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Record W1971733887 · doi:10.2118/97643-ms

Field Experiences in Application of a Novel Relative Permeability Modifier Gel in North Sea Operations

2005· article· en· W1971733887 on OpenAlexaff
Jonathan Wylde, Graham Williams, C. Shields

Bibliographic record

VenueSPE International Improved Oil Recovery Conference in Asia Pacific · 2005
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsBP (Canada)
Fundersnot available
KeywordsProduced waterPetroleum engineeringPermeability (electromagnetism)SeawaterEnvironmental scienceNorth seaWater cutRelative permeabilityOil productionWater injection (oil production)Oil fieldGeologyChemistryGeotechnical engineeringOceanography

Abstract

fetched live from OpenAlex

Abstract Proposal Over a dozen successive selective water shut off treatments (SWSO) have been performed on an individual North Sea field. The target wells were vertical, cased, perforated producers in a mature, high scale potential asset in the UKCS. Reservoir temperatures were in excess of 121°C and permeability ranged from 100 – 1000 mD. Mention is also given to several other treatments performed in this mature field on wells with water rates up to 16,500 bwpd. Treatments were generally bullheaded as part of a scale inhibitor squeeze intervention, being contained in the final portion of the over flush. Results were all positive and in one case reduced water production by up to 60%. Furthermore, oil production was stimulated by up to 250%. The non-hazardous, low concentration chemical treatments were developed for pumping from the surface to reduce water production without affecting hydrocarbon production. It is more generally applicable than previous SWSO systems as it can be applied from ambient temperatures up to 130°C and 20mD – 16 D. This paper details the treatment design and pre-qualification experiments to a variety of field applications of a novel relative permeability modifier gel. Details are given regarding the pumping schedule, treatment well test data, and lessons learnt from the operations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.642

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 communication0.0000.001
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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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

Citations5
Published2005
Admission routes1
Has abstractyes

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