Investigation of imbibition and strain behavior of Longmaxi shale using fiber Bragg grating sensing
Bibliographic record
Abstract
The hydration and swelling of clay in shale reservoirs are important factors for the design of drilling and fracturing fluids. Previous studies show that hydration and expansion are among the main reasons for water imbibition. However, few studies have been carried out on imbibition and strain behavior for the shale of the Longmaxi Formation in Changning, China. In this study, a method based on fiber Bragg gratings for evaluating imbibition and strain behavior is presented. Using this method, three imbibition experiments at different solution concentrations were carried out on the shale samples. The main influencing factors include response characteristics during imbibition, strain response during imbibition, ion concentration of imbibed brine, and the relation between saturation and volumetric strain. The results show that water imbibition can be distinctly categorized into two stages: the initial stage of imbibition is characterized by a dependency on the square root of time, and the water imbibition is a linear function of time. The final water saturation after 250 h of imbibition varies from 54.7% (20 wt% NaCl) to 87.8% (deionized water). As the concentration of NaCl increases, the disparity among the horizontal strain, vertical strain, and volumetric strain diminishes. The saturation and volumetric strain have a strong logarithmic relationship. This study provides a quantitative characterization method of imbibition expansion behavior based on optical fiber sensing, which can realize simultaneous monitoring and characterization of imbibition and strain and provide the basis for the shale imbibition mechanism and fracturing fluid flowback optimization.
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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 | 0.000 |
| 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 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".