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Record W4387447165 · doi:10.2118/215041-ms

Case Study of Successful Pilot Polymer Flooding to Improve the Recovery of Lloydminster Heavy Oil Reservoir- West Central Saskatchewan

2023· article· en· W4387447165 on OpenAlexaffabout
Ivan Ulovich, Abdulmohsin Imqam, Juan Arias de Reyna Martínez, Ahmed Aljubori, Rakeshkumar Rathod

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2023
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsCenovus Energy (Canada)
Fundersnot available
KeywordsPetroleum engineeringEnhanced oil recoveryEnvironmental scienceOil productionProduced waterOil fieldOil in placeFlood mythPilot testWater injection (oil production)Flooding (psychology)GeologyPetroleum

Abstract

fetched live from OpenAlex

Abstract The Lloydminster Heavy Oil Block is the main source of Canada's conventional heavy oil production. The most common methods of recovery in this area are primary production, waterflooding, and chemical-enhanced oil recovery (EOR) such as polymer flooding. Although heavy oil waterfloods could be relatively successful if managed properly, their production and economic efficiencies are often challenging due to quick water breakthrough followed by a steep decline in oil production. Beliveau (2009) showed that over 50% of oil produced from such water flood projects are typically produced at water cuts greater than 90%, which would increase water processing costs. The objective of this study is to outline the implementation of a successful polymer flood project in Lloydminster Heavy Oil Block that includes the production and injection performance of the pilot. It also describes the steps of selecting the appropriate polymer type based on reservoir rock properties, water quality, and other main parameters for the optimal polymer selection. An anionic polymer candidate provided by ZL EOR Chemical Ltd. was selected for the project. The field under study is in the province of Saskatchewan and producing from the Lloydminster sandstone. Initially, the field was produced under a line drive waterflood with horizontal wells. The reservoir has a live oil viscosity of about 2,600 cP at downhole temperature of 21.5°C and the average clean-sand permeability of 1,500 mD. In April 2018, a polymer flood pilot was introduced as a primary recovery method with continuous polymer injection at ~25 cP (~2000 ppm polymer concentration). Injection rates varied from 30 to 50 m3/d/well, based on the target injection volume of 5 to 10% of effective pore volume (PV) per year. As a result, field water cut has decreased and stabilized at ~65%, while oil production rate has remained relatively constant at ~40 m3/d for over five years with no signs of polymer breakthrough. Production performance from the beginning of the polymer flood demonstrates the efficiency of this EOR method, thereby providing valuable insights into the first primary polymer flood project in the Lloydminster Heavy Oil Block.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.267
Teacher spread0.243 · 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 designObservational
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

Citations3
Published2023
Admission routes2
Has abstractyes

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