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Record W4408266424 · doi:10.2118/224015-ms

The Role of Hydrogen Index Independent Measurements and Nuclear Modelling in Thermal EOR Projects

2025· article· en· W4408266424 on OpenAlexaffabout
Ulises Bustos, Li C. Cheung, Hossein Aghabarati, Chris Okuku, Ranjan Das

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsSuncor Energy (Canada)
Fundersnot available
KeywordsIndex (typography)ThermalHydrogenNuclear engineeringEnvironmental sciencePetroleum engineeringComputer scienceThermodynamicsEngineeringChemistryPhysicsWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Steam assisted gravity drainage (SAGD) is a technology used in Canada to extract bitumen from sandstone reservoirs. Steam is injected into the reservoir to rise and form a steam chamber. It heats up the bitumen, lower its viscosity and facilitates production. Among all the various initiatives, non-condensable gas (NCG) injection has been one of the most used elements to improve steam efficiency, particularly in mature operation and in reservoir with relatively higher water saturation. To evaluate SAGD operation efficiency, the understanding of saturation changes is important. In this context, formation evaluation and reservoir surveillance play an important role. For this purpose, the most common service is the cased hole pulsed neutron. The best-known pulsed neutron measurements are the carbon/oxygen ratios, sigma and neutron porosity outputs. These have been widely used for petrophysical analysis in cased wells, involving bitumen saturation changes from carbon/oxygen ratios and qualitative steam volumes from gamma-ray count rates decay. In SAGD projects, however, scheme efficiency monitoring requires analyzing steam and NCG movement and fractions in and around steam chamber, in addition to bitumen and water saturations. During time-lapse logging, experience indicates that changing borehole conditions (fluid type, for instance) along the reservoir surveillance period, are common in SAGD. To avoid biasing true formation response, proper borehole corrections are then required in every single monitoring job. Nuclear modelling on computed formation fluids densities for the actual temperature and pressure regimes, strongly support the understanding of pulsed neutron outputs response while ensuring representative cased hole petrophysical assessment. Pulsed neutron's inelastic and capture gamma ray measurements are used to solve for matrix mineral volumes, thus enabling matrix-corrected porosity (from the neutron and/or additional measurements such as bulk density and sonic whenever available) outputs. The bitumen volume and saturation are assessed from total organic carbon measurement and carbon/oxygen ratios, whereas volumetric analysis of low-density components (steam and NCG) is based on the hydrogen independent FNXS measurement, involving nuclear modeling that computes FNXS response as per temperature and pressure conditions. This workflow also provides steam and non condensable fractions estimations (within the total low-density fluid volume), from hydrogen independent count rates ratio and hydrogen dependent capture ratio. This volume also provides fluids corrections for total porosity output. The technique presented in this work has been tried on actual measurements and proven to be very efficient for petrophysical fluid-rock analysis in reservoir monitoring carried out during variable period (from months to years). Nuclear modeling enabled a better understanding of pulsed neutron response in specific temperature and pressure conditions and thus producing a more accurate and representative reservoir fluids analysis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.210
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes2
Has abstractyes

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