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Record W2032951280 · doi:10.2118/00-04-04

The Steam and Gas Push (SAGP)-2:Mechanism Analysis and Physical Model Testing

2000· article· en· W2032951280 on OpenAlexfundaboutno aff
Qi Jiang, R.M. Butler, C.T. Yee

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
FundersSuncor Energy IncorporatedCanadian Natural Resources LimitedUniversity of Calgary
KeywordsPetroleum engineeringSteam injectionOverburdenFossil fuelMethaneEnvironmental scienceChemistryWaste managementMechanicsEngineeringPhysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract At the 48th Annual Technical Meeting of the Petroleum Society, one of us presented a paper that showed that there was a possibility of making the SAGD process more efficient by adding a small concentration of a non-condensible gas such as methane to steam(1). For this to be effective the steam injection well should be located slightly above the production well. With this configuration, and with a small continuous production of gas with the produced oil and condensate, the non-condensible gas becomes concentrated in the upper part of the chamber and the heat loss to the overburden, and for the heating of the chamber, is greatly reduced; the steam oil ratio is much lower. Another configuration involves the continuous injection of a small stream of non-condensible gas from a well or wells near the top of the chamber with steam injection from a lower well or even into the production well. The heat is confined to the near wellbore region and again there is a considerable economy. The present paper discusses further analysis of these configurations and also results from physical model tests that are being carried out at the University of Calgary. The results of these experiments have been very positive and it appears that the concept may be even more effective than was predicted originally. The reason for this appears to be that the introduction of gas with steam invokes a new mechanism as the gas flows counter currently to the falling liquids; this mechanism involves the creation of a large surface area for mass transfer. As a result, the steam chamber is not only much lower in temperature, particularly at the top, but it also rises more slowly and spreads laterally more quickly. A larger volume is draining at a much lower temperature. Measurements made in our model show large improvements in the steam/oil ratio. The observation of the new mechanism suggests that this approach may have economic applications in fields having top water such as Surmont as well as in more normal type reservoirs. In general, the improved performance should broaden the range of reservoirs that can be produced economically. Introduction It is estimated that there are 273 billion m3 heavy oil and bitumen in place in Canada. They are deposited mainly in the Athabasca, Cold Lake, Lloydminster, and Peace River areas. Conventional heavy oil (10 to 20 ° API), which is partially recoverable by conventional in situ methods, is less than 2﹪ of the total resources. Most of the bitumen has a viscosity ranging from 100,000 to over 1.0 million mPa ⋅s at reservoir temperature. It is present in a solid or semi-solid state in the porous media and there is almost no mobility at the initial reservoir conditions. The effective recovery of bitumen by in situ methods is difficult. The current production of bitumen is over 400,000 barrels a day, which constitutes about 70﹪ of the total heavy oil and bitumen production(2) in Canada.

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)0.001
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations60
Published2000
Admission routes2
Has abstractyes

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