MétaCan
Menu
Back to cohort
Record W2005788962 · doi:10.2118/08-09-23

In Situ Upgrading of Llancanelo Heavy Oil Using In Situ Combustion and a Downhole Catalyst Bed

2008· article· en· W2005788962 on OpenAlexafffund
Ian D. Gates, Nilanjan Chakrabarty, R.G. Moore, S. A. Mehta, E. Zalewski, P. Pereira

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2008
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersDirectorate for Computer and Information Science and EngineeringUniversidad Tecnológica NacionalUniversity of Calgary
KeywordsCombustionAPI gravityCatalysisIn situPetroleum engineeringWaste managementCokeEnvironmental scienceTube (container)Chemical engineeringMaterials scienceChemistryCrude oilMetallurgyGeologyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract There are vast heavy crude oil resources worldwide that are relatively uneconomical to produce and upgrade. However, there are novel processes available that can be employed in a downhole environment to upgrade these oils, resulting in significantly less sulphur content, and lowered densities and viscosities. A process that is especially favourable for downhole implementation is the use of in situ combustion to generate reactive upgrading gases, such as CO, and possibly H2, to drive oil over a near-wellbore heated bed of catalyst. Two laboratory combustion tube tests were completed to validate this concept. The first test used conventional in situ combustion tube packing and testing techniques, while the second test employed a heated catalyst bed in the downstream region of the combustion tube. A heavy crude oil from the Llancanelo field in Argentina was used for the testing. During the first test, this oil was found to be amenable to the in situ combustion process and exhibited stable combustion performance. Passing mobilized oil and combustion gases over the catalyst bed prior to production in the second test resulted in significant upgrading of the produced oil, including substantial decreases in oil density and viscosity. It is believed that the catalyst efficiently used CO, generated at the combustion front, via the water gas shift reaction to generate H2, which then reacted with the oil to effect upgrading. However, it was found that the presence of a large amount of coke on the post-test catalyst probably indicates the need for periodic regeneration. The presence of a heated production-end catalyst zone did not significantly affect the in situ combustion performance during the second test. Introduction Although there exists a large supply of heavy crude oil throughout the world, most of these reserves lie untapped for various reasons, chief among them being the poor economics of recovering heavy oils. While these economics are beginning to change as conventional oil production declines significantly, the cost-effective production and processing of heavy oils remains a much sought after prize. The authors have previously described how in situ combustion, in combination with a near-wellbore catalyst bed, could be used for significant downhole (in situ) upgrading of heavy crude oils(1, 2). This reference also discusses the potential advantages of in situ upgrading using in situ combustion and a fixed catalyst bed, as well as providing a literature review of the subject. Greaves and Xia(3) and Xia et al.(4) have recently been looking at other variations to the catalyzed in situ combustion process. Two laboratory experimental runs were completed to test the potential of using combustion-produced gases to catalytically upgrade heavy crude oil from the Llancanelo field in Argentina. The first test used conventional in situ combustion tube packing and testing techniques, while the second test employed a heated catalyst bed in the downstream region of the combustion tube, affording the oil an opportunity to be upgraded prior to production.

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 score0.178
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.001
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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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

Citations37
Published2008
Admission routes2
Has abstractyes

Explore more

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