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Record W1979372171 · doi:10.2118/71542-ms

Survey of Successful World-Wide Asphaltene Inhibitor Treatments in Oil Production Fields

2001· article· en· W1979372171 on OpenAlexaff
Lawrence M. Cenegy

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2001
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsNalcor Energy (Canada)
Fundersnot available
KeywordsAsphalteneDeposition (geology)Petroleum engineeringInvestment (military)RevenueProduction (economics)Oil productionOil fieldCrude oilEnvironmental scienceBusinessNatural resource economicsGeologyEngineeringChemical engineeringPolitical scienceFinanceEconomicsPaleontologySediment

Abstract

fetched live from OpenAlex

Abstract Asphaltene deposition problems have been known to occur world wide, with serious asphaltene deposition problems being associated with oil fields in Venezuela, the Persian Gulf, the Adriatic Sea and the U.S. Gulf of Mexico. Until recently, these problems were resolved in producing fields by the use of chemical solvents, or by pigging, scraping or other mechanical means of asphaltene removal. Recent advances in asphaltene inhibitor technology have provided cost-effective methods of preventing deposition and, in many cases, increasing the production of the wells being treated. This paper will provide field data relating to the on-going successful asphaltene treatment programs being conducted in above-mentioned oil producing regions around the world. In these cases, large revenue increases were noted by the producers due either to an increase in production or reduced maintenance costs. The paper will detail the specific field parameters as well as the process employed for treating the systems. A cost, and return-on-investment will also be calculated for the treatments, where possible.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.531

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 head0.026
GPT teacher head0.279
Teacher spread0.254 · 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 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

Citations51
Published2001
Admission routes1
Has abstractyes

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