Physical and Numerical Simulations of Offset Well Pair Combined Steam Drive and Gravity Drainage Process to Develop Super-Heavy Oil or Oil Sands Project
Bibliographic record
Abstract
Abstract Steam assisted gravity drainage (SAGD) using parallel dual-horizontal wells made great success in developing heavy oil or oil sands projects. However, the performance may be greatly impaired when shale laminae with high frequency exist. In order to enhance oil production and decrease steam to oil ratio (SOR), this paper conducts feasibility study of offset well pair using steam drive and gravity drainage to develop oil sands project by overcoming shale laminae. Physical simulations of offset well pairs under three horizontal distance were first carried out to analyze the mechanism. On the basis, homogeneous model and heterogeneous model incorporating staggered shale laminae were constructed, respectively. Then numerical simulations of conventional SAGD well pair and offset well pair using steam drive and gravity drainage were conducted to evaluate the influence of pay thickness and possibility of mitigating adverse impact of shale laminae. Moreover, several configurations of offset well pairs and their application results were proposed. The results of physical simulations indicate that there is larger lateral steam chamber development compared with conventional well pair. While for numerical simulations, for homogeneous case, compared with conventional well pair, offset well pair achieves similar performance but delaying oil production for 0.5 year, and the performance cannot be improved significantly even if aggressive pressure difference or subcool control is enforced. But for heterogeneous model with existing inter-well shale laminae, offset well pair can significantly improve early to mid-term performance and accelerate early steam chamber growth by enforcing pressure difference. But once steam chamber has grown to a certain height, there is no big difference between offset and conventional well pairs. Furthermore, three configurations of offset well pairs are evaluated including the injector drilled 3 m high and 4 m laterally from the producer, offset horizontal injector and multilateral producer, and multi-stage hydraulic fracturing or dilation assisted enlarge well spacing of 10-30m. Encouragingly, offset horizontal injector and multilateral producer has made great success by a combination of steam drive and gravity drainage in Canadian Surmont oil sands project. The proposed technology was first studied by combined physical and numerical simulations, and it can be effectively applied to relatively low quality oil sands projects such as thin pay and challenging pay with staggered shale laminae. Several configurations of offset well pairs have been listed as pilot suggestions.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".