Bibliographic record
Abstract
Technology Focus In my last two Technology Focus columns, I discussed CO2-enhanced oil recovery (EOR) and the challenges it faces in conventional oil reservoirs. In this entry, my focus is on its applications in unconventional reservoirs. Oil and gas production from unconventional resources has changed the dynamics of the world oil supply, particularly in the US. This has changed the US from a declining oil producer to one of the highest oil producers in the world. Oil production from unconventional reservoirs is still a challenge and depends on a number of factors, including brute force, for drilling and hydraulic fracturing. Production from these reservoirs declines rapidly, and more wells have to be drilled to keep production at reasonable levels. Recovery, by some estimates, can be less (sometimes much less) than 10%. Currently, the number of wells drilled in unconventional reservoirs exceeds 100,000, and many are producing just a trickle of hydrocarbons. In recent years, some effort has been made to use EOR techniques, particularly CO2 injection, to extract additional oil and gas from unconventional resources. This is by no means a trivial feat. It has the potential to change the dynamics (again) of oil production from these tight and difficult reservoirs. Considerable research and laboratory studies have been conducted addressing the use and potential of CO2 in extracting hydrocarbons from unconventional reservoirs. Estimates of oil recovery range from an additional 10% up to more than 50%. Very few field trials have been conducted, but the use of CO2 in these reservoirs is promising. The recommended papers that follow present examples of laboratory studies, taking the results to the field, and mechanistic studies that elucidate some of the factors to consider and the pros and cons of CO2-EOR in unconventionals. They are meant to be a starting point for better understanding and further research. What the industry needs at this stage is more-daring EOR field trials reminiscent of the risks taken by the pioneers of unconventional resources at the beginning of this century. Recommended additional reading at OnePetro: www.onepetro.org. SPE 191780 Enhanced Oil Recovery in Eagle Ford: Opportunities Using Huff ’n’ Puff Technique in Unconventional Reservoirs by Piyush Pankaj, Schlumberger, et al. OTC 28973 Recent Advances in Enhanced-Oil-Recovery Technologies for Unconventional Oil Reservoirs by S. Balasubramanian, University of Houston, et al. SPE 192734 Miscibility Effects on Performance of Cyclic CO2 Injection in Hysteretic Tight Oil Reservoirs by Yasaman Assef, University of Calgary, 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.515 | 0.382 |
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".