Water-Induced Damage to Propped-Fracture Conductivity in Shale Formations
Bibliographic record
Abstract
Summary Shale fracture conductivity can be reduced significantly by shale/water interactions. Factors that may influence shale fracture conductivity include shale mineralogy, proppant embedment, shale-fines migration, proppant-fines migration, brine concentration, longer-term stress application, and residual water in the fracture. The study of excessive proppant embedment has been reported in our previous work (Zhang et al. 2014a). This paper presents the studies of the remainder of these factors. Laboratory experiments were run to understand each of these factors. To study the effect of rock mineralogy, recovered fracture conductivities after water damage were measured for Barnett shale, Eagle Ford shale, and Berea sandstone. During conductivity measurements, water-flow directions were switched to study the effect of shale-fines migration. The size of shale fines was measured by microscopic imaging techniques, and scanning-electron-microscope observations were also presented. Proppant-fines migration was examined by placing two colors of sand on each half of the fracture surface, and then a microscope was used to identify the migrated crushed sands of one sand color mixed in with the other sand color. Fresh water and 2% KCl were injected to study the effect of brine concentration. After water injection, the proppant pack was either fully dried or kept wet to investigate the damage caused by residual water. Results showed that clay content determines the fracture-conductivity damage caused by water. Fines generated from the shale fracture because of fracture-face spalling, slope instability, and clay dispersion can migrate inside the fracture and are responsible for 12 to 20% of the conductivity reduction. There is no evidence of crushed-proppant-particle migration in this study. Longer-term stress application accounts for a 20% reduction of the fracture conductivity. In the Barnett shale tests, further conductivity damage caused by fresh water after brine injection is not significant when initial conductivities are greater than 65 md-ft. Removal of the residual water from the fracture by evaporation helps to recover the fracture conductivity to a small extent. A theoretical model of propped-fracture conductivity was extended to include the effects of water damage on fracture conductivity. An empirical correlation for the damage effects in the Barnett shale was implemented in this model.
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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".