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Viscoelastic Polymer Flooding and Residual-Oil Desaturation
Viscoelastic Desaturation
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Viscoelastic polymer flooding · Criteria-screened evidence synthesis

Does polymer viscoelasticity reduce residual oil beyond the viscous contribution?

The screened record does not resolve an additional viscoelastic effect. Explore the velocity classifier, then inspect the study-level evidence and admitted contrasts.

Try the velocity classifier
Paired within-study mean ΔSor
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Contrasts / admitted studies
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Paired 95 % t interval
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Studies screened → admitted
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These statistics are computed in the browser from the 49 published contrasts in Section 02; none of them is a SAMPLE value. SAMPLE values on this page are limited to the injectivity calculator defaults.

Read the study abstract and basis

The screened record does not resolve it. Thirty-nine published studies reduce, through logged admission criteria, to seven holding a matched-viscosity inelastic reference, yielding 49 elastic-versus-reference contrasts on one declared velocity and capillary-number basis. The primary quantity is the paired within-study high-minus-low velocity difference across the four studies carrying both regimes: +0.047, +0.005, +0.024 and −0.037 saturation units, mean +0.010 s.u., paired interval at three degrees of freedom [−0.046, +0.066]. Only an effect larger than approximately 0.06 saturation units in magnitude would have been resolvable at this corpus size, so the record measures the literature’s resolving power rather than the effect.

This page is a synthesis of published evidence.

This report examines viscoelastic-polymer evidence reported in the cited literature. Included datasets, screening criteria and calculated results are identified with their sources and assumptions.

Manuscript status: In preparation
How to useThe classifier and paired estimates recompute from the 49-contrast dataset.
  1. Open the Velocity classifier pane to move the velocity cut and the boundary rule and watch the stage cells, the paired within-study estimator and the leave-one-out range respond.
  2. Open Injectivity bounds to set q/h, porosity and an onset velocity and read the onset radius r*.
  3. Contrast dataset carries every record behind the statistics, and Model & equations carries the conventions.

Seeded bootstrap results do not recompute. Values that depend on a random seed — the study-resampling bootstrap — are quoted as computed at seed 20260731 and are not re-derived here.

The central result — paired within-study contrasts

velocity-only classifier · vi > 1 ft/D strict

Screened record

basis of every number on this site

What the screened record can and cannot say

conclusions drawn from the screened record
  1. Of thirty-nine inventoried published studies, seven satisfy the matched-inelastic-reference screen, yielding 49 elastic-versus-reference contrasts. The screen, the per-value provenance, the exclusion log and the statistical guards against non-independence are the methodological contribution; the extensional capillary number used for replotting is prior art (Azad and Trivedi 2021, 2023).
  2. The corpus does not resolve an independent velocity effect attributable to polymer viscoelasticity; this is the central finding. At the stage level the velocity-only tertiary cells do not separate (+0.052 against +0.059, n = 15 and 17); an ordering appears only under boundary reassignment (+0.068 against +0.036) or under the superseded classifier; and every salinity-unconfounded tertiary increment of at least 0.10 saturation units lies at 1 ft/D (0.3048 m/d) or above. The record likewise contains no matched-reference support for a secondary-mode elastic advantage.
  3. Two quantified channels inflate apparent scatter in compiled desaturation curves: stage-wise salinity change (exceeding the unconfounded elasticity channel) and the endpoint-krw convention (a 1.3–2.9-fold capillary-number bias, saturation-dependent and therefore systematic rather than random).
  4. The constructive output is a proposed minimum reporting checklist and a proposed matched-reference carbonate experiment.

What is on this page

click any card to open
Source screening and evidence tiers

Corpus and screening funnel

Thirty-nine published studies were inventoried. Five same-study merges reduced these to 34 evidence units; 15 were excluded with logged reasons, leaving 19 viscoelastic coreflood sources, of which seven were Admitted and 12 Supportive. The comparison-level mapping yields the 49 elastic-versus-reference contrasts carried through the rest of this page.
Prepared by Imad A. Adel

Screening flow

counts from the deposited dataset
Admission rule: a study reporting endpoint saturations for a viscoelastic stage and a matched-viscosity inelastic reference (glycerol, xanthan, scleroglucan, or low-molecular-weight polymer at matched apparent viscosity or matched pressure gradient), with extractable velocity or pressure-gradient information. Supportive: a study missing one element — no inelastic reference, recovery-basis saturations, or unreported interfacial tension or geometry; these inform interpretation but never enter the quantitative comparisons.

