Coming to Americas
Bibliographic record
Abstract
Abstract The deepwater basins of the Americas have been among the most active and successful with discovered resources to date of over 100 billion boe. Some of the world’s most prolific hydrocarbon basins are located along the Americas margins. Considerable undiscovered potential remains, and prospects can be multi-billion barrels of oil in size. This paper will focus on deepwater hot spots in East Coast Canada, Gulf of Mexico, the Equatorial and Atlantic Margins, and Colombia. This paper will explore the factors that have contributed to building a successful deepwater sector – from access to exploration, from development to production. It highlights some of the common challenges operators face across the region, and best practice by governments and industry in handling these issues for sustainability in a highly cyclical oil and gas business. And, finally, this paper will set the stage for a panel discussion scheduled for 9.30am to 12.00pm, Wednesday, May 8, 2019 at the Offshore Technology Conference (OTC). The panelists are oil company executives representing independents, integrated oil companies and national oil companies along with service providers as follows: Erik Oswald, VP Americas, ExxonMobil ExplorationCindy Yeilding, Senior VP, BP AmericasCarlos Portela, President, Ecopetrol AmericaTim Duncan, CEO, Talos EnergyLiz Schwarze, VP Global Exploration, ChevronChris Golden, Senior VP, EquinorJulie Wilson, Director, Wood MackenzieSandeep Khurana, Senior Manager, Granherne
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) | 0.000 | 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 | 0.001 |
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".