Interlayer Interference Analysis and Layered Development Strategy in CO <sub>2</sub> Miscible Flooding of Reverse-Rhythm Reservoirs
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide To address the severe interlayer interference and insufficient sweep efficiency during CO 2 flooding in reverse-rhythm reservoirs, this study conducted miscible CO 2 flooding experiments using a self-designed three-layer heterogeneous two-dimensional (2D) visual physical model under two production schemes: sequential layered production and simultaneous layered production. Through image monitoring and a gas/oil ratio control system, the evolution characteristics of displacement front advancement, miscible layer expansion, and interlayer interference under different schemes were revealed. The results indicate that high-permeability layers tend to form gas channeling paths and exhibit a gravity override, which significantly suppresses oil recovery from medium- and low-permeability layers. In contrast, the simultaneous layered production scheme enables collaborative exploitation of multiple layers, significantly improving sweep efficiency and miscible layer continuity in lower-permeability layers and effectively mitigating interlayer interference. The overall oil recovery factor increased from 68.63 to 79.24%. Further analysis shows that shutting the production end of the high-permeability layer enhances vertical mass transfer of CO 2 and delays gas breakthrough, making the medium-permeability layer the dominant contributor to recovery. This study clarifies the controlling mechanisms of permeability contrast and gravitational differentiation on interlayer interference, confirms the crucial role of layered production in controlling displacement paths and enhancing oil recovery, and provides theoretical insights and engineering guidance for the development of CO 2 -EOR in reverse-rhythm reservoirs.
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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) | 0.000 | 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 | 0.001 |
| 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".