Admitted studies

Appendix A · one row per study
Values are in the first-listed unit of each column header. Reference grades: A — xanthan, scleroglucan or a matched low-elasticity polymer; B — glycerol.

Laboratory lineage

bounds independence
Laboratory lineage is carried as an explicit dataset column because it bounds independence: Qi, Erincik, Jin, Ehrenfried and Koh share the UT Austin ecosystem (overlapping protocols, polymers and outcrop cores), against Vermolen et al. (2014, Shell), Clarke et al. (2016, Schlumberger), Irfan et al. (2021, UTP), Cottin et al. (2014, TotalEnergies) and the Daqing study. Four of the seven admitted studies are one lineage, and a fifth study of the same lineage sits in the Supportive tier; the statistical treatment exists because of this.

Evidence-unit classification and reasons

Appendix B · exclusion and support log
Classification rule, applied in order. First, does the unit contain or preserve an interpretable observation bearing on polymer elasticity, residual-oil displacement, porous-medium resistance or field accessibility? If not, it is Excluded. Second, does it satisfy the full matched-reference admission criteria? If so, it is Admitted. Third, can the observation still inform interpretation, risk of bias, carbonate applicability, mode contrast or experimental design without entering pooled or cell statistics? If so, it is Supportive; if not, it is Excluded. A unit reporting the same experiments as a more complete source is labelled a Merged duplicate and is never counted twice.

Domain-resolved design and reporting assessment

Table B.1 · seven admitted studies
L low concern, M some concern, H high concern, U unclear. A criterion is rated low concern only where it is satisfied for all admitted contrasts used in the relevant analysis; some concern where it holds for a subset, through an indirect proxy, or with incomplete reporting; high concern where it fails for the contrasts used; and unclear where the source does not provide sufficient information. No composite score is computed; the ten domains are not commensurable.
Elastic-versus-reference contrasts

Contrast dataset

All 49 elastic-versus-reference contrasts on one declared velocity basis (interstitial, frontal advance). Positive ΔSor means the elastic fluid desaturated further than its matched inelastic reference. Flood identifiers are dataset keys and are carried unaltered.
Prepared by Imad A. Adel

ΔSor against interstitial velocity

log velocity axis · dotted line = 1 ft/D cut · dashed line = 0.10 s.u.
Within the salinity-unconfounded tertiary set, every increment of at least 0.10 saturation units lies at 1 ft/D (0.3048 m/d) or above, five of the eight at exactly the boundary velocity. Across all 49 contrasts, thirteen increments reach 0.10 s.u., eight of them at the boundary.

The 49 contrasts

click a column header to sort
tertiary, salinity-unconfounded — the primary 32 at exactly 1.000 ft/D — boundary record salinity-confounded — excluded from the cell statistics
Two structural features bound the reading of any single record. In-core contrasts are chained: each elastic stage starts from its reference’s endpoint, so the recorded contrast is the elastic increment from a saturation the reference already set. Injection order is not constant across studies: in Jin coreflood 1 the elastic stage preceded its reference, is credited +0.110, and the glycerol stage injected after it removed a further 0.168 (0.238 to 0.070). Four Jin comparisons (J3, J6, J7, J11) carry no inelastic stage in their own cores and are admitted on the study-level reference; the dataset flags both features per comparison.
IRFAN21 contributes a single high-velocity comparison, and its admitted increment rests on 0.7 mL of recovered oil against a 62.33-mL pore volume, that is ΔSor = 0.011. The source does not report the collection-system accuracy or repeatability, so the significance of this increment cannot be established from the published record. It is retained at face value and flagged in the domain-resolved assessment rather than adjusted.
Mode and flow intensity

Velocity classifier

Each comparison is classified on interstitial velocity alone: high-intensity above the cut, low-intensity at or below it, applied as a strict inequality. Stage-level cells are descriptive context; the paired within-study contrast is the primary quantity. Both are recomputed here as the cut and the boundary rule are moved.
Prepared by Imad A. Adel

Classifier controls

tertiary, salinity-unconfounded · n = 32
How to useMove the cut or switch the rule; the readouts, the figure and the paired table recompute.
  1. Set the velocity cut with the slider. The primary cut is 1.0 ft/D; 0.5 and 2.0 ft/D are the reported regroupings.
  2. Choose the boundary rule: strict assigns vi > cut to the high cell (the primary rule), inclusive assigns vi ≥ cut.
  3. Read the paired estimator in the table below the figure: only studies carrying both cells enter it, and the count changes with the cut.

