Bibliographic record
Abstract
Technology Focus Last year’s Offshore Facilities Technology Focus (February 2014) highlighted the slowdown of new-project approvals that the inflated cost of doing business in the oil and gas sector had already brought about. That slowdown has continued throughout the past year, although the high cost of goods and services has been replaced as the driver by the much lower revenues now attainable from the oil and gas produced. In many cases, the currently required capital investment cannot be justified. Of course, the cost of goods and services will gradually moderate as the demand from operators temporarily wanes, but the project activity will really pick up again only when the value of the hydrocarbons recovers to a point where confidence in longer-term economic viability is restored. Meanwhile, we risk witnessing yet another cycle of layoffs and redundancies, even while the wailing over resource shortages for the tasks ahead still echoes around the upstream corridors of power. One of the phenomena examined in this year’s feature is the destabilizing escalation in weight, and hence cost, of offshore facilities that has been an increasingly common feature of our industry after project sanction at a given commitment level. This is clearly something the industry has to get a proper grip on before confidence can be restored fully. We also continue to highlight a theme that has appeared in each of the last four editions of the Offshore Facilities feature, namely the critical importance and benefits of effective collaboration at all levels and between sectors of our industry in honing the efficiency with which development objectives are achieved. Availability and application of new ways of tackling tough development challenges remain key components of this collaborative quest for ever-better operational efficiency. We delve into several recent examples of how this has been achieved, using new technologies, methods, and materials. It is hoped that these might serve as a timely reminder to avoid temporary layoffs by encouraging instead a redeployment of resources temporarily liberated by the current lull in field-development activity. Many of these could, and perhaps should, be tasked with qualifying the next tranche of new approaches that will benefit the eventual resumption of unfettered field- development activity. Innovation is the life-blood of any high-tech industry, and the operators are the primary beneficiaries of its application. If we do not take advantage of opportunities such as those currently presented, to focus liberated resources onto developing and qualifying the innovations needed for enabling the next set of challenges to be overcome, then we will have only our collective selves to blame. JPT Recommended additional reading at OnePetro: www.onepetro.org. OTC 25354 Espirito Santo: Operational Feedback on the Use of Steel Risers on a Turret-Moored FPSO by Andrew Newport, SBM Offshore, et al. OTC 24834 Concept Evaluation of Concrete Floating Liquefied Natural Gas by A. Nezamian, WorleyParsons, et al. SPE 170696 Upstream-Offshore- Facility Weight-Growth Study by Ray Rui, Independent Project Analysis, et al.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".