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
Facing crippling crude prices and a historic supply overhang, the once-booming US shale sector is for the first time being forced to shut in thousands of wells across its most prolific tight-oil basins. Accurate production data lag by months in the US, but analysts are reporting onshore shut-in for early May to be somewhere between 100,000 to 400,000 B/D. The largest cuts announced so far come from ConocoPhillips which said in addition to its Canadian oil sands projects that it is shutting in nearly the all of its US onshore position - some 2,400 wells, representing about 165,000 B/D. A projection from commodity researchers at JP Morgan Chase suggests as others follow suit these curtailments may reach 1.5 million B/D by June. The business driver behind the so-far uncoordinated effort is crystal clear. Much less so is how the development will play out when prices bounce back up and the wells are turned back on. That part is a subsurface mystery. A new report by Wood Mackenzie published in April summarizes several factors shale producers are dealing with as they undertake painful but necessary shut-in campaigns. The chief risk listed for subsurface considerations was reservoir damage caused by a loss of relative permeability. “Routine short-term shut ins - days to weeks - for maintenance or ‘frac hit’ avoidance seem to cause few reservoir problems,” the report reads. “But wide-spread shut in of tight-oil horizontal wells is rare, so the long-term reservoir response is uncertain.” As the situation unfolds, many in the petroleum engineering community have taken to social media and online SPE forums to ask practical questions about how best to shut in wells, which ones to shut in, and how to restart them again. Some of the answers hinge on how long the shut-ins are meant to last; 2 months or 6 months could make a big difference. “I don’t think anyone really knows for sure what will happen,” said Eric Gagen, who has spent more than a decade restoring shut-in wells offshore and in shale plays. The petroleum engineer served as a technical manager at a coiled-tubing company until industrywide staff reductions began this month. He said long-term shut-ins on the order of several months could introduce a range of issues that span surface equipment operations to “unexpected” downhole chemical reactions. At a minimum, Gagen said operators shutting in for months should expect to see significantly higher water cuts upon restart. In most tight-rock reservoirs, especially those that are oil-wet, water becomes more mobilized than oil over time “and shut-in wells have a tendency to produce even more water as they are put back on production.” Undulating wellbores - a common feature of horizontal wells - may exacerbate this issue. In the worst of outcomes, a water-loaded well produces such an excess of water that remediation efforts stop making economic sense. At that point, the well is a candidate for a plug-and-abandonment operation.
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 | 0.000 | 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 | 0.000 |
| 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