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Record W2018808295 · doi:10.2118/04-12-04

Alkaline/Surfactant/Polymer (ASP) Flood Potential in Southwest Saskatchewan Oil Reservoirs

2004· article· en· W2018808295 on OpenAlexafffundabout
Mingzhe Dong

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsSaskatchewan Research Council (Canada)
FundersPetroleum Technology Research Centre
KeywordsPulmonary surfactantPetroleum engineeringPilot testOil in placeEnhanced oil recoveryFlooding (psychology)Flood mythSurface tensionEnvironmental scienceGeologyChemistryPetroleumGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Most of the medium oil reservoirs in southwest Saskatchewan are in thin pay zones of less than 8 m. Primary and waterflood methods have reached more than 80% of their estimated oil recovery potential. These medium oil reservoirs are basically untouched by enhanced oil recovery techniques. An initial study was conducted to assess the suitability of Alkaline/Surfactant/Polymer (ASP) flooding for southwest Saskatchewan reservoirs. On the basis of screening criteria in the literature, the region's reservoir conditions, except for some of the formation types, are favourable for ASP flooding. If only sandstone formations are considered for this process, about 49% of the pools in the region are good candidates for ASP flooding. Extensive oil/water interfacial tension and viscosity measurements were taken using screening criteria for surfactant, alkaline, and polymers. A series of sandpack flood tests were conducted in sandpacks to evaluate ASP flooding for the oil. A tertiary oil recovery of 39% IOIP (72% ROIP) was obtained for the test using all three chemicals. These sandpack flood test results showed that a synergistic enhancement among the chemicals did occur in the ASP system for the medium oil with a very low acid number. The results also indicated that, for a medium oil, mobility control was essential and selection of the right surfactant was important. Introduction Oil reservoirs located in southwest Saskatchewan, with 3.1 billion barrels of proven oil, are characterized by thin pay (2 to 8 m in thickness) and shaley sand. The estimated oil recovery by primary and secondary methods from these reservoirs is about 25% initial oil in place (IOIP)(1). Waterfloods in most of these reservoirs have experienced early water breakthrough and high water cut due to the high oil-to-water viscosity ratio. For some of these reservoirs, waterfloods have nearly reached their economic limit. For achieving additional oil recovery and subsequent financial benefits, the development of an enhanced oil recovery technique is essential. Chemical-enhanced oil recovery methods mainly include micellar/polymer flooding, alkaline flooding, polymer flooding, and combinations of two or all of the three methods. Extensive studies of these processes have found that successful chemical flooding needs to be able to efficiently lower the oil/water interfacial tension and to have very good mobility control. The displacement mechanism of an ASP flood is similar to that of micellar/polymer flooding except that much of the surfactant is replaced by low-cost alkali. Therefore, the overall cost is lower even though the chemical slugs can be larger. Polymer is usually incorporated in the larger, dilute slug. It has been recognized that oil recovery can be greatly improved by the synergism of chemicals used in the ASP formulations. ASP processes are also being tested in the field. A field-wide project in Wyoming reports costs of US$10 to $22/tonne (US$1.6 – 3.5/bbl) of incremental oil produced(2). The economic analysis of two ASP pilot tests in the Daqing oil field, China, showed that the chemical cost was US$21 to $28/tonne (US$3 – 4/bbl) of incremental oil produced(3).

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 categoriesMeta-epidemiology (narrow)
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 score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.004
GPT teacher head0.188
Teacher spread0.183 · 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.

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

Citations31
Published2004
Admission routes3
Has abstractyes

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