Bibliographic record
Abstract
Technology Focus Efforts for increasing recovery factors in all reservoir types continued with increasing momentum during the past year. Maturing fields combined with limited exploration forced operators to focus on recovering more from existing fields. Implementing enhanced oil recovery (EOR) in a depressed-oil-price environment is accepted as a challenge by our resilient industry, and, therefore, all aspects of EOR, including EOR agents, EOR physics, and EOR modeling and monitoring, improved further. We saw progress in all EOR schemes in the past year, from expanding-solvent steam-assisted gravity drainage (SAGD) to increasing recovery factors in unconventional fields in the US. While carbon-dioxide EOR continues to be used in conventional reservoirs, it is also becoming a desired EOR agent for unconventionals. EOR implementations in high-viscosity-oil reservoirs continued to see improvements with more chemistry, with heat, with improved reservoir characterization, and with advancements in SAGD implementation. Progress in chemical EOR, from polymer to alkaline/surfactant/polymer, has been significant. Not only are there new chemicals with improved recovery capabilities, but also the cost of the chemicals is being reduced continuously. All those factors led to more operators using chemical EOR. It is worth reiterating that increasing recovery factors in unconventionals will remain the top priority for many years to come. The next chapter of the exciting unconventionals journey will be more about EOR. EOR momentum on all fronts is reflected in the technical papers reviewed this year. This is the first time I have seen that all EOR schemes were covered. Half the technical papers were about fundamentals, and the other half were about field implementation. I found that to be the best indicator that EOR is becoming an integral part of managing oil fields. The selected papers provide a summary of some of the noteworthy advancements in EOR performance and modeling. Recommended additional reading at OnePetro: www.onepetro.org. SPE 187032 Nanoscale-Flow-Chip Platform for Laboratory Evaluation of Enhanced-Oil-Recovery Materials by Michael Engel, IBM Research, et al. SPE 185526 Surveillance and Initial Results of an Existing Polymer Flood: A Case History From the Rayoso Formation by L.A. Martino, YPF, et al. SPE 183165 Borehole Controlled-Source Electromagnetics for Hydrocarbon-Saturation Monitoring in the Bockstedt Oil Field, Onshore Northwest Germany by K. Tietze, GFZ Potsdam, et al. SPE 182669 Uncertainty Quantification for Foam Flooding in Fractured Carbonate Reservoirs by A. Almaqbali, Heriot-Watt University, et al. SPE 185002 ES-SAGD Relative Permeability as a Function of Temperature and Solvent Concentrations by M. Zeidani, University of Calgary, et al.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".