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Record W3135678192 · doi:10.2118/200624-pa

A Crucial Role of the Applied Capillary Pressure in Drainage Displacement

2021· article· en· W3135678192 on OpenAlexaff
Danial Arab, Apostolos Kantzas, Ole Torsæter, Salem Akarri, Steven L. Bryant

Bibliographic record

VenueSPE Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPetroleum engineeringWater injection (oil production)Capillary actionWettingViscosityCapillary pressureEnhanced oil recoveryOil viscosityGeologyMaterials scienceGeotechnical engineeringEnvironmental sciencePorous mediumComposite materialPorosity

Abstract

fetched live from OpenAlex

Summary Waterflooding has been applied either along with primary production to maintain reservoir pressure or later to displace the oil in conventional and heavy-oil reservoirs. Although it is generally accepted that waterflooding of light oil reservoirs in oil-wet systems delivers the least oil compared to either water-wet or intermediate-wet systems, there is a lack of systematic research to study waterflooding of heavy oils in oil-wet reservoirs. This research gives some new insights on the effect of injection velocity and oil viscosity on waterflooding of oil-wet reservoirs. Seven different oils with a broad range of viscosity ranging from 1 to 15 000 mPa·s at 25°C were used in 18 coreflooding experiments in which injection velocity was varied from 0.7 to 24.3 ft/D (2.5×10−6 to 86.0×10−6 m/s). Oil-wet sand (with contact angle of 159.3 ± 3.1°) was used in all the flooding experiments. Breakthrough time was precisely determined using an in-line densitometer installed downstream of the core. Oil-wet microfluidics (164.4 ± 9.7°) were used to study drainage displacement at the pore scale. Our observations suggest the crucial role of the wetting phase (oil) viscosity and the injection velocity in providing the driving force (capillary pressure) required to drain oil-wet pores. Capillarity-driven drainage can significantly increase oil recovery compared to injecting water at smaller pressure gradients. Increasing viscosity of the oil being displaced (keeping velocity the same) increases pressure gradient across the core. This increase in pressure gradient can be translated to the increase in the applied capillary pressure, especially where the oil phase is nearly stationary, such as regions of bypassed oil. When the applied capillary pressure exceeds a threshold, drainage displacement of oil by the nonwetting phase is facilitated. The driving force to push nonwetting phase (water) into the oil-wet pores can also be provided through increasing injection velocity (keeping oil viscosity the same). In this paper, it is demonstrated that in an oil-wet system, increasing velocity until applied capillary pressure exceeds a threshold improves forced drainage to the extent that it increases oil recovery even when viscous fingering strongly influences the displacement. This is consistent with the classical literature on carbonates (deZabala and Kamath 1995). However, the current work extends the classical learnings to a much wider operational envelope on oil-wet sandstones. Across this wider range, the threshold at which applied capillary pressure makes a significant contribution to oil recovery exhibits a systematic variation with oil viscosity. However, the applied capillary pressure; that is, the pressure drop observed during an experiment, does not vary systematically with conventional static parameters or groups and thus cannot be accurately estimated a priori. For this reason, the scaling group presented here incorporates a dynamic capillary pressure and correlates residual oil saturation more effectively than previously proposed static scaling groups.

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 score0.233
Threshold uncertainty score0.227

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 head0.002
GPT teacher head0.184
Teacher spread0.182 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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