Numerical Simulation of Black Oil-three Compound Combination Flooding
Bibliographic record
Abstract
Numerical methods of permeation fluid mechanics for black oil (water, oil and gas)--three compound combination flooding (polymer, surface active agent and alkali) in porous media is discussed in this paper. In view of petroleum geology, geochemistry, computational mechanics of flow and computer technology, a mechanics model of three-phase flow (water, oil and gas)--three compound combination flooding (the polymer, surface active agent and alkali) is presented firstly, then the characters and the application are stated in this paper. A numerical algorithm consisting of a full implicit program, an implicit computation for the pressure and an implicit/explicit program respective for the pressure and the concentration is given by structuring an upstream sequence and an iterative algorithm of implicit fined upwind fractional step finite difference to solve the pressure equation, the saturation equation and the concentration of chemical substance components and the petroleum acid concentration equation. This program runs quickly and is of high accuracy. The design of this software is given and can be applied in major industries, which is made up on ten-meters steps, hundreds of thousands nodes and tens of years and has been carried out successfully in analysis and simulation of national major oil-fields extraction such as Daqing Oilfield, Shengli Oilfield and Dagang Oilfield and others, which gives rise to outstanding economic and social benefits. A precise analysis is given for a simplified model and the numerical simulation system depends on mathematics and mechanics. An idea is presented to solve this international famous problem.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".