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Record W2080397875 · doi:10.2118/94092-ms

Air Injection Into a Mature Waterflooded Light Oil Reservoir. Laboratory and Simulation Results for Barrancas Field, Argentina

2005· article· en· W2080397875 on OpenAlexaboutno aff
Maria L. Pascual, D. Crosta, Dennis Coombe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSecondary air injectionPetroleum engineeringCombustionWater injection (oil production)Environmental scienceSaturation (graph theory)Oil fieldInjectorIgnition systemOil productionGeologyWaste managementEngineeringChemistryMechanical engineering

Abstract

fetched live from OpenAlex

ABSTRACT This paper describes preparations for an air injection pilot into a mature waterflooded light oil reservoir in Barrancas field, Argentina. Primary development started in 1954, with waterflooding beginning in 1967. As the reservoir characteristics are quite similar to economically viable air injection projects in the Williston Basin, the feasibility of air injection for Barrancas was investigated. The upper layer has contributed 40 % of the total field production with 46 % of the injected water entering into the sequence. The three lower zones appear to be good candidates for air injection due to their current high oil saturation. Laboratory studies carried out at the University of Calgary were aimed at determining pilot design information (self-ignition, fuel availability, air requirements). These included accelerated rate calorimetry, ramped test oxidation, and high pressure/high temperature combustion tube tests. The combustion tube showed excellent burning characteristics (temperature profiles >300 °C). A reasonable simulation match was obtained using compositional PVT from Barrancas to define the component description. The laboratory simulations were then used to explore various additional sensitivities. The history match model consisted of a target pilot zone of six inner producers surrounded by additional outer producers and numerous water injectors. The four sequences were separated with transmissibility barriers of varying strength, and also contained channels with permeability enhancements. The magnitudes of these factors and the water-oil relative permeability characteristics were adjusted during the history match. The black oil reservoir description was then converted to the thermal/compositional representation for the air injection sensitivity runs. Several air injection scenarios with two air injectors were considered, including variation in air injection rates and injection completion zones, and wet combustion as a follow-up to dry. According to the results of this study, the process is technically feasible. Currently the economic aspects are being studied before pilot implementation.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.060
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.007
GPT teacher head0.252
Teacher spread0.245 · 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 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

Citations14
Published2005
Admission routes1
Has abstractyes

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