State-of-the-Art of Heavy-Oil Development in China and Its Technology Challenges
Bibliographic record
Abstract
Abstract The commercial heavy oil development in China was initial in 1982 when the first cyclic steam stimulation (also known as steam huff and puff) pilot well test was successful in Liaohe Oil Field, northeast of China. In 1993, the annual heavy oil production had reached 70 million barrels and kept the level for more than 10 years. The major development manner of heavy oil reservoir is steam injection, including cyclic steam (CSS) and steam flooding. CSS annual production is beyond 5.5 million barrels, more than 80% of heavy oil production. Steam flooding, successful in developing shallow heavy oil reservoir such as Kalamy oil reservoir, northwest of China, accounts for 8% heavy oil production with the highest annual production nearly 7 million barrels. For more than 20 years development, great progress has been made in several technologies as followed. (1) Integrated steam huff and puff technology with recovery factor higher than 20% of OOIP (2) Steam flooding technology, including high-temperature profile conformance technology, survey technology and steam measurement technology. The recovery factor of shallow heavy oil reservoir is beyond 40% of OOIP. (3) Super-heavy oil development technology, including integrated heat technology, high-efficiency steam injection technology, playing an important role in maintaining heavy oil production level with the highest annual oil production beyond 16 million barrels. Although lots of progresses have been made, several problems as followed exist in heavy oil reservoir development. (1) CSS enters into later stage, with low pressure, low oil production and so, poor recovery results. (2) No mature development manner following CSS has come into being. (3) Steam flooding in deep heavy oil reservoirs is still in pilot test. It will take a long time to make it commercial application. (4) Steam Assisted Gravity Drainage (SAGD), is also in pilot test being carried out in Liaohe oil field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".