Study on the Depositional Microfacies and Internal Architecture of Sandy Debris Flows in Low-Permeability Oilfields: Implications for Remaining Oil Recovery in the HeShui Oilfield
Bibliographic record
Abstract
As oil resources continue to be depleted, traditional extraction technologies face significant challenges, and improving remaining oil recovery has become a critical issue in the development of low-permeability oil fields. The study first establishes a stratigraphic framework through a fine stratigraphic correlation of key wells, followed by a comprehensive characterization of the internal arrangement of sand bodies, with a detailed analysis of the distribution of interlayers and the complexity of sand body stacking patterns. Based on field data, including tracer monitoring and water absorption profiles, the distribution of remaining oil is predicted. The results reveal that sandy debris flow deposition plays a key role in the enrichment of remaining oil, particularly considering how its internal structure impacts reservoir connectivity and waterflood efficiency. The sedimentary pattern in the study area is dominated by debris flow deposition, with poor continuity of sand bodies; over 90% of individual sand bodies encountered during horizontal well drilling have a width of less than 60 m. Sand body stacking types are classified into overlapping, splicing, and isolated types, and different stacking types significantly influence reservoir waterflood efficiency and the distribution of remaining oil. The innovation of this study lies not only in the microstructural investigation of sandy debris flow but also in the comprehensive characterization of its strong heterogeneity. By analyzing the internal configuration of sand bodies, sedimentary microfacies, and physical property distributions, this study uncovers how these factors influence the distribution of remaining oil. This approach provides valuable insights for accurately predicting and enhancing remaining oil potential.
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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) | 0.000 | 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".