Bibliographic record
Abstract
Technology Focus A year ago, this feature noted the continued languishing of crude-oil prices and the low margins in tight and very tight reservoir asset developments and the resulting substantial reduction in new-well drilling and completion. Little has changed since then. In the meantime, technology advancements have enabled a greater number of hydraulic fractures in long horizontal completions in such reservoirs, for example, resulting in more-cost-effective completions and greater initial oil-production rates. But low primary oil recovery and steep initial-production-rate declines still present overriding limitations. These tight and very tight oil-bearing reservoirs are typically characterized by oil-recovery factors of approximately 10%. However, on a positive note, in addition to improvements in completion efficiencies, recent advancements also have been made in the understanding and application of enhanced-oil-recovery (EOR) methods in such reservoirs. While enhancing oil production from multizone, hydraulically fractured completions in tight reservoirs is not straight forward, recent studies, including field trial programs, have shown that applications such as gas injection and waterflooding, including smart water injection, have the potential to create significant improvement in oil recovery. The three papers featured this month are from Canada. All address the importance of wettability and wettability alteration in improving sweep efficiency and oil extraction by use of gas injection or water injection. Both laboratory studies and field application, in the case of waterflooding, are discussed. Each, with their unique perspectives and approaches, provides understanding of EOR fluids; formation interactions; and the benefits and present limitations of gas injection, conventional waterflooding, and smart water injection. Recommended additional reading at OnePetro: www.onepetro.org. SPE 185037 EOR in Tight Reservoirs—Technical and Economic Feasibility by K. Joslin, Computer Modelling Group, et al. SPE 185680 Compositional-Simulation Evaluation of Miscible-Gas-Injection Performance in Tight Oil Formation by Ahmed Mansour, Texas Tech University, et al. SPE 180284 The Use of Propellants To Stimulate and Enhance Productivity From Tight, Damaged, and Low-Quality Reservoirs by J. Gilliat, Baker Hughes, et al.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.171 | 0.060 |
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".