Evaluation of Recovery Performance of Miscible Displacement and WAG Process in Tight Oil Formations
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Bibliographic record
Abstract
Abstract Recent advances in well design and production techniques have brought considerable attention to exploitation of tight (low permeability, absolute permeability <1 mD) oil resources. Drilling of long horizontal wells and deployment of hydraulic fractures along these wells (multi-fractured horizontal wells) can substantially improve the primary production rates from such reservoirs. Nevertheless, the low effective permeability of these reservoirs to oil hinders the sustainability of favorable oil rates and at some point applying some EOR technique becomes inevitable. In the current study, CO2 miscible flooding and WAG process in a tight oil reservoir are investigated. Although several studies have investigated different aspects of the process in conventional oil plays, the design of an effective scheme in tight oil formations is more complex. These complexities are related to the proper design of the fractures (half-length, conductivity, orientation (transverse vs. longitudinal), etc.) and their relative placement along producers and injectors and the operational constraints on each well or segment of the well. In this work, we utilize an EOR scheme design where multi-fractured horizontal wells are used for both injection and production, and the hydraulic fracturing stages are staggered to delay breakthrough and improve sweep efficiency. For a set of defined parameters, compositional simulations are conducted to investigate the effect of the CO2 slug size, WAG ratio and cycle length on the recovery efficiency of the model. The recovery from the aforementioned EOR process is then compared with its corresponding base case in which the reservoir has gone through periods of primary and water-flooding stages. The results of this study show that the incremental oil recovery from WAG process in tight formation can reach as high as 20%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it