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Record W2017186035 · doi:10.2118/2007-075

The Role of Capillarity in the VAPEX Process

2007· article· en· W2017186035 on OpenAlex
M. Ayub, M. Tuhinuzzaman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsPenn West Exploration (Canada)
Fundersnot available
KeywordsProcess (computing)Computer scienceEngineering drawingMechanical engineeringProcess engineeringMaterials scienceEngineeringOperating system

Abstract

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Abstract Vapor extraction (VAPEX) process warrants the oil industry attention because of its applicability to recover viscous oil in the cases when Steam Assisted Gravity Drainage (SAGD) fails due to the presence of bottom water aquifer, low heat conductivity, thin pay zone and excessive heat losses to adjacent formations. Dilution of heavy oil and thus lowering the viscosity, density, IFT and capillary pressure is considered as the basic mechanism of the VAPEX process. Although, researchers have studied many influencing factors on oil recovery in VAPEX, the effect of capillary pressure has never been studied or understood completely. The objective of this study is to explore the effects of capillary pressure in the VAPEX process by combining experimental results with simulation studies. Extensive experimental studies are conducted in a rectangular transparent visual cell. Grain size distribution and model height are kept constant, while the viscosity of the targeted oil is varied. Capillary pressure and relative permeability data are obtained from flooding experiments to utilize in the simulator. Results analysis reveals that capillarity acts in favor of the VAPEX process by shaping up the vapor chamber, reducing free gas production and also increasing drainage rate by increasing the effective area for molecular diffusion. Introduction With the decline in conventional oil reserves, a major thrust of oil industries throughout the world is on the exploitation of heavy oil and bitumen reservoirs. The magnitude of these resources is about six trillion barrels of oil, which is about six times the total conventional oil reserves(1). A major part of these resources are located in Venezuela, Russia, Canada and the United States. The estimated original oil in place (OOIP) of heavy oil and bitumen in Canada is about 2.7 trillion barrels, which is twice the total conventional oil reserves in the Middle East. Total estimated resource only in the province of Alberta is 1.6 trillion barrels, buried at a depth of 0 – 800m(2). Currently, Steam Assisted Gravity Drainage (SAGD) has become a popular technique for the recovery of heavy oil and bitumen. Despite the apparent successes of the steam processes, it suffers from inherent disadvantages in reservoirs with thin pay zone, bottom water zone and/or overlying gas zone, low thermal conductivity of the rock matrix, high water saturation, low porosity, vertical fractures and/or fissures, etc (3). Vapor Extraction (VAPEX), which was initially proposed by Butler and Mokrys(3,4), is a relatively new process that involves reduction of viscosity by diluting the oil with vaporized hydrocarbon solvents. The concept is analogous to that of SAGD and is represented in Figure 1. It involves two horizontal wells, where the injection well is placed above the production well on the same vertical plane. Then vaporized solvent such as butane, introduced into the reservoir through the injection well, dilutes the heavy oil, which drains down towards the production well under the influence of gravity. In VAPEX, production rates are directly related to the viscosity reduction, which in turn depends on the amount of solvent dissolved in the crude.

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.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
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 science0.0010.000
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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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