The Application of Hydrocarbon-Degrading Bacteria in Daqing's Low Permeability, High Paraffin Content Oilfields
Bibliographic record
Abstract
Abstract To seek an effective oil recovery approach, Brevibacillus brevis and Bacillus cereus were screened and applied in a Microbial Enhanced Oil Recovery (MEOR) process to recover oil from Daqing low permeability areas. The selected bacteria were found to be highly compatible with indigenous microbes; the laboratory data shows: (1) The oil-water interfacial tensions (IFT) after microbial treatment decreased by 50%; (2) The alkanes with middle and high carbon numbers could be degraded; (3) The viscosity of treated crude oil decreased by about 40%; (4) The content of paraffin and resin decreased from 1.3% to 4.9%, and from 0.7% to 2.6%, respectively, thus improving significantly the rheology of the crude oil; and (5) The oil recovery from laboratory coreflooding achieved about 6.5% original oil in place (OOIP) over that achieved by waterflooding. From 2002 to 2005, microbial huff ‘n’ puff trials have been conducted in 70 wells altogether in the Daqing Chaoyanggou (0.5×10−3μm2−25×10−3μm2) and Pubei areas (103×10−3μm2). Effectiveness was observed in 43 out of 60 Chaoyanggou wells, with accumulative incremental oil amounting to 9175.7 tons. Eight out of 10 Pubei wells showed effective results as well, with 1873 tons of accumulative incremental oil. The total incremental oil from the two areas amounted to 11,000 tons, with an average of about 158 tons for one individual well. Based on the success of microbial huff ‘n’ puff trials, a microbial flooding pilot test with two injectors and 10 producers was carried out in the Chaoyanggou low permeability area (25×10−3μm2) in June 2004. The bacteria injection was followed by a pressure decrease in two injectors and an increase in the fluid injection. The daily produced fluid and oil increased from 43.6 tons to a high of 79.6 tons and from 24.7 to 40.8 tons, respectively. Water cut decreased from 45.2% to 38.6%. By the end of Dec, 2007, 7 out of 10 wells showed significant oil production response. The incremental oil is about 13,000 tons. The analysis made to the effective and non-effective wells demonstrates that MEOR plays an important role in establishing an effective driving system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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 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".