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Record W2172863163 · doi:10.2118/06-01-03

Air Injection-Improved Determination of the Reaction Scheme With Ramped Temperature Experiment and Numerical Simulation

2006· article· en· W2172863163 on OpenAlexaboutno aff
B. Déchelette, O. Heugas, Gérard Quenault, J. Bothua, J. R. Christensen

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2006
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCombustionAdiabatic processNuclear engineeringReliability (semiconductor)Petroleum engineeringProcess engineeringSimulationEnvironmental scienceComputer scienceEngineeringChemistryThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract Abstract In situ combustion is a possible method for producing heavy oil when other methods such as SAGD are not adequate (e.g., in thin beds, or when CO2 emission for steam generation is unacceptable). Previous field trials of this process have often been unsuccessful. However, in recent years, several new well implementations have been proposed (COSH, THAI), exploiting the more advanced drilling capabilities now available. Simulations of such configurations require a reliable representation at field scale of the oxy-combustion reactions, which is not available at the present time. The objective of the work described in this paper is to illustrate some improvements in the description of oxy-combustion reactions both at the experimental level and in the simulation models. A "ramped temperature" experiment has been conducted on an extra heavy stock tank oil (10,000 cP at reservoir conditions). This experiment has been successfully matched using a commercial simulator. The improvement over classical adiabatic reactor experiments is significant: two combustion reactions are clearly observed, and the Arrhenius parameters are determined with increased accuracy. The reliability of the inferred parameter values is checked by applying them to simulations of previous adiabatic disk reactor experiments conducted under a variety of conditions. The final part of the paper is dedicated to illustrating the impact of the new reaction scheme on the simulation results at field scale. Introduction With the more advanced drilling capabilities now available, such as horizontal wells, several new well configurations have recently been proposed for in situ combustion applied to heavy oil [COSH(1), THAI(2)]. To assess the potential of these new configurations by simulation, a reliable representation of the oxy-combustion reactions is required. These reactions govern the oxygen consumption and the time of oxygen breakthrough. Consequently, they will directly influence the efficiency of the recovery process in any given well configuration. Previous authors have addressed the topic of oxy-combustion reactions and kinetics, and a number of publications are available in the literature(3–15). One of the major literature contributors is the University of Calgary, notably due to their work in determining/ proving the presence of the high/low temperature oxidation zones(3, 4). On our side, in order to improve the description of the oxy-combustion reaction scheme both at the experimental level and at the numerical simulation level, we have conducted and simulated a new type of ramped temperature experiment with an extra heavy oil. This new type of experiment has been successfully matched on a commercial simulator (STARSTM from CMG) and has led us to develop a new reaction scheme with two combustion reactions. In the final part of the paper, the impact of this new reaction scheme is evaluated at field scale by comparing numerical simulations made with the old and with the new reaction schemes. Ramped Temperature Experiment Motivations Before developing the ramped temperature experiment, two types of experiments had been developed in Total's Thermal Methods Laboratory in order to determine the kinetic parameters of the oxy-combustion reactions for light oils(9):

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 score0.111
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.004
GPT teacher head0.208
Teacher spread0.205 · 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

Citations52
Published2006
Admission routes1
Has abstractyes

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