Hover for values; drag to zoom; use Reset axes in the figure toolbar, or double-click the plot.

Paired differencesstudy means, high minus low

What it showsRecords sitting at exactly the cut are counted in the boundary readout; at 1.0 ft/D five of the 32 comparisons sit there, so the stage-level ordering is a property of the boundary treatment as much as of the floods.

Paired within-study estimator — primary

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Each row is one laboratory compared against itself at two flow rates, holding laboratory, protocol, fluid systems and measurement practice fixed. Studies carrying only one cell form no paired difference and are excluded from the estimator.

Paired inference

t interval and leave-one-study-out
A study-resampled interval for the paired estimator is not derived: four clusters admit only 35 distinct resample combinations and cannot support a calibrated percentile interval. The paired inference rests on the t interval and the leave-one-out table. At the primary cut the interval does not constrain the effect at four studies, and the sign reverses only when QI17 is removed.
Study-resampling bootstrapstage-level high−low difference
Unpaired study-level comparisonmean of study means
The unpaired statistic mixes one-sided studies into the contrast and is retained as a confounded sensitivity. At the primary cut, five studies contribute a high cell and five a low cell, and only four contribute both.

Subset sensitivities

computed live at the selected cut
The ΔNc-matched subset reproduces the absence of separation, so restricting to capillary-number-matched pairs does not restore an ordering. The Grade-A-referenced subset holds a single comparison above the boundary at the primary cut, and no conclusion is drawn from it.

Stage-level leave-one-study-out

Table 3 · at the 1 ft/D cut
The stage-level difference moves between −0.025 and +0.009 and reaches approximate zero only when Erincik, the study holding the four boundary stages, is removed.

Reference-grade split

Table 4 · static
The large tertiary increments are glycerol-referenced (Erincik, Qi, Ehrenfried). Where the in-situ offset is recoverable from stage-wise pressure gradients and velocities it runs against the elastic stages: the in-core resistance ratio of the elastic stage to its same-core glycerol reference spans 1.16–2.11 across the six Erincik pairs, 0.44–5.0 across Qi and 1.00–1.07 across Jin. Part of the large glycerol-referenced increments can therefore be ordinary viscous displacement at an unmatched in-situ viscosity.

Superseded velocity-or-gradient classifier

Table S2 · labelled sensitivity
The earlier classification assigned a comparison to the high cell when the interstitial velocity exceeded 1 ft/D or the pressure gradient reached 10 psi/ft (226.2 kPa/m). It is retained only as a sensitivity, because the pressure gradient is in part a response to the elastic resistance under test rather than an imposed condition, and because it groups stages that differ in velocity by an order of magnitude. It does not feed any statistic elsewhere on this site.
Field-velocity application of Eq. 7

Injectivity bounds

Field relevance is bounded with the radial velocity around an unfractured vertical injector. Eq. 7 gives the radius r* inside which a given interstitial onset velocity is exceeded at porosity φ. This is a conservative single-layer bound; fractures, thin high-flux layers and horizontal-well geometries extend it.
Prepared by Imad A. Adel

Onset-radius calculatorSAMPLE DATA

Eq. 7
How to useSet the rate, porosity and onset velocity; the radius, the figure and the table recompute.
  1. Set q/h, the injection rate per metre of completed interval; the page opens at 10 m3/d per metre.
  2. Set porosity; radii scale as 1/φ.
  3. Enter the onset velocity, the interstitial velocity at which the fluid’s porous-medium resistance begins to rise, measured for the fluid–rock system in question. Porosity and onset velocity open at SAMPLE values.

The chart traces r* against q/h at the entered onset, with the open marker at the selected rate. Hover the curve for values; drag to zoom; use Reset axes in the figure toolbar, or double-click the plot.

Onset radius against rate per intervallog–log · entered onset velocity

Onset radii—
Rows are fixed rates; the highlighted row is the selected rate. Radii scale as 1/φ and as 1/vonset.

