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Record W1978722531 · doi:10.2118/01-02-03

Design and Implementation of a Successful Vertical Tertiary Hydrocarbon Miscible Flood

2001· article· en· W1978722531 on OpenAlexaffabout
D.K. Fong, A. Laflamme, J.P. Grenon, Benjamin Weaver, F.J. McIntyre, S.G. Stetski

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsPetroleum engineeringFlood mythGeologyOil in placeHydrocarbonOil fieldFlooding (psychology)PetroleumEnvironmental sciencePaleontologyChemistryGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Tertiary hydrocarbon miscible flooding is an important enhanced oil recovery process for revitalizing mature, waterflooded, carbonate reservoirs. Over the last 16 years Husky Oil has developed extensive expertise in successfully applying tertiary vertical gravity-stabilized hydrocarbon miscible floods in the Rainbow Basin, Alberta. The combined incremental oil reserves of four major tertiary miscible floods (Keg River B, F, and South E and G pools) are expected to be 25 ? 106 m3. This paper presents the design, operation, and three-year actual field performance of a vertical tertiary hydrocarbon miscible flood in the northwest lobe of the Rainbow Keg River F pool. Oil production from the northwest lobe has improved significantly, from less than 100 m3/cd during the first few months of miscible flooding to more than 200 m3/cd over the past year. This paper discusses major design factors and a sound corresponding operating strategy that have ultimately resulted in the technical and economical success of the vertical tertiary miscible flood scheme. These factors include:Selection of a minimum operating pressureOptimal solvent compositionSolvent slug sizeCritical frontal advancement rate, andProper placement of solvent slug. Introduction Tertiary hydrocarbon miscible flooding is an important enhanced oil recovery (EOR) process for revitalizing mature, water-flooded, carbonate reservoirs. Husky Oil Operations Limited, over the last 16 years, has developed extensive expertise in successfully applying tertiary vertical gravity-stabilized hydrocarbon miscible floods in the Rainbow Basin in Northwest Alberta. The combined incremental oil reserves of four major tertiary miscible floods (Keg River B, F, and South E and G pools) due to tertiary miscible flooding are expected to be 25 ? 106 m3. Applicability of a tertiary hydrocarbon miscible flood has been evaluated and found to be technically feasible and economically attractive for the Rainbow Keg River (RKR) F pool. The tertiary miscible scheme was proposed to be implemented first in the northwest lobe of RKR F pool, since this region is more geologically and structurally isolated and has the thickest remaining oil bank among the lobes of F pool (Figure 1). Expansion to the restof the pool would be considered when more NGL becomes available. This paper presents the design, operation, and three-year actual field performance of a successful vertical tertiary hydrocarbon miscible flood in the northwest lobe of Rainbow Keg River F pool. FIGURE 1: Rainbow Keg River F Pool structure map. Available In Full Paper. Reservoir Depletion History As was discovered in March 1966, Rainbow Keg River F pool had four separate gas caps and one continuous oil zone. The original gas-oil contacts were all at about 1,310 m sub-sea (mSS), and the oil-water contact (OWC) was at 1,408 mSS, giving an oil zone thickness of 98 m, containing up to 40 E6 m3 of original oil in place (OOIP). The oil had a density of 654 kg/m3, a viscosity of 0.268 cp and was saturated at reservoir conditions of 87 °CDATA[C and 17,457 kPag.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.365

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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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 designSimulation or modeling
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

Citations2
Published2001
Admission routes2
Has abstractyes

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