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Record W2050154174 · doi:10.2118/06-02-02

Application of In-Depth Gel Placement for Water and Carbon Dioxide Conformance Control in Carbonate Porous Media

2006· article· en· W2050154174 on OpenAlexafffund
L. Taabbodi, K. Asghari

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
FundersPetroleum Technology Research Centre
KeywordsPolyacrylamideSodium carbonateCarbon dioxideCarbonatePorous mediumChemical engineeringSupercritical carbon dioxidePermeability (electromagnetism)PolymerChemistryChromiumPorosityChromatographySodiumMaterials sciencePolymer chemistryOrganic chemistryMembrane

Abstract

fetched live from OpenAlex

Abstract This paper presents the results of an investigation of the application of gel placement in an attempt to reduce the effective permeability of a carbonate porous medium to water and supercritical carbon dioxide, as encountered in the CO2 flooding of carbonate reservoirs. Three gel systems based on a high and a low molecular weight polyacrylamide polymer with chromium(III), as crosslinker, were used for this study. Since sodium lactate is commonly used for increasing gelation time at elevated temperatures, experiments were conducted by adding sodium lactate to the gel solution with a ratio of polymer to sodium lactate equal to one. The higher molecular weight polyacrylamide gel system was composed of 7,200 ppm Alcoflood 935 and 300 ppm Cr(III), while the other gel system tested was composed of 5% low molecular weight polyacrylamide (Alcoflood 254S) with a ratio of 1:12 chromium(III)-acetate to polymer as crosslinker. Experiments were conducted at 8,274 KPa and 40 °C with and without the presence of residual oil. Performance and stability of the above gel systems for reducing the permeability of the carbonate medium to the injected water and carbon dioxide was tested in a series of flow experiments by alternately injecting several pore volumes of water and carbon dioxide into the porous media in several cycles. The porous medium used was crushed carbonate with an initial permeability of over 9.86 µm2. For all experiments, the presence of Sor led to lower residual resistance factors (RRF). Nevertheless, RRFs were between 100 and a few thousands for all experiments conducted. The results obtained are a clear indication of the effectiveness of these gel systems for conformance control purposes during carbon dioxide flooding projects in carbonate reservoirs. Introduction From the pore-scale point of view, dense carbon dioxide is an ideal displacement fluid for many crude oils. Carbon dioxide gains miscibility with oil and is able to achieve very high recovery efficiencies at reservoir pressures near or above minimum miscibility pressure. However, even when pressure conditions for miscibility are met, this high microscopic sweep efficiency is not often observed in field tests. The combined effect of heterogeneity of the reservoir and the low viscosity of the injected carbon dioxide leads to the viscous fingering of carbon dioxide through fractures, channels, or high-permeable streaks in the reservoir. This causes early breakthrough of injected carbon dioxide into production wells, which reduces oil recovery efficiency. Different techniques have been investigated for reducing channelling through fractures or high-permeability zones. One such technique is in-depth gel placement. This process has been applied successfully in many reservoirs, resulting in fracture sealing, water and gas shut-off, and permeability modification. The objective of gel placement is to reduce fingering of the injected fluid through fractures or high-permeability zones of formation while minimizing gel penetration in hydrocarbon bearing regions of the reservoir. The main advantages of using gels over the other methods, such as cements or mechanical plugs, is their flexibility for pumping without a workover rig, high control of setting time, a deeper penetration into the formation, ease of cleaning, and an easy removal from the wellbore by water recirculation(1, 2).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
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 head0.003
GPT teacher head0.182
Teacher spread0.179 · 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 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

Citations16
Published2006
Admission routes2
Has abstractyes

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