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Record W2055831412 · doi:10.2118/2006-112

Role of Catalytic Agents on Combustion Front Propagation in Porous Media

2006· article· en· W2055831412 on OpenAlexafffund
G.D. Adagulu, I. Yücel Akkutlu, Y. C. Yortsos

Bibliographic record

VenueCanadian International Petroleum Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPorous mediumCombustionFront (military)Materials scienceCatalysisPorosityChemical engineeringComposite materialChemistryMechanical engineeringEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Naturally occurring clays, metallic minerals and additives (catalytic agents) change morphology and surface properties of the reservoir matrix. In in-situ combustion processes these pore-scale modifications lead to variations in combustion front performance. It has been previously reported that catalytic agents have a dual effect on combustion: they modify the kinetics of oxidation reactions inside the front, and they increase the specific surface area of sand grains ahead of the front, promoting hydrocarbon deposition. The emphasis of this paper is the use of analytical approach to investigate the front performance in the presence of catalytic agents under reservoir conditions. The model describes front propagation in a homogeneous porous medium. The front involves coherent propagation of lowtemperature (fuel-generating) and high-temperature (fuel-burning) reaction regions under the influence of reservoir heat losses. The catalytic agents are implicitly introduced to the model in terms of their dual effects. It is found that a strong catalytic effect exists due to changes in the specific surface area of hydrocarbons reacting with the injected oxygen. Variations in the activation energies of the oxidation reactions, on the other hand, are compensated by the reaction frequency (pre-exponential) factors, and they do not influence the combustion performance significantly. The catalytic effect is more pronounced at low air injection rates where heat losses are dominant. Changes in fuel deposition improve the combustion process, in particular at high air injection rates. Then, the front behavior is analyzed in a space of parameters that includes the catalytic agents. For analysis purposes, the space is divided into two sub-domains: one for the fuel generation efficiency and another for the dual effects. The results show existence of optimum conditions in the presence of catalytic agents. Such optimal reservoir conditions lead to frontal coherence and have the potential to significantly enhance combustion performance. Introduction Air injection and in-situ combustion processes have long been used as a thermal oil recovery method. During injection, the development of a self-sustaining combustion front and its propagation throughout the reservoir are necessary for improved recoveries. Front propagation is dictated by the availability of reactants, i.e., oxygen and fuels, and their reaction kinetics under the influence of reservoir heat losses. Unlike steam-based recovery methods, an in-situ combustion process produces significant amounts of heat in the reservoir. Because of the high temperature gradients to the surrounding formations, the process is subject to acute heat loss rates, however. Consequently, temperatures may be reduced considerably, eventually leading to a deteriorated performance and debilitated field operations [1–3]. In this paper, the goal is to determine under which conditions combustion temperature can be maintained at sufficient levels for the combustion front to be controlled adequately and the air injection process to become optimized. Previous laboratory investigations have addressed this issue using kinetic and combustion tube experiments. In the absence of external heat losses, it has been repeatedly shown that naturally occurring clays, metallic minerals and some water soluble metallic additives in the oil/sand mixtures improve self-sustainability of the combustion front.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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 designSimulation or modeling
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
Published2006
Admission routes2
Has abstractyes

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