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Record W2496728102 · doi:10.2118/2004-058

Bottom-Water Reservoirs, Simulation Approach

2004· article· en· W2496728102 on OpenAlexafffundabout
K. Elkaddifi, Ezeddin Shirif, M. Ayub, Amr Henni

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Regina
FundersPetroleum Technology Research Centre
KeywordsPetroleum engineeringReservoir simulationGeologyComputer science

Abstract

fetched live from OpenAlex

Abstract In many light or moderately viscous oil reservoirs in Saskatchewan and Alberta, a high inactive water saturation zone of varying thickness and extent ("bottom-water zone") occurs in communication with the oil zone above. As a result, the primary production period is short, and water breakthrough occurs very early in the life of the reservoir. Later, during the secondary recovery stage, such a zone can have an adverse effect on the waterflood efficiency. This Paper addresses the problem of waterflooding such reservoirs. This study was directed towards reducing water mobility in the bottom-water zone for more efficient oil displacement. A commercial simulator (CMG/IMAX) was used to conduct this study. Polymer in various concentrations was used as a blocking agent in the bottom-water zone and as a mobility control agent in the oil zone. Different strategies were investigated to reduce the water mobility in the bottom-water zone and improve the vertical sweep efficiency. The variables examined were: permeability ratio, oil viscosity, relative waterto- oil layer thickness, polymer concentration, injection rate and injection point, as well as the effect of vertical and horizontal injection and production well combinations. The results showed that minimizing crossflow between layers by blocking the bottom-water zone could increase oil recovery. It was also found that for an unfavorable mobility ratio, as the injection rate increases the ultimate oil recovery increases. The injection of a polymer solution had a favorable impact on waterflood performance. Moreover, the worse the conventional waterflood performance was, the more effective the polymer was as a mobility and blocking control agent. The use of horizontal wells showed slightly better oil recovery over vertical wells in a conventional waterflood of reservoirs under bottom-water conditions. In addition, some certain well combinations (horizontal production and vertical injection) gave better oil recovery due to the increase in the swept area. Introduction The efficient and economic recovery of oil from reservoirs under bottom-water conditions is recognized as a formidable task. High water cuts and rapidly decreasing oil rates early in the production life of such reservoirs have in many instances prompted their suspension or abandonment at very low levels of oil recovery. Reservoir characteristics and rock and fluid properties combine to yield the single most important parameter (mobility ratio) in a waterflood. A number of chemicals such as polymers, emulsions, biopolymers, foam and carbon dioxideactivated silica gel have been used to control the mobility ratio. One of the oldest techniques to control mobility of water in waterflooding is the use of polymers. This control agent was shown to be effective in the early sixties by Pye1. He performed numerous field and laboratory studies of polymer flooding using polyacrylamide solutions. It was observed experimentally that the viscosity of the water-soluble polymer solutions measured in the formation sample departed markedly from that obtained using a viscometer. He quantified the unusual departure of the measured values from the expected response as the resistance factor. It was assumed that the permeability was constant.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.055
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.231
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2004
Admission routes3
Has abstractyes

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