The Offshore Heavy Oil Development Challenges in Brazil
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 largest accumulations of heavy oil and bitumen under development in the world are located in Venezuela and Canada1. So far, Canada and Venezuela have developed technologies that make it technically and economically feasible to develop these accumulations. The successful thermal methods as steam injection, combustion in-situ and its variations applied in the onshore heavy oil projects have severe limitations to be applied in offshore deep waters. The technological and logistic aspects of the offshore environment make these methods unsuitable if considering the current technologies. Nowadays, cold production is the only method that could be applied for offshore fields located in deep waters. Even if this technology is applied, it should have some limitations. Unlike the cold production in operation today in Venezuela and Canada, where sand is produced with oil, offshore sand production would be prohibitive due to the high costs of processing or transporting the sand to shore. The crude production in Brazil is increasing and more and more heavy oil has been produced. In addition, large resources of heavy oil have been discovered during the last 6 years and are under evaluation. In this scenario, the development of technologies that improve the economics of such discoveries is critical for the country to reach and maintain the so aspired self-sufficiency in petroleum. This paper will summarize the planned path to overcome the challenges related to the exploration, development, production and marketing of the offshore heavy oil in Brazil.
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