The Imbibition Mechanism and the Calculation Method of Maximum Imbibition Length during the Hydraulic Fracturing
Bibliographic record
Abstract
It has been recognized that fluid imbibes into the matrix and floods the oil during hydraulic fracturing; however, the mechanism of fluid imbibing into the matrix and flooding the oil remains unclear. Additionally, there is a scarcity of methods for calculating the maximum imbibition length. In this paper, we first analyzed the imbibition mechanism during hydraulic fracturing and then developed a method for calculating the imbibition length using mercury intrusion experiments, seepage theory, and numerical calculations. By comparing the proposed method calculations with experimental results and published model calculations, we verified our proposed method. Finally, we presented the influences of the maximum imbibition length. From the work, we can know that imbibition during hydraulic fracturing involves counter‐current imbibition under surrounding pressure. The influence of permeability on threshold pressure gradients was found to be greater than that on capillary pressure, resulting in an increase in the maximum imbibition length with increased permeability (ranging from 0.01 to 0.2 × 10 −3 μ m 2 ), while the time taken to achieve the maximum imbibition length decreased exponentially. When the reservoir permeability was 0.1 × 10 −3 μ m 2 , the contact angle was 60°, and the interface tension was 50 mN/m, the maximum imbibition length was 1.8 m, and the time of achieving maximum imbibition length was 70 days. This study provided a method for evaluating the extent of imbibition.
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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 | 0.004 | 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 | 0.001 |
| 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".