Bibliographic record
Abstract
Guest editorial Deepwater E&P is a growing part of the world's energy supply. Estimates are that deepwater production will grow 78% by 2011, making it one of the leading growth sectors in our industry. The explanation is simple: many of the world's largest untapped reservoirs are in deep water. The "golden triangle" of the Gulf of Mexico, offshore Brazil, and west Africa are joined by newer areas of opportunity in India, Malaysia, Australia, the eastern Mediterranean, offshore Norway, and eastern Canada. There are even more promising possibilities in the salt and subsalt reservoirs located in the basins of the golden triangle. The industry's definition of deepwater exploration and its technical challenges are expanding along with knowledge of the reserves. Ten years ago, deep water was anything more than 1,500 ft water depth. Today, the deepwater frontier is more than 5,000 ft. The frontier of a decade ago is now practically routine. And along with these greater water depths, operators are facing increasing total well depths and higher temperatures and pressures. The deepwater opportunity comes at a price—the high rig rates and capital intensity make it a high-risk and high-reward proposition. And the enormous technical challenges make deepwater wells a focal point for developing and deploying advanced technology in every aspect of well construction and production. Completions technology brings operators more production, lower costs and lower risks, and holds the promise of enabling the future production the world demands. What follows is a snapshot of the deepwater completions picture, with emphasis on those areas that will contribute most to operators’ success. All these elements are interrelated and complementary. Developments in one area contribute to the effectiveness of the others. Ultimately, it is the integrated development of all aspects of deepwater completions that promises to make possible the production the world is counting on over the next several years. High-Rate Fracturing Systems Stimulating production through hydraulic fracturing is a proven way of making deepwater wells economical. Frac packs of long, thick unconsolidated producing intervals in turn depend on the ability to pump frac fluid at a high rate and place proppant in large quantities. Tools and techniques that make access to these zones profitable include using hydrostatic properties of frac fluids to increase bottomhole fracture pressure without unsafe surface treating pressures. This helps achieve the high pressure needed for the fracture without exceeding the pressure rating of surface equipment. Also, tool systems using carbide-protected crossover tool designs are now able to withstand the large volumes of proppant at high rates needed to capitalize on the high-rate fluid pumping. These technologies are valuable in their own right, and they are crucial to the development of single-trip multizone completions.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.055 | 0.017 |
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 source (direct Gemma or distilled Codex), 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".