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Record W4242378463 · doi:10.2118/2009-195

Effect of Temperature and Pressure on Contact Angle and Interfacial Tension of Quartz-Water-Bitumen Systems

2009· article· en· W4242378463 on OpenAlexaff
M. Rajayi, A. Kantzas

Bibliographic record

VenueCanadian International Petroleum Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Calgary
FundersFordham University
KeywordsSurface tensionQuartzContact angleMaterials scienceAsphaltTension (geology)Composite materialPetroleum engineeringGeologyThermodynamicsUltimate tensile strength

Abstract

fetched live from OpenAlex

Abstract Thermal recovery methods (such as steam injection) are recent remarkable technologies to recover bitumen from oil sands. The injected steam contacts the oil sand and forms an interface. The steam changes to water transferring its heat to bitumen across this interface. The heated bitumen will have a lower viscosity, mobilize and recover from the reservoir. Study on hot water-bitumen interfaces should be crucial in understanding the thermal recovery methods. The strength and energy of hot water-bitumen interfaces are expected to play important roles in the recovery of bitumen from oil sands. However, measurements on hot water-bitumen interfaces are not apparent in the literature. A relevant measurement would be the contact angle and interfacial tension of the waterbitumen interfaces at different temperatures. In this paper, it has been attempted to reveal and present the results of several water-bitumen contact angle and interfacial tension measurements. The measurements cover a temperature range from ambient to 100 ° C for a given pressure. The experiments are run in x-ray transparent cells and images are taken using a micro-CT scanner. The results of contact angle and the interfacial tensions of hot water-bitumen interface are produced by using the axisymmetric drop shape analysis (ADSA) method. Introduction Thermal recovery of bitumen causes many changes in the oil sand reservoirs and in fluids properties such as viscosity, density of each fluid, interfacial tension and wettability of the aqueous-hydrocarbon and rock-fluid interfaces. Wettability measurement in the oil recovery industry is quite popular and several different methods have been used to characterize the wettability of different reservoirs. These methods are reviewed in detail by Anderson (1). They are generally categorized in two major groups; qualitative and quantitative methods. Common qualitative methods for wettability measurement are imbibition rates, microscope examination floatation, glass slide method, relative permeability curves, permeability saturation relationships, capillary pressure curves, displacement capillary pressure, reservoir logs, nuclear magnetic resonance (NMR) and dye adsorption. Quantitative methods include contact angle, spontaneous and forced imbibition (Amott) and USBM wettability method. According to Anderson (1) the contact angle method is used to measure the wettability of a certain surface, but the Amott and USBM methods are used for core wettability measurements. Quantitative methods are more commonly used; nevertheless, there is no single universally accepted method. Contact angle (Θ) is the angle at which a fluid-fluid interface meets the solid surface. The Θ is always measured relative to the denser phase. In this work, water is the dense phase. The contact angle method is very useful for wettability measurement when working with clean surfaces and pure fluids. Typically contact angle measurements are done on oil-waterquartz surface systems in order to study the wettability variations under different temperatures and pressures. For the measurement of Θ two immiscible fluids are placed on a solid surface; fluid 1 is the denser fluid. (Θ) can vary between 0 ° and 180 °. If Θ is less than 75 °, fluid 1 is the wetting phase and if Θ is more than 105 ° fluid 2 is the wetting phase.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.657
Threshold uncertainty score0.412

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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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