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Record W2091109477 · doi:10.2118/2006-087

The Effect of Scale on the Primary Depletion of Heavy Oil Solution Gas Drive

2006· article· en· W2091109477 on OpenAlexafffund
N. Goodarzi, Apostolos Kantzas

Bibliographic record

VenueCanadian International Petroleum Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersCanada Research Chairs
KeywordsCitationDownloadScale (ratio)Computer scienceProduction (economics)Library scienceWork (physics)Operations researchEnvironmental scienceWorld Wide WebEngineeringGeographyEconomicsCartographyMechanical engineering

Abstract

fetched live from OpenAlex

Abstract It has been well established that the primary production of heavy oil, exhibits higher that expected recovery due to the production of sand and the foamy oil mechanisms. In the literature, there has been much work done in the past to investigate the solution gas drive mechanisms that cause this behavior, in the absence of sand production. The aim of this work is to perform pressure depletion experiments on packings of different scales of length and diameters, ranging from 0.5 m to over 18 m in length and diameters of 0.02 m to 0.08 m. The experimental results combine the production, pressure and saturation data from three different scales with the same depletion rate. An attempt is made to compare and relate the results from the different scales. Introduction Investigations of heavy oil solution gas drive, at the laboratory scale, rely on high depletion rates to reproduce the behavior seen at much lower depletion rates in the field. In addition, altering the depletion rates results in different critical gas saturations, gas relative permeabilities and overall recovery (1,2). The high depletion rate is important at early times when the gas is nucleating and growing; however, at late times the pressure gradient is dominant in mobilizing the fluid(3). Therefore, a high depletion rate experiment may represent near wellbore behavior and a slow depletion rate represents mechanisms further from the well. Andarcia et al. (4) commented on the difficulty in determining the influence that the depletion rate and the spatial size have on the gas and oil relative permeability. Scaling the experimental results to represent reservoir mechanisms is complex. There is very little information regarding the effect of experimental sand pack length in the literature. Sheng et al.(5) used the dynamic kinetic model they developed to predict the effect of length for sand packs of three different lengths. They determined that the length of the sand pack is associated with the pressure gradient; in the long sand packs, high-pressure gradients do not develop in the regions far from the wellbore. Therefore, even though the high depletion rate at the production end was the same as the shorter packs, the average pressure decline is slower, resulting in lower recoveries. Wall and Khurana(6) found that the gas saturation that develops as the pressure of a saturated liquid declines in a porous medium generates low values of relative permeability. They noted that the gas relative permeability is an irreversible function of gas saturation, with the added problem that even at relatively high gas saturations there is zero permeability to gas. Kennedy and Olson(7) observed that variations in gas distribution in the reservoir account for different relative permeabilities for the same gas saturation. Pooladi-Darvish and Firoozabadi(8) also stated high bubble densities and discontinuous gas accounts for the reduced gas mobility. Tang and Firoozabadi(9) assumed that gas and oil flow in pseudo steady state, the gas saturation across the core is uniform, and flow is one dimensional, in order to develop a mathematical model to calculate oil and gas relative permeabilities.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.431
Threshold uncertainty score0.995

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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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 designBench or experimental
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

Citations3
Published2006
Admission routes2
Has abstractyes

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