An Experimental Study of Spontaneous Imbibition in Horn River Shales
Bibliographic record
Abstract
Abstract Fracture fluid flow back has been identified as one of the major challenges of hydraulic fracturing operations conducted in shale reservoirs. Factors causing the very low fracture fluid recovery need to be well understood and properly addressed, in order to get full benefits from costly hydraulic fracture jobs conducted in unconventional reservoirs. Despite the recent surge of investigations of the problem, one major question still remains: what happens to the fracture fluid that is not recovered? Does it stay in the fracture or does it go into the matrix? In case of both mechanisms are responsible for fracture fluid retainment, what fraction of fracture fluid stays in the propped fracture and what fraction is transferred from fracture to matrix. The focus of the current study is to understand if the transfer of fracture fluid from fracture to matrix through imbibition is of significant importance. We systematically measure the imbibition rate of water, brine, and oil into the actual core samples from the three shale sections of Horn River basin (i.e., Fort Simpson, Muskwa and Otter Park). We characterize the shale samples by measuring, porosity, wettability, mineral composition through XRD analysis, and interpreting the well log data. The results show that imbibition could be a viable mechanism for fluid transfer from fracture to matrix in Horn River shales. The comparative study shows the imbibition rate in the direction parallel to the bedding plane is higher than that in the direction perpendicular to the bedding. The study also suggests that the imbibition rate of the aqueous phases is significantly higher than that of the oleic phases.
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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) | 0.001 | 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".