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Record W1975391963 · doi:10.2118/0407-0090-jpt

Investigation of Drainage-Height Effect on Production Rate in the Vapor-Extraction Process

2007· article· en· W1975391963 on OpenAlexaboutno aff
Karen Bybee

Bibliographic record

VenueJournal of Petroleum Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSoil vapor extractionSteam injectionPetroleum engineeringSteam-assisted gravity drainageOil productionDrainageExtraction (chemistry)Environmental scienceProcess (computing)Process engineeringWaste managementAsphaltEngineeringComputer scienceOil sandsMaterials scienceContaminationChemistry

Abstract

fetched live from OpenAlex

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 101684, "Further Investigation of Drainage-Height Effect on Production Rate in Vapex," by A.J. Yazdani, SPE, and B.B. Maini, SPE, U. of Calgary, prepared for the 2006 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24–27 September. The full-length paper presents the results of a new set of vapor-extraction (vapex) -process experiments in a newly designed very-large physical model. The results are in good agreement with the trend of previous experiments in smaller models. The previously proposed scaleup relationship adequately predicts the results obtained with the new physical model. The new results were used to improve the previously reported empirical scaleup correlation for the vapex process. Experiments with different sand-packs reconfirm square-root functionality of the dead-oil production rate to the permeability. Introduction Interest in heavy-oil- and bitumen-recovery methods is growing because of the huge amount of proven resources in the world. Steam-assisted gravity drainage (SAGD), cyclic steam injection, and other steam-injection methods have been implemented successfully in some oil fields. However, there are many situations where economic constraints limit the application of these thermal processes. High costs of steam generation, excessive heat losses in thin reservoirs, produced-CO2 emission problems, water treatment, and many other technical problems are some of the reasons that make it necessary to look for alternatives to thermal methods. Solvent-based heavy-oil-recovery methods have gained attention recently because of their potential advantages over thermal processes. Solvents, if dissolved in the oil, are able to reduce oil viscosity dramatically. This viscosity reduction is comparable to that obtained by heating. Among the solvent-based methods, vapex has received more interest because of the very encouraging results reported in laboratory studies. Vapex basically is a solvent analog of the SAGD process. Two parallel horizontal wells are drilled one on top of the other in the same configuration as in SAGD. A solvent or a mixture of solvents is injected into the top well near its dewpoint. The solvent-selection criteria depend on reservoir pressure and temperature. A carrier gas usually accompanies the solvent to raise the dewpoint and keep it in vapor form at the prevailing reservoir pressure. Ethane, propane, and butane are considered good solvent candidates. Nitrogen, methane, or CO2 can be used as the carrier gas. The injected solvent vapor displaces the oil and begins to form a vapor chamber around the wells, which then propagates later-ally toward the formation boundaries. The oil production is a result of the dissolution and diffusion of the solvent into the oil zone. The diluted oil moves down to the bottom well through a thin layer near the edge of the oil/solvent interface. In this process, the driving force for the fluid flow primarily is gravity, and the wells are kept at equal pressures. Molecular diffusion and mechanical dispersion are believed to be the controlling mass-transfer mechanisms responsible for the solvent mixing with the oil. The solvent can be extracted at the surface and reinjected to the reservoir. The process continues until the economic limits are exceeded for the oil-production rate when the chamber drainage height decreases.

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)0.002
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 score0.037
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.253
Teacher spread0.247 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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