Displacement Experiment Characterization and Microscale Analysis of Anisotropic Relative Permeability Curves in Sandstone Reservoirs
Bibliographic record
Abstract
As a critical parameter for describing oil–water two-phase flow behavior, relative permeability curves are widely applied in field development, dynamic forecasting, and reservoir numerical simulation. This study addresses the issue of relative permeability anisotropy, focusing on the seepage characteristics of two typical bedding structures in sandstone reservoirs—tabular cross-bedding and parallel bedding—through multi-directional displacement experiments. A novel anisotropic relative permeability testing apparatus was employed to conduct displacement experiments on cubic core samples, comparing the performance of the explicit Johnson–Bossler–Naumann (JBN) method, based on Buckley–Leverett theory, with the implicit Automatic History Matching (AHM) method, which demonstrated superior accuracy. The results indicate that displacement direction significantly influences seepage efficiency. For cross-bedded cores, displacement perpendicular to bedding (Z-direction) achieved the highest displacement efficiency (75.09%) and the lowest residual oil saturation (22%), primarily due to uniform fluid distribution and efficient pore utilization. In contrast, horizontal displacement exhibited lower efficiency and higher residual oil saturation due to preferential flow path effects. In parallel-bedded cores, vertical displacement improved efficiency by 18.06%, approaching ideal piston-like displacement. Microscale analysis using Nuclear Magnetic Resonance (NMR) and Computed Tomography (CT) scanning further revealed that vertical displacement effectively reduces capillary resistance and promotes uniform fluid distribution, thereby minimizing residual oil formation. This study underscores the strong interplay between displacement direction and bedding structure, validating AHM’s advantages in characterizing anisotropic reservoirs. By integrating experimental innovation with advanced computational techniques, this work provides critical theoretical insights and practical guidance for optimizing reservoir development strategies and enhancing the accuracy of numerical simulations in complex sandstone reservoirs.
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 | 0.000 |
| 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 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".