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Record W4407824390 · doi:10.1002/9781394356294.ch3

Pipestone Acid Gas Injection System

2025· other· en· W4407824390 on OpenAlexaboutno aff
Rinat Yarmukhametov, J. R. Maddocks, Tim Oldham, Dan Simons

Bibliographic record

Venuenot available
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringChemistryEnvironmental scienceGeology

Abstract

fetched live from OpenAlex

GLE was contracted by Ovintiv to design an acid gas compression, acid gas pipelines, and an injection well originating from their pipestone processing facility (PPF) located near Grand Prairie Alberta. The plan for the PPF project scope includes the installation of acid gas compressors, acid gas dehydration, and piping up to the pipeline riser area of the facility. The pipeline scope consists of three acid gas pipelines (96% H 2 S) and a fuel gas pipeline in a common ditch to deliver the acid gas stream to an injection well located approximately 8 km from the processing plant, where it will be pumped into two injection wells. The pipeline scope includes pig senders and receivers at the PPF and well site as well as four intermediate sectionalizing valve riser sites between the PPF and well site. The well site scope includes acid gas injection pumps, two wells, and associated utilities such as flare, fuel gas, and instrument air. The paper will present some of the design aspects, challenges, and solutions that were unique to this project. Process modeling topics discussed include steady-state and dynamic modeling for acid gas pipelines, wellsite flare system design, hydrate formation prevention during planned and emergency blowdown, and overpressure protection of high-pressure injection pumps and injection line. Operational design topics discussed include acid gas pipeline risk assessment and mitigation strategies, AG (acid gas) pipeline operational procedures, acid gas injection pump control, and thermal relief mitigation strategies in piping and valves.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.058
Threshold uncertainty score0.999

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)0.0020.000

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 head0.017
GPT teacher head0.222
Teacher spread0.204 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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