A New Look at the Viscoelastic Fluid Flow in Porous Media—A Possible Mechanism of Internal Cake Formation and Formation Damage Conrol
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Fluid loss control is generally achieved by increasing the shear viscosity of the fluid and developing internal/external filter cake using fluid loss control additives. If the viscosifiers and fluid loss control additives are not selected properly, both mechanisms may lead to significant reduction of permeability. Moreover, increasing fluid shear viscosity may not be desirable all the time due to the high annular pressure losses (i.e., ECD limit), in particular, when drilling long horizontal and extended reach wells. In this paper, a new methodology is presented to formulate an "ideal well fluid", which effectively reduces fluid loss into formation without causing additional frictional pressure losses in the well. Blends of a water-soluble resin (Polyox) with different molecular weight distribution (MWD) and similar average molecular weight (Mw) were prepared. The Polyox blends were then used to prepare aqueous polymer solutions, which had similar shear viscosity but significantly different elastic characteristics (i.e., normal stress difference and relaxation time). Core flow experiments have been conducted to investigate the effects of viscoelastic fluid rheology on the formation of "internal cake" (i.e., frictional pressure drop). Since both fluids have the same shear viscosity but different elastic properties, it was possible to see the effect of fluid elasticity on the frictional pressure losses alone. The fluid with higher elasticity exhibited significantly higher resistance to flow through porous media than that of the fluid with lower elasticity. Experimental results indicated that filtration of a polymer based fluid into porous media could be considerably reduced by controlling the MWD of the polymer at constant shear viscosity and concentration of the polymer. Furthermore, formation damage risk of polymer based well fluids could be minimized without inducing additional pressure drop due to fluid flow inside the well.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it