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Record W4281922753 · doi:10.1115/1.4054704

Experimental and Mechanistic Characterizations of Oil-Based Cement Slurry Flow Behavior Through Fractures in a Carbonate Reservoir

2022· article· en· W4281922753 on OpenAlexafffund
Haiwen Wang, Zulong Zhao, Zhanwu Gao, Yanan Ding, Daoyong Yang

Bibliographic record

VenueJournal of Energy Resources Technology · 2022
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsPetroleum Technology Research CentreUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsSlurryCementMaterials scienceFracture (geology)CarbonateViscosityVolumetric flow rateFlow (mathematics)ComminutionComposite materialGeotechnical engineeringRheologyMechanicsMineralogyPetroleum engineeringGeologyMetallurgy

Abstract

fetched live from OpenAlex

Abstract In this paper, techniques have been developed to experimentally and mechanistically describe the oil-based cement slurry (OBCS) flow through fractures in carbonate reservoirs when it is co-injected with a pad fluid. Experimentally, a three-dimensional (3D) physical model is used to simulate flow behavior within fractures in carbonate rocks by using the ultra-fine cement and class G cement with or without pad fluids. The injection pressures of an OBCS flow are measured and recorded as a function of time during the experiments at a constant flowrate, while effects of fracture width (i.e., 0.5 mm and 1.0 mm) and cement type (i.e., the class G cement and the ultra-fine cement) on injection pressure are examined and analyzed. Theoretically, the Navier–Stokes (NS) equations are modified and integrated to obtain the explicit velocity equations of visco-plastic materials in a planar fracture, and to further quantify the injection pressure of the slurry flow as a function of viscosity, flowing distance of the injected slurry, fracture width, and flowrate. It is found from the experimental measurements that the fracture width imposes a much larger impact on injection pressure along the fracture than other parameters. Once slurry is made in contact with water, its injection pressure not only increases rapidly with one or two orders of magnitude or even larger but also is changed from its linear to exponential relationship with time after a certain time. During the linear stage, the injection pressure of ultra-fine cement is smaller than that of the class G cement, while an opposite pattern is yielded during the exponential stage, i.e., the exponent of the injection pressure formula pertaining to the ultra-fine cement is found to be about 1.5 times larger than that of the class G cement. By incorporating the experimentally measured patterns of the slurry distribution within the fracture model, the newly developed mechanistic model has been validated by reproducing the experimental pressure measurements, allowing us to perform reliable characterization of the OBCS flow behavior in a fracture and then to efficiently and accurately predict and optimize its water-plugging performance.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.210
Teacher spread0.204 · 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 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

Citations2
Published2022
Admission routes2
Has abstractyes

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