Screening statement

what the bound does and does not do
Viscoelastic Sor credit, where claimed at all, belongs only to the reservoir volume that the radial bound or a fracture / thin-bed equivalent places above onset. The unfractured single-layer geometry is a screening idealisation. The bound delimits where elastic flow resistance is possible; it does not locate desaturation.
The field-velocity argument was raised in Seright and Wang (2023) and developed by Azad and Seright (2025), whose deep-pattern analysis (0.01–0.2 ft/D typical, under one percent of pattern volume above onset) and exceptions (close spacing, ≈ 1.7 ft/D at Pelican-Lake-type geometry; Daqing throughput of 0.14–0.20 PV/yr at 150–250-m spacing) are cited here as published results; the calculator above applies the same bound to an entered onset velocity.
Eq. 7 is evaluated directly: r* = q/(2π·h·φ·vonset), with the interstitial onset converted at 0.3048 m/d per ft/D. Porosity and onset velocity open at SAMPLE values chosen for illustration; neither is a measurement. The onset velocity has to be measured for the fluid–rock system in question; the calculator does not supply one. The bound assumes a single unfractured layer around a vertical injector; fractures, thin high-flux layers and horizontal wells extend the region above onset.
Proposed minimum reporting checklist

Proposed minimum reporting checklist

The screen that reduced 39 published studies to seven usable studies is itself the clearest statement of what the literature lacks. It is restated here as a prospective checklist: a future coreflood that satisfies it enters this framework directly; one that does not cannot be placed on a common basis with the admitted set.
Prepared by Imad A. Adel

R1–R8

each item with its motivating defect in the screened corpus
    A coreflood satisfying R1–R8 supplies a contrast the present record cannot: a matched-viscosity inelastic reference in the same core, at matched capillary number, at constant salinity, on a declared velocity basis, with endpoint saturations measured twice and the saturation-dependent water relative permeability reported. One compliant flood pair would add evidence the existing record cannot supply under any re-analysis.
    The carbonate gap and the proposed experiment

    Proposed two-core carbonate experiment

    No carbonate study satisfying the admission criteria was identified in the screened corpus at the 3 August 2026 search cutoff; the admitted set is entirely sandstone and sandpack, and the closest near-miss fails on in-situ reference matching and constant-salinity grounds. The proposed matched-reference experiment is specified by the checklist of Section 05; its velocity ladder brackets the onset measured for the fluid–rock system under test rather than the sandstone threshold.
    Prepared by Imad A. Adel
    Elastic flow resistance is a necessary condition for any viscoelastic desaturation mechanism, not a demonstration of it; whether desaturation accompanies the onset is the question the proposed experiment is designed to answer.

    Core 1 — matched-reference sequence

    checklist item per element

    Velocity schedule

    ascending then descending, bracketing the system’s onset range
    Schematic. The rung velocities are set from the onset range measured for the fluid–rock system under test, with rungs below and above it. The descending arm separates progressive retention from rate response, which an ascending-only ladder cannot do.

    Core 2 — order-reversal control

    the discriminating control

    Pre-registered outcomes

    read against the competing hypotheses

    Operating bounds

    quantified constraints on execution
    A single core pair resolves the mechanism only for the system tested and does not establish a population effect; the pre-registered outcomes are stated so the result enters the checklist framework as one study, and the checklist is written so further studies accumulate on a common basis.
    Reference · Model and equations

    Model & equations

    Every convention, constant and estimator behind the numbers on this site. Two velocity bases appear: the interstitial basis of Eq. 1, Eq. 2 and Eq. 5, and the superficial (Darcy) flux u = φ·vi on which the shear-rate coefficient of Eq. 3 and the radial bound of Eq. 7 are defined. Every reported value states its basis.
    Prepared by Imad A. Adel

    Model equations

    Eq. 1 – Eq. 7

    Estimators computed in this page

    single source of truth

    Assumptions and input parameters

    carried from the deposited dataset

    Extensional capillary number — implementation verification

    Table S1 · against Azad and Trivedi (2021), Table 3
    The extensional capillary number is prior art and is applied unchanged. The reimplementation reproduces the source pore-scale viscosities to better than 0.4% on each source’s own velocity-reporting convention, which verifies implementation consistency only. It does not validate the physical model, and it does not establish that Nce resolves the study-level contradiction.
    Worked example (Azad and Trivedi 2021, Experiment 2; source inputs). k = 2,100 md, φ = 0.22, σi = 17.3 mN/m, u = 0.2 ft/D as reported (vi = 0.909 ft/D), 1,800-ppm HPAM (μp0 = 110 cp, λ = 0.1 s, n = 0.6, τext = 0.352 s, μmax = 560,000 cp, n2 = 3.57). Eq. 3 with C = 6 gives γ̇ = 4.98 s−1; Eq. 4 gives μapp,pore = 25,559 cp (shear branch 105 cp; strain-hardening branch 25,454 cp) against 25,504 cp reported; Eq. 5 on the reported velocity gives Nce = 1.04×10−3 against 1.0×10−3. The corresponding corpus flood is CF3-HPAM1800-lo.

