Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Refracturing opportunities In what may become Act Two for the North American “shale revolution,” some operators are returning to their mature shale wells to refracture, or restimulate, the rock to accelerate the rate of production and enhance the ultimate recovery of trapped hydrocarbons. Refracturing is not a new technique and has been applied for many years in tight rock and vertical wells. But now producers want to apply refracturing to a large inventory of unconventional wells suffering from low production because of ineffective initial completions. Refracturing could also serve as a countermeasure against the characteristically steep decline rates of shale wells. A few years after coming on-stream, most horizontal shale wells produce at a fraction of their initial rate, yet large volumes of oil and gas remain in the rock that could be produced through refracturing. Those involved expect shale well refracturing activity in the United States and Canada to increase steadily as companies figure out how to optimize the mechanics of the operation. Their optimism is based on some early success stories, and the sheer number of possible refracturing opportunities that exist. “Over these next 2 years, the industry will be sharpening their pencils on how and where they are going to (refracture), and then they are going to do it because the potential is tremendous,” said Ibrahim Abou- Sayed, founder of a Houston-based company called i-Stimulation Solutions that offers upstream engineering and consulting services. However, some companies are sitting it out until newer technology overcomes some of the challenges involved with refracturing to make it an easier operation to carry out. Tim Leshchyshyn, founder of a Calgary-based company called FracKnowledge that maintains a database of fracturing information, characterizes refracturing as a “large, complicated topic” that needs more research and development to become a reliable technique. “For many of the candidates that need to be refractured, the industry is short on technology to do so,” he said. “I think there are some tools out there that help, but there is still a lot of room for technology development to make it easy and highly successful.”
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.
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 | 0.000 | 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 it