk matrix was rationalized against a database of approximately 70 tubing failures. Parameters used in the risk matrix included weld type, weld and base metal hardness, and austenite/ferrite volume fraction ratios. The rationale and factors influencing replacement-tubing decisions (alternate metallurgy) to minimize the occurrence of failures is also described.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
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 head0.019
GPT teacher head0.201
Teacher spread0.182 · 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 designObservational
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

Citations3
Published2004
Admission routes1
Has abstractyes

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