    References

    SPE style · metadata from Crossref, corrected only from publisher records
    1. Abrams, A. 1975. The Influence of Fluid Viscosity, Interfacial Tension, and Flow Velocity on Residual Oil Saturation Left by Waterflood. Society of Petroleum Engineers Journal 15 (5): 437–447. SPE-5050-PA. https://doi.org/10.2118/5050-PA.
    2. Alfazazi, U., Chacko Thomas, N., Al-Shalabi, E.W., and AlAmeri, W. 2021. Investigation of Oil Presence and Wettability Restoration Effects on Sulfonated Polymer Retention in Carbonates Under Harsh Conditions. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, 15–18 November 2021. SPE-207892-MS. https://doi.org/10.2118/207892-MS.
    3. Azad, M.S., and Seright, R.S. 2025. Are Field Polymer Enhanced Oil Recovery Projects Reaping the Benefits of Residual Oil Saturation Reduction Due to Polymer Viscoelasticity? SPE Journal 30 (6): 3792–3809. SPE-223155-PA. https://doi.org/10.2118/223155-PA.
    4. Azad, M.S., and Trivedi, J.J. 2019. Quantification of the Viscoelastic Effects During Polymer Flooding: A Critical Review. SPE Journal 24 (6): 2731–2757. SPE-195687-PA. https://doi.org/10.2118/195687-PA.
    5. Azad, M.S., and Trivedi, J.J. 2021. Quantification of Sor Reduction during Polymer Flooding Using Extensional Capillary Number. SPE Journal 26 (3): 1469–1498. SPE-204212-PA. https://doi.org/10.2118/204212-PA.
    6. Azad, M.S., and Trivedi, J. 2023. Quantification of polymer viscoelastic effects on SOR reduction using modified capillary. US Patent No. 11,761,331 B2, issued 19 September 2023.
    7. Barri, A., Azad, M.S., Al-Shehri, D., Ayirala, S.C., Patil, S., Al-Hamad, J., Abdullah, E., and Al Abdrabalnabi, R. 2023. Is There a Viscoelastic Effect of Low-MW HPAM Polymers on Residual Oil Mobilization in Low-Permeability Rocks at a Darcy Velocity of 0.2 ft/Day? Energy & Fuels 37 (14): 10188–10199. https://doi.org/10.1021/acs.energyfuels.3c00955.
    8. Chatzis, I., and Morrow, N.R. 1984. Correlation of Capillary Number Relationships for Sandstone. Society of Petroleum Engineers Journal 24 (5): 555–562. SPE-10114-PA. https://doi.org/10.2118/10114-PA.
    9. Clarke, A., Howe, A.M., Mitchell, J., Staniland, J., and Hawkes, L.A. 2016. How Viscoelastic-Polymer Flooding Enhances Displacement Efficiency. SPE Journal 21 (3): 675–687. SPE-174654-PA. https://doi.org/10.2118/174654-PA.
    10. Cottin, C., Bourgeois, M., Bursaux, R., Jimenez, J., and Lassalle, S. 2014. Secondary and Tertiary Polymer Flooding on Highly Permeable Reservoir Cores: Experimental Results. Paper presented at the SPE EOR Conference at Oil and Gas West Asia, Muscat, Oman, 31 March–2 April 2014. SPE-169692-MS. https://doi.org/10.2118/169692-MS.
    11. Dafaalla, M., Azad, M.S., Ayirala, S., Alotaibi, M., Fahmi, M., Saleh, S., Al Shehri, D., and Mahmoud, M. 2025. Potential of polymer’s viscosity and viscoelasticity for accessible oil recovery during low salinity polymer flooding in heterogeneous carbonates. Fuel 379: 133008. https://doi.org/10.1016/j.fuel.2024.133008.
    12. Dhahir, D., Azad, M.S., Ayirala, S., Seright, R.S., Al Shehri, D., and Alotaibi, M. 2026. Examining the Desaturation Potential of Low and High-Salinity Viscoelastic Polymer Solutions at High Salinity and High Temperature Carbonate Reservoir Conditions. Paper presented at the SPE Improved Oil Recovery Conference, Tulsa, Oklahoma, USA, 21–23 April 2026. SPE-231553-MS. https://doi.org/10.2118/231553-MS.
    13. Du, Y., Xu, K., Mejia, L., and Balhoff, M. 2021. A Coreflood‐on‐a‐Chip Study of Viscoelasticity's Effect on Reducing Residual Saturation in Porous Media. Water Resources Research 57 (8): e2021WR029688. https://doi.org/10.1029/2021WR029688.
