Bibliographic record
Abstract
Technology Focus With the recent increase in new-well activity in unconventional reservoirs and the well-factory approach, a natural limitation exists in the capacity for implementing hydraulic-fracturing optimization. An even greater limitation exists with the consideration of stimulating production from existing wells in decline. Great strides have been made in drilling and completion efficiencies and well-cost reduction during the past several years. That focus has been most important in the lower-for-longer oil-price environment we have fought through. Naturally, that focus has, to some extent, limited alteration of initial-stimulation design—for example, with respect to fracture-stage sizes, fracture-spacing optimization, and proppant types and volumes. Furthermore, restimulation of existing wells is not an area that has received as much attention as other areas, and, where it has, the focus has been on simply repeating refracturing with proppant. Remedial chemical-treatment options have not been explored to a significant extent, especially at the field level. Instead, greater attention has been placed on how to make the leap from primary production achieved from initial well completion to field-scale enhanced oil recovery (EOR). The in-between measure of remedial production enhancement in existing wells is largely being skipped. With low primary-recovery rates in unconventional reservoirs and the longer-term development prospects for EOR applications on a fieldwide scale, the potential for accelerated completion optimization in new wells and production-enhancement treatments in existing wells is substantial and perhaps comes with more immediate returns. Along those lines, the first of three papers featured this month addresses the optimization of fracture spacing and penetration ratio in unconventional reservoirs. The other two papers discuss studies related to remedial production and recovery improvement in existing wells—surfactant soak and flowback treatments in oil-bearing formations and solvent treatments for water and condensate blockage in tight formations, respectively. Recommended additional reading at OnePetro: www.onepetro.org. SPE 189805 Dual-Permeability Matrix-Fracture Corefloods for Studying Gasflooding in Tight Oil Reservoirs by Peng Luo, Saskatchewan Research Council, et al. SPE 190214 Underlying Mechanisms of Tight Reservoir Wettability and Its Alteration by Peng Luo, Saskatchewan Research Council, et al. SPE 187542 Limitation of EOR Applications in Tight Oil Formation by Ahmed Mansour, Texas Tech University, 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 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.253 | 0.076 |
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".