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Record W4413250323 · doi:10.1016/j.petsci.2025.07.021

An experimental study of huff-and-puff oil recovery for tight-tuff heavy oil reservoirs by synergistic with viscosity reducer and CO2 utilizing online NMR technology

2025· article· en· W4413250323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science · 2025
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
FundersNational Natural Science Foundation of ChinaBeijing Municipal Natural Science FoundationNatural Science Foundation of Beijing MunicipalityInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsReducerPetroleum engineeringViscosityOil viscosityWellboreEngineeringChemical engineeringEnhanced oil recoveryMaterials scienceMechanical engineeringComposite material

Abstract

fetched live from OpenAlex

The tight-tuff heavy oil reservoir exhibits severe heterogeneity and is characterized by high density, high viscosity, and a high wax content, posing significant challenges for its development. While CO 2 huff-and-puff (H-n-P) enhances oil recovery, these reservoirs struggle with low displacement efficiency. This study proposes a method that combines CO 2 with an oil-soluble viscosity reducer to improve displacement efficiency in the H-n-P process for tight-tuff heavy oil reservoirs. It also focuses on evaluating pore utilization limits and optimizing the injection strategy. Core samples and crude oil from the TH oilfield (a tight-tuff heavy oil reservoir) were used to conduct online NMR core flooding experiments, including depletion development, water, CO 2 , and HDC (CO 2 combined with an oil-soluble viscosity reducer) H-n-P injection processes. A single-porosity model accurately reflecting its geological characteristics was developed using the GEM component simulator within the CMG numerical simulation software to investigate the optimized schemes and the enhanced oil recovery potential for a tight-tuff heavy oil reservoir in the TH oilfield. This model was utilized to evaluate the impact of various injection strategies on oilfield recovery efficiency. The study was designed and implemented with five distinct injection schemes. Results showed that oil was produced primarily from large and medium pores during the depletion stage, while water H-n-P, with CO 2 H-n-P, first targeted macropores, then mesopores, and micropores. The lower pore utilization limit was 0.0267 μm. In the HDC H-n-P process, most oil was recovered from water-flooded pores. Still, HDC's lower injection capacity increased the pore utilization limit to 0.03 μm, making micropore recovery difficult. Experimental and modeling results suggest that the optimal development plan for the TH oilfield is one cycle of HDC H-n-P followed by two cycles of CO 2 H-n-P. This strategy leverages HDC's ability to promote water and oil recovery in the early stage and mass transfer and extraction capacity of CO 2 in later cycles. Additionally, the characteristics of CO 2 and HDC H-n-P processes, pore utilization, and recoverable oil (at the pore scale) were evaluated. The results of this study are crucial for refining the reservoir development plan.

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.

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 score0.653
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.271
Teacher spread0.260 · 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