    14. Erincik, M.Z., Qi, P., Balhoff, M.T., and Pope, G.A. 2017. New Method to Reduce Residual Oil Saturation by Polymer Flooding. Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 9–11 October 2017. SPE-187230-MS. https://doi.org/10.2118/187230-MS.
    15. Erincik, M.Z., Qi, P., Balhoff, M.T., and Pope, G.A. 2018. New Method To Reduce Residual Oil Saturation by Polymer Flooding. SPE Journal 23 (5): 1944–1956. SPE-187230-PA. https://doi.org/10.2118/187230-PA.
    16. Fabbri, C., Al Saadi, H.A., Wang, K., Maire, F., Romero, C., Cordelier, P., Prinet, C., Jouenne, S., Garnier, O., Xu, S., Leon, J.M., Baslaib, M., and Masalmeh, S. 2021. Polymer Injection to Unlock Bypassed Oil in a Giant Carbonate Reservoir: Bridging the Gap Between Laboratory and Large Scale Polymer Project. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, 15–18 November 2021. SPE-208121-MS. https://doi.org/10.2118/208121-MS.
    17. Guo, H., Song, K., and Hilfer, R. 2022. A Brief Review of Capillary Number and its Use in Capillary Desaturation Curves. Transport in Porous Media 144 (1): 3–31. https://doi.org/10.1007/s11242-021-01743-7.
    18. Huh, C., and Pope, G.A. 2008. Residual Oil Saturation from Polymer Floods: Laboratory Measurements and Theoretical Interpretation. Paper presented at the SPE Symposium on Improved Oil Recovery, Tulsa, Oklahoma, U.S.A., 19–23 April 2008. SPE-113417-MS. https://doi.org/10.2118/113417-MS.
    19. Irfan, M., Stephen, K.D., and Lenn, C.P. 2021. An experimental study to investigate novel physical mechanisms that enhance viscoelastic polymer flooding and further increase desaturation of residual oil saturation. Upstream Oil and Gas Technology 6: 100026. https://doi.org/10.1016/j.upstre.2020.100026.
    20. Jain, H., Azad, M.S., Ayirala, S., Mahmoud, M., Al Shehri, D., and Fahmi, M. 2026. Viscoelasticity vs. viscosity: what dominates the Sor reduction at shear thinning flux in low permeable limestone cores at low salinity polymer flood conditions? Results in Engineering 30: 110897. https://doi.org/10.1016/j.rineng.2026.110897.
    21. Jameel, M.F., Azad, M.S., Adebayo, A.R., Ayirala, S., Al Shehri, D., and Mahmoud, M. 2026. IFT Vs. Viscoelasticity: What is the Most Potent Microscopic Light Oil Recovery Mechanism in Water-Wet High-Permeable Formations? Paper presented at the SPE Improved Oil Recovery Conference, Tulsa, Oklahoma, USA, 21–23 April 2026. SPE-231475-MS. https://doi.org/10.2118/231475-MS.
    22. Jiang, H., Wu, W., Wang, D., Zeng, Y., Zhao, S., and Nie, J. 2008. The Effect of Elasticity on Displacement Efficiency in the Lab and Results of High Concentration Polymer Flooding in the Field. Paper presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 21–24 September 2008. SPE-115315-MS. https://doi.org/10.2118/115315-MS.
    23. Jin, J., Qi, P., Mohanty, K., and Balhoff, M. 2020. Experimental Investigation of the Effect of Polymer Viscoelasticity on Residual Saturation of Low Viscosity Oils. Paper presented at the SPE Improved Oil Recovery Conference, Virtual, 31 August–4 September 2020. SPE-200414-MS. https://doi.org/10.2118/200414-MS.
    24. Koh, H., Lee, V.B., and Pope, G.A. 2018. Experimental Investigation of the Effect of Polymers on Residual Oil Saturation. SPE Journal 23 (1): 1–17. SPE-179683-PA. https://doi.org/10.2118/179683-PA.
