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Record W2008008738 · doi:10.2118/133206-pa

Is High-Pressure Air Injection (HPAI) Simply a Flue-Gas Flood?

2010· article· en· W2008008738 on OpenAlexafffund
Alejandro Montes, D. Gutiérrez, R.G. Moore, S. A. Mehta, M.G. Ursenbach

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCMG Reservoir Simulation Foundation
KeywordsFlue gasPetroleum engineeringSecondary air injectionSteam injectionCompletion (oil and gas wells)Environmental scienceEnhanced oil recoveryCabin pressurizationCompressed airLight crude oilFlood mythWaste managementMaterials scienceGeologyEngineeringMechanical engineeringComposite materialGeography

Abstract

fetched live from OpenAlex

Abstract High-pressure air injection (HPAI) is an enhanced oil recovery (EOR) process in which compressed air is injected into a deep, light-oil reservoir, with the expectation that the oxygen in the injected air will react with a fraction of the reservoir oil at an elevated temperature to produce carbon dioxide. Over the years, HPAI has been considered a simple flue-gas flood, giving little credit to the thermal drive as a production mechanism. The truth is that, although early production during a HPAI process is mainly due to re-pressurization and gasflood effects, once a pore volume of air has been injected the combustion front becomes the main driving mechanism. This paper presents laboratory and field evidence of the presence of a thermal front during HPAI operations, and of its beneficial impact on oil production. Production and injection data from the Buffalo Field, which comprises the oldest HPAI projects currently in operation, were gathered and analyzed for this purpose. These HPAI projects definitely do not behave as simple immiscible gasfloods. This study shows that a HPAI project has the potential to yield higher recoveries than a simple immiscible gasflood. Furthermore, it gives recommendations about how to operate the process to take advantage of its full capabilities. Introduction High-Pressure Air Injection (HPAI) is an emerging technology for the enhanced oil recovery (EOR) of light oils that has proven to be a valuable process, especially in deep, thin, low-permeability reservoirs(1-7). A number of successful high-pressure air injection projects in light oil reservoirs have been documented in the literature(8-10). Most of these projects have been operating for many years, attesting to their technical and economic success. The improvement in recovery of light oil by HPAI involves a combination of complex processes, each contributing to the overall recovery. These processes include flue gas sweeping, field re-pressurization, oil swelling, viscosity reduction, stripping of the lighter components of the oil, and thermal effects. Early production during the HPAI process is related to re-pressurization and gasflood effects; hence, the influence of the thermal zone is secondary during the early life of an injector. The oil displaced directly by the thermal front will depend on the effectiveness of the generated flue gas on oil displacement from outside the thermal region.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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

Citations67
Published2010
Admission routes2
Has abstractyes

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