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Record W4399627871 · doi:10.2118/218041-pa

New Insights from an Old Method after History Matching a Newly Designed 1D Cyclic Steam Stimulation Experiment

2024· article· en· W4399627871 on OpenAlexaff
Belenitza Sequera-Dalton, D. Gutiérrez, R.G. Moore, S. A. Mehta, M.G. Ursenbach, Héctor A. García, R. Pérez, H. A. Rodríguez, Eduardo Manrique

Bibliographic record

VenueSPE Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBallastSteam injectionPetroleum engineeringCabin pressurizationCore (optical fiber)Environmental scienceMaterials scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Summary A cyclic steam stimulation (CSS) laboratory experiment was conducted with dead heavy oil. Four cycles of steam injection and fluid production were performed, at reservoir pressure, to assist in the numerical modeling and understanding of the main mechanisms involved in the process. This was an important step in developing a base model for a broader project evaluating CSS steam-hybrid experiments with live oil. Experimental data, history matching approach and results, as well as key insights are presented. An experimental setup, originally designed to evaluate CSS hybrid processes, was improved by fitting a sight glass to identify the fluids flowing out of the opposite core end (into a ballast system), during injection cycles. Dead oil was used to facilitate the analysis of this experiment. Relative permeability curves were tuned to history match each cycle sequentially. Injection periods were matched before production ones to estimate the amounts of oil and water displaced to the ballast during injection (unknown, although total liquid volumes in the ballast were recorded continuously), which were later injected back into the core during production periods. A 1D grid represented the core section, while the ballast system was modeled with a production well and an injection well. Experimental data such as temperature profiles, pressures, and rates were honored. A volumetric ratio of 40% water and 60% oil appeared to be the typical composition of the fluid received by the ballast during injection periods, based on simulation results. Fluids reinjected from the ballast back into the core were modeled as an emulsion (i.e., a water-oil mixture). Relative permeability curves were the same for injection and production periods within the same cycle, except for an increased critical water saturation during the last two production periods. One set of relative permeability curves was obtained for each of the four cycles. Although all the cycles of the CSS experiment were history matched successfully using water-oil relative permeability curves, the need to have different curves for each continuous cycle suggests that different flow phenomena were taking place during the CSS test. After reviewing different mechanisms associated with steam injection processes, it appears plausible that injected steam, after condensing to water, partially emulsified with the heavy oil in the core. Insights from this work suggest a need to rethink the traditional way of modeling heavy oil recovery with steam, where water-in-oil emulsion formation typically occurs.

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: Methods · Consensus signal: none
Teacher disagreement score0.266
Threshold uncertainty score0.781

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.280
Teacher spread0.267 · 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
GenreMethods

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
Published2024
Admission routes1
Has abstractyes

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