An Approach to Model CHOPS (Cold Heavy Oil Production with Sand) and Post-CHOPS Applications
Bibliographic record
Abstract
ABSTRACT Due to its lower cost, the cold heavy oil production with sands (CHOPS) method is becoming more popular, not only in Canada where it originated, but also in many other countries including Venezuela, Kuwait, Russia and China. However, this method has several practical limitations. It continuously changes the geo-mechanical and petro-physical properties of the reservoir due to the sand produced, resulting in high permeability channels known as wormholes. Moreover, the method has a low oil recovery factor of 5 to 15 % and this entails further recovery techniques. Thermal methods after CHOPS are not usually favorable due to heterogeneity and reservoir instability. In addition, the CHOPS method is typically applied in thin formations in which heating by injected steam is characteristically inefficient. Solvent injection possesses similar problems caused by heterogeneity and cost. An option could be the hybrid application of steam/solvent. Assessment of this technique first requires a realistic modeling of the CHOPS application. Due to dynamic changes in reservoir properties, no valid model is yet available to accurately simulate CHOPS production. Our main focus in this paper is to investigate efficient EOR/IOR methods after CHOPS. To achieve this, we first propose a partial-dual porosity approach coupled with algorithms for wormhole generation to create a realistic static reservoir model. After generating fractal wormhole patterns of different kinds using a diffusion limited aggregation (DLA) algorithm, they were introduced into a reservoir model with extremely fine grids. It is assumed that wormhole's properties are a function of its radius and can be controlled along its length and pattern, which facilitates the history matching process. After validation of the model using data obtained from a field in Alberta, several post-CHOPS scenarios including thermal, solvent and thermal/solvent hybrid applications were simulated. The new modeling workflow, proposed and validated to model the CHOPS process with realistic wormholes representations along with a simple mathematical wormhole network growth model, are the primary contributions of this paper. Secondarily, hybrid steam/solvent applications were evaluated using this validated static model and compared with the sole application of steam and solvent.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".