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Record W2794304183 · doi:10.2118/189776-ms

Hydrocarbon Recovery Using a Convective Solvent Extraction Process

2018· article· en· W2794304183 on OpenAlexaff
Arun Sood, Subodh Gupta

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2018
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsCenovus Energy (Canada)
Fundersnot available
KeywordsInjectorPetroleum engineeringOil sandsDew pointEnvironmental scienceSolventGeologyMaterials scienceAsphaltChemistryEngineeringMechanical engineeringMeteorology

Abstract

fetched live from OpenAlex

Abstract Going forward, limiting greenhouse gas emissions and reducing water usage in oil sands upstream operations is essential to meeting regulatory requirements and a pre-condition for the social license to operate. As Oil Sands Industry exhausts its best quality rich pay and gradually move into producing bitumen from marginal quality assets with thin pay zones, SAGD performance will deteriorate with higher steam to oil ratios. In this paper, Enhanced Convective Solvent Extraction (ECSOLVEX) process is described to apply to such reservoirs. ECSOLVEX predominantly uses a pure solvent which is injected into the reservoir at or above its dew point temperature. Injection and production wells are placed some distance apart in the same lateral plane. Sidetracks from injector well to close proximity of the producer well allow a solvent chamber to extend to the inter-well region. The process is primarily gravity driven with a mild convective gradient from injector to the producer well. A solvent chamber is established along the side track lateral, which grows parallel to the injector and producer wells. Water production is limited since it is a solvent driven processthat would result in a reduced footprint for the surface oil water separation facility. Simulation results show that each side track creates its own drainage chamber which performs independently of other drainage chambers till they merge, thus the production performance of this process is a function of the number of sidetracks drilled. As an example, with propane as the solvent, production rates can be doubled that of SAGD if sidetracks are drilled every 100m. The energy consumption and associated emissions of such a process would be 70% less than SAGD. The performance can be further improved by localized heating in the proximity of the producer well. ECSOLVEX process concept provides the opportunity for economic recovery from pay zones which are not thick enough for traditional SAGD process to operate. It demonstrates significantly lower energy consumption as compared to SAGD, leading to a lower carbon footprint and has the potential to reduce the size of the oil water separation facility.

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 score0.249
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.031
GPT teacher head0.296
Teacher spread0.266 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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