Innovative 3D Modelling and Polymer Injection Techniques in Heavy Oil Reservoirs with “Chinese Dragon” Wells
Bibliographic record
Abstract
Summary Manantiales Behr North fields bear heavy oil (600 to 800 cp) in thin fluvial reservoirs. It has been traditionally exploited using vertical wells and historically had a low primary recovery factor. High OPEX associated with surface treatment to reduce oil viscosity impacts current operations. To improve heavy oil production, it was necessary to consider a different development strategy. Cyclic steam injection was considered, but heat loss to the reservoir, high steam generation costs and associated CO2 emissions, discouraged its implementation. Instead, polymer injection in horizontal wells emerged as a more viable alternative, offering better control over fluid mobility and higher recovery rates. This technique has been successfully implemented in other heavy oil regions, such as Canada, and is particularly suited to the fluvial nature of the La Paulina reservoir. The well design, which includes long horizontal branches up to 1000 meters with sinusoidal or “Chinese dragon” trajectories, helps avoid water channeling and improves vertical connectivity, optimizing polymer injectivity. To assess the feasibility and risks of this approach, multiple 3D reservoir models were developed, considering high permeability contrasts, fine-scale heterogeneities, and tortuosity. Two main strategies were analyzed based on the availability of PIU (Polymer Injection Units): Scenario 1: Begin polymer injection in two pilots. Zone A using horizontal wells for both injection and production and Zone B combining horizontal injectors and vertical producers. Scenario 2: Drilling primary production horizontal wells for three years, followed by polymer injection, drilling horizontal infill wells to complete patterns. In both scenarios, the well spacing proposed is 100 meters, with a polymer concentration of 5000 ppm and a total injection rate of 2000 m³/day. The project success could lead to polymer flooding expansion across other heavy oil field blocks. By starting in an area with proven oil reserves, the project seeks to optimize oil recovery while minimizing risks. Simulation results indicate a potential increase in the RF from 6% up to 14%–29%. Although horizontal well technology for polymer injection is well established, this would be the first experience in Argentina. The combination of horizontal polymer injection and a sinusoidal well design which aims to bypass reservoir heterogeneity, presents a promising solution for improving recovery rates in thin, layered heavy oil reservoirs like La Paulina. Careful model-based planning and a staged development approach ensure that risks are minimized and the chances for success are maximized.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".