Bibliographic record
Abstract
Hydraulic fracturing continues to be one of the popular stimulation techniques employed to enhance production from oil and gas wells worldwide. The application of this technique in both conventional and unconventional reservoirs has resulted in improved hydrocarbon recovery from several oil and gas reserves worldwide. The authors of paper SPE 217813 discuss the use of far-field diverters as a technique to protect parent wells from the detrimental effects of fracture-driven interactions when fracture-stimulating infill wells. Various case histories of the wells drilled and completed in the Bakken and Three Fork formations are presented in the paper. The authors observe that most infill wells under study exhibited superior or comparable year-long production behavior when compared with offset parent wells and also resulted in fewer wellbore cleanouts in some of the parent wells. The authors also note that effectiveness of such treatments depends on formation characteristics and wellbore production history. Paper SPE 213110 presents the observed benefits of fracture-stimulating a high-viscosity oil-bearing formation that was earlier classified as a secondary target in the Apaika-Nenke oilfield in Ecuador. The authors provide a detailed description of reservoir, geology, and pressure/volume/temperature properties, along with modeling workflows adopted to maximize the benefits of stimulating low-API and highly viscous oil-bearing formations that resulted in improved well performance in comparison to unstimulated cases. In paper SPE 215705, the authors present the introduction of hydraulic fracturing on initially unstimulated wells completed in low-permeability oil-bearing formations in North Africa. The authors report a multifold increase in well production after fracture stimulation from the formations that have been producing for a long time after initial well completion that did not include well stimulation. The authors emphasize that the potential to improve well performance with fracture-stimulation treatments must be pursued despite challenges offered by wellbore architecture. Recommended additional reading at OnePetro: www.onepetro.org. SPE 216510 Photonic-Hydraulic Fracturing Hybrid Approach Minimizing Breaking Pressure by Sameeh I. Batarseh, EXPEC, et al. SPE 217764 Statistics and Case Studies of Drainage Frac Height and Zonal Contribution of Stacked Plays in the Midland and Uinta Basin by Shuangyu Ge, RevoChem, et al. SPE 217327 Successful Deployment of New Innovative Polymer Fluid System for Coalbed Methane Hydraulic Fracturing in Hancheng Area, Shaanxi Province, China: A Case History by S.H. Goh, SLB, 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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".