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Record W4386953121 · doi:10.1115/omae2023-100573

Dynamic Filtration Loss Control Through Optimization of Drilling Fluid Rheological Properties: A Comparative Study of the Fluid Viscoelasticity Versus Shear Viscosity Effects

2023· article· en· W4386953121 on OpenAlexaff
Hongbo Chen, Ergün Kuru

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsViscoelasticityRheologyElasticity (physics)Drilling fluidShear rateMaterials scienceShear (geology)Composite materialMechanicsDrillingPhysics

Abstract

fetched live from OpenAlex

Abstract Shear viscosity and elasticity have been identified as two of the most influential factors controlling the volume of drilling fluid invasion into reservoir and the resultant formation damage. Past studies were inconclusive regarding individual effects of fluid shear viscosity vs elasticity, as it was challenging to disintegrate and measure their impacts independently. Therefore, we investigated the relative contributions of the fluid shear viscosity and the elasticity on the fluid invasion and the resultant productivity impairment. 24 water-based drilling fluids were prepared using various blends of three different molecular weight PHPA polymers. Detailed rheological characterizations of these fluids were carried out by conducting amplitude sweep and controlled shear rate tests. Viscoelastic properties of the fluids were quantified in terms of energy dissipation, which physically signifies the amount of energy required per unit volume to cause an irreversible deformation in the fluid’s internal structure. Static filtration tests and core flooding experiments were conducted to determine the static fluid loss, pressure drop across the cores at different flow rates, and the resultant formation damage induced by each fluid. Using a unique technique we developed in our previous work, we have formulated two groups of fluids; one group with the same shear viscosity and variable elasticity and the other group with the same elasticity and variable shear viscosities. Hence, we could investigate the individual effects of shear viscosity and elasticity on the static and dynamic filtration loss and the resultant formation damage. By investigating the independent effects of viscoelasticity and shear viscosity on the fluid filtration loss characteristics, we have observed that: 1-) The static filtration rate can be more effectively reduced by altering fluid viscoelasticity as compared to the fluid shear viscosity. 2-) Both shear viscosity and viscoelasticity have a direct relationship to the pressure drop associated with the core flow. However, the effect of viscoelasticity on the pressure drop is more pronounced. 3-) Increasing fluid viscoelasticity inhibits fluid invasion into the formation better than that of the fluid shear viscosity. 4-) The results have suggested that viscoelasticity can be effectively used for developing non-invasive fluids, which would reduce static filtration rate, increase pressure drop (i.e. building internal cake), and minimize formation damage by effectively reducing fluids invasion. The study introduces an innovative approach to investigate the fluid loss and formation damage characteristics of viscoelastic, solids-free drilling fluids. The sole effects of shear viscosity and viscoelasticity on filtration loss characteristics were investigated and compared. Understanding the mechanisms of internal cake formation and their quantitative relation to fluid viscous and elastic properties will help the design of optimum drilling and completion fluids and, hence, minimize the productivity reduction associated with applications of these fluids.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.021
GPT teacher head0.238
Teacher spread0.217 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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