Experimental Investigation for Microscale Stimulation of Shales By Water Imbibition During the Shut-in Periods
Bibliographic record
Abstract
Abstract Imbibition of water into the shale matrix is known as the primary reason for inefficient water recovery after hydraulic fracturing treatments. The hydration of clay minerals may induce microfractures in clay-rich shale samples. The increased porosity and permeability due to induced microfractures has been considered to be partly responsible for 1) excessive water uptake of gas shales, and 2) increase in hydrocarbon production rate after prolonged shut-in periods. To test this hypothesis, it is necessary to measure imbibition-induced strain and stress under representative laboratory conditions. In this study, we conduct laboratory tests to 1) measure the strain and stress induced by water imbibition in gas shales and 2) investigate the effect of confining load on the rate of water imbibition. We conduct a three-phase study on rock samples from the Horn River Basin (HRB) and the Duvernay (DUV) Formation, located in the Western Canadian Sedimentary Basin. In the first phase, we measure baselines for water and kerosene imbibition into the rock samples by conducting spontaneous imbibition tests. In the second phase, we measure expansion of the rock samples during imbibition of water and kerosene, in separate tests, using a linear variable differential transformer (LVDT). In the third phase, we measure imbibition-induced tensile stress during water imbibition into the samples. The results show that both HRB and DUV shale samples imbibe more water than kerosene, due to water adsorption by clay minerals. Imbibition of water increases the porosity of the HRB and the DUV samples by up to 0.94 and 0.25 percentage points, respectively. Expansion of all samples is anisotropic, with higher expansion perpendicular to the depositional lamination. Water imbibition into the samples induces an expansive stress as high as 17 psi. Moreover, applying confining stress reduces the imbibition of water by up to 18.1% and 33.7% in the HRB and DUV samples, respectively.
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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) | 0.002 | 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".