Resilient Field Developments That Can Accommodate Uncertainty Are the Best Solution for a Sustained Low Oil Price Environment
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
Abstract The upstream industry has been unable to deliver projects successfully over the last ten years, with up to 70% of projects failing to meet schedule or cost targets. This failure rate did not matter when the oil price was high as the projects remained profitable. However, after the oil price dropped in 2015, this level of project failure has become untenable. The linear gated project management systems adopted by the industry over the last fifteen years are suitable for straightforward projects that can be well defined. However, they are not suitable for many of today's projects that are more complex and have significant uncertainty, which require a different approach. This paper describes a project management process developed in the UKCS in the 1990's that was used to bring three projects stuck for 15 years to project sanction. In addition, a recent project is described where the development was designed to accommodate a range of outcomes and by doing so allowed the project to be sanctioned with significant uncertainty still remaining. In the current environment of a sustained low oil price, across the board cuts are often implemented in an attempt to make projects economic. Arbitrary cuts on their own are unlikely to make projects viable and instead the industry needs to take a step back and question the processes that have been used and why they have failed. A different approach is suggested; one that embraces uncertainty to produce resilient projects that can accommodate change. Implementing this will require a change in mindset as much as a change in process.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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