    25. Laudon, S., Balhoff, M., and Mohanty, K. 2024. The Effect of Polyethylene Oxide on Residual Oil Saturation of Low Permeability Carbonates. Paper presented at the SPE Improved Oil Recovery Conference. SPE-218150-MS. https://doi.org/10.2118/218150-MS.
    26. Laudon, S., Balhoff, M., and Mohanty, K. 2026. The effect of polyethylene oxide polymer injection on residual oil saturation of Indiana limestone. Geoenergy Science and Engineering 264: 214549. https://doi.org/10.1016/j.geoen.2026.214549.
    27. Masalmeh, S., AlSumaiti, A., Gaillard, N., Daguerre, F., Skauge, T., and Skauge, A. 2019. Extending Polymer Flooding Towards High-Temperature and High-Salinity Carbonate Reservoirs. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, 11–14 November 2019. SPE-197647-MS. https://doi.org/10.2118/197647-MS.
    28. Qi, P., Ehrenfried, D.H., Koh, H., and Balhoff, M.T. 2017. Reduction of Residual Oil Saturation in Sandstone Cores by Use of Viscoelastic Polymers. SPE Journal 22 (2): 447–458. SPE-179689-PA. https://doi.org/10.2118/179689-PA.
    29. Qi, P., Lashgari, H., Luo, H., Delshad, M., Pope, G., and Balhoff, M. 2018. Simulation of Viscoelastic Polymer Flooding - From the Lab to the Field. Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, 24–26 September 2018. SPE-191498-MS. https://doi.org/10.2118/191498-MS.
    30. Sandengen, K., Melhuus, K., and Kristoffersen, A. 2017. Polymer “viscoelastic effect”; does it reduce residual oil saturation. Journal of Petroleum Science and Engineering 153: 355–363. https://doi.org/10.1016/j.petrol.2017.03.029.
    31. Seright, R.S., and Wang, D. 2023. Polymer flooding: Current status and future directions. Petroleum Science 20 (2): 910–921. https://doi.org/10.1016/j.petsci.2023.02.002.
    32. Seright, R.S., Azad, M.S., Abdullah, M.B., and Delshad, M. 2023. Effect of Residual Oil Saturation and Salinity on HPAM Rheology in Porous Media. Paper presented at the SPE Annual Technical Conference and Exhibition, San Antonio, Texas, USA, 16–18 October 2023. SPE-215060-MS. https://doi.org/10.2118/215060-MS.
    33. Vermolen, E.C.M., van Haasterecht, M.J.T., and Masalmeh, S.K. 2014. A Systematic Study of the Polymer Visco-Elastic Effect on Residual Oil Saturation by Core Flooding. Paper presented at the SPE EOR Conference at Oil and Gas West Asia, Muscat, Oman, 31 March–2 April 2014. SPE-169681-MS. https://doi.org/10.2118/169681-MS.
    34. Wang, D., Cheng, J., Yang, Q., Gong, W., and Li, Q. 2000. Viscous-Elastic Polymer Can Increase Microscale Displacement Efficiency in Cores. Paper presented at the SPE Annual Technical Conference and Exhibition, Dallas, Texas, 1–4 October 2000. SPE-63227-MS. https://doi.org/10.2118/63227-MS.
    35. Wang, D., Cheng, J., Xia, H., Li, Q., and Shi, J. 2001a. Viscous-Elastic Fluids Can Mobilize Oil Remaining after Water-Flood by Force Parallel to the Oil-Water Interface. Paper presented at the SPE Asia Pacific Improved Oil Recovery Conference, Kuala Lumpur, Malaysia, 8–9 October 2001. SPE-72123-MS. https://doi.org/10.2118/72123-MS.
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    Cited in the text but not listed, because no DOI for them could be verified against Crossref: Ehrenfried (2013) and Wreath (1989), theses; Koh (2015), dissertation; Humphry et al. (2014). Seright et al. (2011) is named in the screening register as inventoried and not cited, and is not listed.
    Reference · Nomenclature

    Nomenclature

    Symbols, Greek symbols and abbreviations used across this page, with the reporting unit of each quantity and its SI equivalent where the two differ.
    Prepared by Imad A. Adel
    SymbolsRoman▶
    Greek symbols▶
    Abbreviations▶