MétaCan
Menu
Back to cohort
Record W2072955682 · doi:10.2118/04-09-01

Downhole Catalytic Process for Upgrading Heavy Oil: Produced Oil Properties and Composition

2004· article· en· W2072955682 on OpenAlexfundno aff
M. Greaves, T.X. Xia

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2004
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
FundersLoughborough UniversityUniversity of BathUniversity of Saskatchewan
KeywordsDiesel fuelGasolineAsphaltCombustionOil sandsCatalysisPetroleum engineeringFuel oilSecondary air injectionSynthetic crudeLight crude oilEnvironmental scienceChemistryWaste managementMaterials scienceUnconventional oilFossil fuelGeologyEngineeringOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The level of in situ upgrading of heavy Wolf Lake oil achieved by a downhole catalytic process, which is a catalytic variant of the THAI process-"Toe-to-Heel Air Injection"-has been investigated using various analytical methods. These included gas chromatography (GC), elemental analysis, simulated distillation (SIMDIS), micro-activity test (MAT), plus density and viscosity. The tests were performed on the oil produced from the downhole catalytic upgrading process, which was conducted in semi-scaled 3D combustion cells. The tests employed a standard hydrogen de-sulphurisation (HDS) catalyst, which was "gravel packed" around the horizontal producer well, forming an annular radial inflow type reactor. Although the analytical measurements made were necessarily selective in their scope, they nevertheless provide a good indication of what the potential may be for downhole upgrading in the field. Downhole catalytic upgrading produces a "light oil, " characterized by a low viscosity of around 60 mPas, or less. The produced oil is readily converted into gasoline and diesel fractions, with a higher conversion on an FCC basis than that obtained with normal virgin bitumen vacuum gas oil. Environmentally, there are also very significant potential benefits regarding in situ removal (and retention) of heavy metals, and reduction of sulphur in the oil. Introduction Fireflooding, in situ combustion (ISC), or heavy oil air injection (HOAI) is a process wherein a combustion front is propagated through the formation, vapourizing the oil and water ahead of it. Conventional forward combustion is a long-distance displacement process (Figure 1), so that vapourized oil and water are condensed in the cooler parts of the reservoir and are eventually produced from a producer well. Theoretically, forward combustion is intended to burn the least desirable fraction of the oil, leaving a clean formation behind. Its main drawback is that there must be sufficient mobility for the vapourized oil and water to be producedfter they have condensed ahead of the combustion front. This factor, frequently leading to loss of air injectivity and consequent inability to maintain the process in a high temperature oxidation (HTO) mode, has probably been responsible for the poor performance, or failure, of many field applications of the conventional ISC process. Short-distance displacement (Figure 1) is a concept that was made possible by the development of horizontal well technology. SAGD (steam-assisted gravity drainage) is the most well-known thermal process in this category. THAI-"Toe-to-Heel Air Injection," is an integrated horizontal wells-thermal process, also fitting into the short-distance displacement category (Figure 1), but with some unique features. Briefly, there is no necessity for communication into, or displacement through, the oil layer downstream of the combustion front. Rather, this is excluded by THAI, since the cold heavy oil region downstream of the combustion front provides a natural "barrier" by virtue of its very high viscosity, as well as providing a seal around the horizontal producer well. Figure 1 illustrates the "moving window" effect in THAI, due to the propagation 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Citations24
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Canadian Petroleum TechnologySame topicPetroleum Processing and AnalysisFrench-language works237,207