Bibliographic record
Abstract
Technology Focus When the October 2014 Tight Reservoirs feature went to press, the WTI crude oil price was at or near USD 100/bbl. When the feature was published, the price, although already declining, was still more than USD 80/bbl. And the October 2014 feature noted the fast-paced growth in exploration and development of unconventional hydrocarbon reservoirs and the associated need to determine how to accelerate and sustain longer-term production. Now, 1 year later and in a very different business climate with much lower hydrocarbon prices and greatly reduced well-drilling activity, there is a shift in focus. The need to understand, develop, and implement the means to increase reserves recovery (or to produce more from what we have while at the same time reducing costs) is now the priority. In order to accomplish these more-prudent, more-sustainable objectives, increased attention is being placed on understanding fluid-flow behavior in tight and unconventional reservoirs, on perforating and stimulation optimization, on enhanced-oil-recovery methods applicable to such formations, and on modeling and forecasting economic production profiles and field economic limits in variable price environments. Estimates of tight-reservoir hydrocarbon reserves continue to vary with uncertainty. What is known with certainty, though, is that current recovery rates are low and the upside is substantial. So, overcoming the challenges to reach more-aggressive, stretch targets in recovery and cost efficiency will be well worth the effort. The present business environment, though painful, presents an opportunity for the future. But, as always, collaboration across and among operators, technology and service providers, and academia will be necessary. The papers featured this month provide a few examples of innovation, technology advancements, and learnings that can be applied to achieve more-sustained and more-economic production and reserve recovery. JPT Recommended additional reading at OnePetro: www.onepetro.org. SPE 171580 A New Methodology To Forecast Solution Gas Production in Tight Oil Reservoirs by Shaoyong Yu, ConocoPhillips Canada SPE 171826 Perforating With Deep- Penetrating Guns Followed by Propellant Treatment Yields Results in Tight Reservoirs—UAE Case Study by M.N. Aftab, ADCO, et al. SPE 172663 Impact of Perforation- Tunnel Orientation and Length in Horizontal Wellbores on Fracture- Initiation Pressure in Maximum-Tensile- Stress-Criterion Model for Tight Gas Fields in the Sultanate of Oman by Andreas Briner, PDO, et al.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.150 | 0.047 |
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".