Bibliographic record
Abstract
The next year could spell trouble for operators producing oil in west Texas and southeastern New Mexico. The Permian Basin currently has more crude than it can handle, and production there continues to grow at a steady rate month-over-month after surpassing 3 million B/D earlier this year, according to data from the US Energy Information Administration. Pipeline takeaway capacity isn’t sufficient and won’t be until the second half of 2019. There aren’t nearly enough trucks or truck drivers to make up the difference, and any meaningful expansion of crude-by-rail transport is restricted by infrastructure and business-related constraints. Both options are already competing with movement of equipment and supplies such as sand and water, demand of which has also grown—along with their costs—to support the continued production growth. Many operators in the basin struggled to generate positive cash flow even before the bottlenecks became an issue. Now, the price of the crude they’re producing is trading at a big discount vs. spot prices in Houston, near the Gulf Coast refining and export center; and Cushing, Oklahoma, the crude trading hub from which the West Texas Intermediate (WTI) price is derived. The spread between Midland crude and WTI grew to double digits in May, spiking from roughly $1 a couple months earlier. If WTI prices were closer to where they were a year ago, the impact of the spread immediately “would have been significant for almost every operator,” noted R.T. Dukes, Wood Mackenzie US Lower 48 upstream research director. Fortunately for Permian operators, WTI prices have been much higher than the range of prices for which they budgeted coming into the year, minimizing the impact of the spread thus far. But WTI prices aren’t guaranteed to remain that high, and differentials could grow—just look at the Western Canada Select heavy crude price, which has traded at up to a $30/bbl discount to WTI this year due in large part to transportation constraints. The spread forced operators such as Cenovus, Husky Energy, and Canadian Natural Resources to slow their oil sands production during the first quarter. Permian operators are similarly being forced to examine whether continued growth over the next year is sustainable or even worthwhile. Their exposure to Midland spot prices varies, ranging anywhere from less than 5% to 50–60% of Permian production, said John Coleman, Wood Mackenzie senior analyst, North American crude oil markets. Most operators are in the 20–30% range, meaning there already has been a modest hit to cash flow, he said. Consultancy Rystad Energy believes the Midland vs. Cushing spread will “stay very much depressed” into mid-2019 and “won’t be surprised” if it moves into the low $20s/bbl, said Artem Abramov, Rystad vice president, shale analysis. “Everything points to the situation getting worse and worse going forward.”
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".