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Record W2065482358 · doi:10.2118/68885-jpt

Foamy-Oil Flow

2001· article· en· W2065482358 on OpenAlexaffabout
Brij Maini

Bibliographic record

VenueJournal of Petroleum Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWellheadPetroleum engineeringFlow (mathematics)Scope (computer science)Scale (ratio)PetroleumComputer scienceOperations researchGeologyEngineeringMechanicsGeographyPhysics

Abstract

fetched live from OpenAlex

Distinguished Author Series articles are general, descriptive representations that summarize the state of the art in an area of technology by describing recent developments for readers who are not specialists in the topics discussed. Written by individuals recognized to be experts in the area, these articles provide key references to more definitive work and present specific details only to illustrate the technology. Purpose: to inform the general readership of recent advances in various areas of petroleum engineering. Summary Foamy-oil flow is a non-Darcy form of two-phase flow of gas and oil encountered in many Canadian and Venezuelan heavy-oil reservoirs during production under solution-gas drive. Unlike normal two-phase flow, which requires a fluid phase to become continuous before it can flow, it involves flow of dispersed gas bubbles. This paper is aimed at acquainting the readers with this type of flow and its role in heavy-oil production. The paper starts with a discussion of what the term "foamy-oil flow" means and how it evolved. Then a brief review of the Canadian field practices is presented. This is followed by a discussion of the pore-scale mechanisms involved and the interplay between capillary and viscous forces. A discussion of the strengths and weaknesses of various mathematical models proposed for numerical simulation of this type of flow is also included. The paper ends with a brief discussion of issues that remain unresolved. Introduction The term "foamy oil" originated from observations of stable foams in samples collected at the wellhead from many Canadian and Venezuelan heavy-oil wells that produce under solution-gas drive. The oil produced from these wells was in the form of thick oil-continuous foam. It was noticed that, very often, a sample container that was overflowing with oil at the time of collection at the wellhead was nearly empty; less than 20% of its volume was filled with oil when opened in the laboratory a few days later, by which time the foam had collapsed. Many of these reservoirs also exhibit anomalous production behavior, both in terms of higher-than-expected well productivity and remarkably high primary recovery factors,1 and this observation was not the result of metering errors caused by foam. Over the years, this anomalous production behavior became closely associated with the foamy nature of the produced oil, and it was suggested that perhaps the two-phase flow behavior of this type of oil in a reservoir rock is different from that of a normal oil/gas mixture. The term "foamy-oil flow" was coined to distinguish the two-phase oil/gas flow in a porous medium of such heavy oils from the normal two-phase behavior. This overview attempts to acquaint the reader with recent developments related to this topic, then provides some insight into the mechanisms involved. Smith1 appears to be the first to publish a detailed analysis of such unusual production behavior. He attributed it to the flow characteristics of heavy oil containing a large volume fraction of very small gas bubbles. He suggested that the mobility of a dispersion of very small bubbles in the heavy oil could be several-fold higher than the single-phase oil mobility. Maini et al.2 attempted to verify this assertion of high dispersion mobility in the laboratory but found that the presence of freshly nucleated gas bubbles actually decreased the oil mobility. However, they found that the dispersed flow of gas was indeed possible under solution-gas-drive conditions. Since then, the flow behavior of such gas-in-oil dispersions has become a subject of several investigations3–15 and considerable speculation, but it remains controversial and poorly understood. Nonetheless, it is well accepted that solution-gas drive in foamy-oil reservoirs involves some unusual effects. It should be mentioned that such dispersed flow of gas under solution-gas-drive conditions in the laboratory was noted by Handy16 in 1958 in high decline rate experiments. However, he concluded that, at the low pressure decline rates in the field, the dispersed flow would not be a significant factor. Although there is still debate on the suitability of the phrase "foamy-oil flow" to describe the anomalous flow of the oil/gas mixtures in cold production of heavy oil, the expression has become a part of petroleum engineering terminology. To some, the term "foamy-oil flow" suggests two-phase flow in the form of oil-continuous foam, and they find it to be a misnomer because the actual microstructure may not resemble foam. To others, including this author, it only denotes the flow of a gas-in-oil dispersion, which is what appears to be involved. However, the full meaning of the term is still evolving, and for now it can be treated as a catchall phrase for representing the contribution of nonequilibrium processes in solution-gas drive in heavy-oil systems. There are two types of nonequilibrium processes involved in solution-gas drive in heavy oils. There is the nonequilibrium between solution gas and free gas that leads to a possibility of significant supersaturation of dissolved gas in the oil phase. The ramifications are delayed release of solution gas and an apparent bubblepoint that is lower than the true thermodynamic bubblepoint. This nonequilibrium process is affected by the kinetics of bubble nucleation and gas diffusivity. Because bubble nucleation is a stochastic process driven by supersaturation, the degree of supersaturation required before nucleation occurs depends on the time available for nucleation. Therefore, this type of nonequilibrium is likely to be more significant in laboratory experiments, which are run on a much smaller time scale compared with the field case.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.004
GPT teacher head0.208
Teacher spread0.203 · 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 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

Citations104
Published2001
Admission routes2
Has abstractyes

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