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Record W2062707764 · doi:10.2118/129989-ms

Field Applications of Behind-Pipe Saturation Evaluation in a Miscible CO2 Flood

2010· article· en· W2062707764 on OpenAlexaff
Richard G. Hughes, Samuel Amadi, D. F. D'souza

Bibliographic record

VenueSPE Improved Oil Recovery Symposium · 2010
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsPetroleum engineeringSaturation (graph theory)Oil fieldWell loggingFlood mythLoggingWater saturationEnvironmental scienceGeologyGeotechnical engineeringMathematics

Abstract

fetched live from OpenAlex

Abstract To evaluate the amount of bypassed oil in a CO2 flood, it is necessary to obtain some estimate of the remaining oil saturation. Near wellbore oil saturation determination requires a tool or sequence of tools that is able to distinguish oil from other phases that may be present in situ especially when those phases are miscible with the oil. Cased hole logging in waterfloods, steam floods and CO2 sequestration cases has been presented and the techniques used are in the process of becoming reasonably reliable evaluation tools. Very little work has been presented on the case where an existing CO2 flood needs to be evaluated, but has no baseline cased hole logs to tie to. This paper presents the results of field tests where carbon-oxygen and pulsed neutron logs were used in combination to evaluate in situ saturations in an area where oil, water and CO2 are present but where no previous (baseline) cased hole logs had been run. One of the wells had a nearby core characterization and modern open-hole logs to tie the cased hole logs to while another was in the same formation, but only had 1960's vintage open-hole logs. Techniques described in a previous publication were used to perform the evaluation. The theoretical result previously presented worked fairly closely to what was described. However, there are a number of variable parameters required that need to be evaluated and reasonable estimates (or methods to obtain reasonable estimates) of those values are not well documented. This paper will also document the methodologies that seemed to work to successfully estimate these parameters.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.599

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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