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Record W3006610700 · doi:10.3390/polym12020452

Qualification of New Methods for Measuring In Situ Rheology of Non-Newtonian Fluids in Porous Media

2020· article· en· W3006610700 on OpenAlexfundno aff
Jørgen Gausdal Jacobsen, Behruz Shaker Shiran, Tormod Skauge, K. S. Sorbie, Arne Skauge

Bibliographic record

VenuePolymers · 2020
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersNorges ForskningsrådUniversitetet i BergenEnergi Simulation
KeywordsRheologyShear thinningMaterials sciencePorous mediumPressure dropShear rateNewtonian fluidVolumetric flow rateNon-Newtonian fluidMechanicsPolymerPorosityComposite materialPhysics

Abstract

fetched live from OpenAlex

) data from linear core floods have typically been used to measure in situ rheology of non-Newtonian fluids in porous media. However, linear flow is characterized by steady-state conditions, in contrast to radial flow where both pressure and shear-forces have non-linear gradients. In this paper, we qualify recently developed methods for measuring in situ rheology in radial flow experiments, and then quantitatively investigate the robustness of these methods against pressure measurement error. Application of the new methods to experimental data also enabled accurate investigation of memory and rate effects during polymer flow through porous media. A radial polymer flow experiment using partially hydrolyzed polyacrylamide (HPAM) was performed on a Bentheimer sandstone disc where pressure ports distributed between a central injector and the perimeter production line enabled a detailed analysis of pressure variation with radial distance. It has been suggested that the observed shear-thinning behavior of HPAM solutions at low flux in porous media could be an experimental artifact due to the use of insufficiently accurate pressure transducers. Consequently, a generic simulation study was conducted where the level of pressure measurement error on in situ polymer rheology was quantitatively investigated. Results clearly demonstrate the robustness of the history match methods to pressure measurement error typical for radial flow experiments, where negligible deviations from the reference rheology was observed. It was not until the error level was increased to five-fold of typical conditions that significant deviation from the reference rheology emerged. Based on results from pore network modelling, Chauveteau (1981) demonstrated that polymer flow in porous media may at some rate be influenced by the prior history. In this paper, polymer memory effects could be evaluated at the Darcy scale by history matching the pressure drop between individual pressure ports and the producer as a function of injection rate (conventional method). Since the number of successive contraction events increases with radial distance, the polymer has a different pre-history at the various pressure ports. Rheology curves obtained from history matching the radial flow experiment were overlapping, which shows that there is no influence of geometry on in-situ rheology for the particular HPAM polymer investigated. In addition, the onset of shear-thickening was independent of volumetric injection rate in radial flow.

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)0.008
metaresearch head score (Gemma)0.009
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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.040
GPT teacher head0.322
Teacher spread0.282 · 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
GenreMethods

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

Citations6
Published2020
Admission routes1
Has abstractyes

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