MétaCan
Menu
Back to cohort
Record W2791107086 · doi:10.2118/189767-ms

Cold Solvent Process For Heavy Oil Recovery

2018· article· en· W2791107086 on OpenAlexaff
Arun Sood, Subodh Gupta

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2018
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsCenovus Energy (Canada)
Fundersnot available
KeywordsSolventSteam injectionPetroleum engineeringMerge (version control)Steam explosionMaterials scienceBrineEnvironmental scienceChemistryWaste managementPulp and paper industryGeologyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract A solvent process for heavy oil recovery is described in which an infill injection well is used to inject a cold solvent into neighboring steam chambers once they merge. Simulation results are presented summarizing acceleration in oil recovery and the beneficial impact on energy consumption. Approximately 60% of injected energy in SAGD process is retained in the reservoir. If a cold solvent is injected into a SAGD formation, it will use the stored energy to vaporize and spread within the steam chamber, while at the same time effectively cooling it. An infill injection well is drilled near the top of the rich pay zone and half way between two neighboring SAGD well pairs. Once the steam chambers merge, cold solvent is injected targeting the outer peripheries of the steam chamber. A small amount of non-condensable gas can also be added to help with pressure maintenance. Cooling of steam chamber enhances solubility of solvent in the bitumen phase and accelerates recovery. Once a secondary peak oil rate is observed due to the cold solvent, proportion of non-condensable gas to solvent in the injected fluid is steadily increased and eventually steam injection is completely ceased and the process switches to blow down phase with 100% non-condensable gas injection. Simulation results show that injection of liquid propane and traces of non-condensable gas through the infill injection well provides pressure support and immediately reduces the amount of steam injection required through the primary SAGD injection well by 40-60%. This is followed by a steady increase in oil production rate aided by the viscosity reduction due to propane solubility. A secondary oil production rate peak, comparable to the original peak observed with steam, is achieved. A variation of this process was also simulated for mature SAGD formations, where cold propane injection is accompanied by total steam injection cessation, showing advantageous results. Cold Solvent Process separates out injection of solvent from steam resulting in a much simpler facility design. No additional energy is used to vaporize the solvent at the wellhead. Unlike steam/solvent co-injection processes, solvent is delivered to the cold bitumen interface directly and extracts useful energy from the residual heat in the rock matrix.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score1.000

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 science0.0010.000
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 head0.022
GPT teacher head0.261
Teacher spread0.239 · 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.

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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueSPE Canada Heavy Oil Technical ConferenceSame topicEnhanced Oil Recovery TechniquesFrench-language works237,207