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Record W4250034782 · doi:10.2118/2007-130

Effect of Foaminess on the Performance of Solution Gas Drive in Heavy Oil Reservoirs

2007· article· en· W4250034782 on OpenAlexafffundabout
A.B. Alshmakhy, B. Maini

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPetroleum engineeringEnvironmental scienceFossil fuelProcess engineeringWaste managementEngineering

Abstract

fetched live from OpenAlex

Abstract Some of heavy oil reservoirs under solution gas drive show abnormally high final recoveries. One of the mechanisms to explain these phenomena is the foamy oil flow effect which occurs under a certain combination of capillary, viscous and gravity forces. It has been studied extensively, yet remains poorly understood and difficult to model. The objective of this work was to investigate the effect of oil foaminess on the performance of solution gas drive in heavy oil reservoirs. In this research, the first step was to find a foaming agent that will have a measurable effect on foam stability of a viscous mineral oil. An experimental procedure was developed to quantify the oil foaminess in the presence of added foaming agent. Several depletion tests were conducted with the added foaming agent at different depletion rates using a 2 meters long sand-pack. The experimental results showed that the foam stability had a positive effect on the solution gas drive performance. Such positive effects of enhanced oil foaminess were mainly observed at low depletion rates. It appears that foam stability plays an active role in the gas-phase build up during solution gas drive and the resulting production behavior. Introduction With high oil prices and continuous decline of conventional resources, the attention is shifting into heavy oil in many parts of the world. Six to nine trillion barrels, or more than two-thirds of the world's oil resources, are heavy viscous crudes that are challenging to produce.1 Heavy oil promises to play a major role in the future of oil industry. Therefore, understanding heavy oil behavior and improving the recoveries in heavy oil reservoirs is crucial to meeting the future energy demand. With higher viscosity, ranging from 500 to 50,000 cp and less than 20 ° API gravity, heavy oils are more difficult to produce than the conventional oils. The high viscosity results in lower recovery factors in primary production. However, some Canadian heavy oil reservoirs produce more than what is expected by the conventional equations. Primary recovery from these reservoirs could be as high as 20%.2 Two main effects are involved in heavy oil – solution gas drive reservoirs: geomechanical effects and fluid flow effects. In conventional solution gas drive the gas evolves in the pore space and connects with the gas in the other pores forming a free continuous gas resulting in higher gas rates. In heavy oil reservoirs, the gas bubbles tend to remain dispersed within the viscous oil because of the high viscosity, low diffusion rates and higher pressure gradients. This behavior results in higher oil reservoir. The production from this kind of reservoirs is usually accompanied with sand and is referred to as Cold Heavy Oil Production (CHOP). The two-phase flow of oil and dispersed gas bubbles is usually referred to as foamy oil flow. Smit3 appears to be the first researcher who provided an analysis to the anomalous behavior of the heavy oil reservoirs under solution gas drive using field data. The most common techniques used to produce the heavy oil from the underground formations are by using the thermal recovery processes.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.228
Teacher spread0.220 · 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

Citations2
Published2007
Admission routes3
Has abstractyes

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