Applications of Weak Gel for In-Depth Profile Modification and Oil Displacement
Bibliographic record
Abstract
ABSTRACT With the development of waterflooding in an oil field, water breakthroughsare a common problem. Polymer solutions are widely applied to resolve thewater-channeling problem in a deep formation. In practice, polymers are used asagents in deep formation treatment either to block in-depth high permeabilityzones or to lower water mobility. However, for in-depth profile modification, apolymer solution has to be injected at a relatively high concentration so thatsuch treatment sometimes becomes uneconomical. On the other hand, polymerflooding is ineffective primarily due to the viscosity loss caused bymechanical and chemical degradations. This paper presents a weak gel system, which can be used as an in-depth profile modification agent and as an oildisplacement agent in a heterogeneous reservoir. This gel has relatively lowstrength but can still be cross-linked in the reservoir formation. Themechanisms of weak gel system are described in detail. In addition to studyingthe effects of polymer concentration, cross-linker concentration, temperatureand pH value on gelation time, rheological behavior, gelation ranges and gelstrength are examined. The coreflood results not only provide evidence that theweak gel acts both as an in-depth profile modification agent and as an oildisplacement agent but show an enhanced oil recovery as well. Furthermore, thepilot tests have been performed in four areas of Gudong oil field and Gudao oilfield in China since 1992. As a result, the injection pressure has beenincreased for all testing wells and the field water-cut has been reduced. Bythe end of 2001, the accumulative incremental oil production has been over58,000 tons.
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) | 0.001 | 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 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".