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Record W2616519164 · doi:10.2118/185533-ms

Impact of Clay type on SAGD Performance Part I: Microscopic Scale Analysis of Clay-SARA Interactions in Produced Oil

2017· article· en· W2616519164 on OpenAlexaboutno aff
Taniya Kar, Berna Hasçakir

Bibliographic record

VenueSPE Latin America and Caribbean Petroleum Engineering Conference · 2017
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsnot available
FundersTexas A and M University
KeywordsAsphalteneKaoliniteIlliteClay mineralsChemical engineeringOil sandsChemistryAsphaltMineralogyGeologyMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The impact of non-swelling clays on Steam-Assisted Gravity Drainage (SAGD) performance was studied in this work. Two SAGD experiments were conducted on a Canadian bitumen by preparing the reservoir rocks with two different non-swelling clays; kaolinite (SAGD1) and kaolinite (90 wt%) and illite (10 wt%) (SAGD2). Change in clay type from kaolinite to a mixture of kaolinite and illite resulted in 15 wt% lower cumulative oil recovery. The role of clays and their interaction with crude oil fractions; namely Saturates, Aromatics, Resins and Asphaltenes (SARA fractions), on process performance was investigated through control experiments under optical and scanning electron microscopy. Pseudo blends of clays and SARA fractions revealed that kaolinite-asphaltenes interaction in SAGD1 occurs at steam condition, however, the same interaction happens for kaolinite-illite mixture at liquid water condition. It has been observed that while kaolinite-asphaltenes interaction is a direct interaction, 10 wt% illite addition to clay (SAGD2) causes an indirect interaction. This indirect interaction occurs due to mainly aromatics-clays association. Clays in SAGD2 were observed to be carried inside asphaltenes clusters. Since aromatics are soluble in asphaltenes, initially a black colored microscopic image was obtained. Upon the evaporation of aromatics, it has been observed that clays still preserve their original white color, however, stuck in asphaltenes clusters. Thus, our results concluded that not only heavy and polar fractions of crude oil, but also non-polar fractions may play an important role in oil displacement during SAGD.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.274
Teacher spread0.258 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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