Water Blocking Caused by Fracturing Fluid Leakage in Mixed-Wet Unconventional Tight Reservoirs
Bibliographic record
Abstract
Abstract It has been recognized that, water blocking caused by water-based fracturing fluid leakage is one of the major reasons for well productivity reduction in hydraulic fractured tight formations. Mixed-wettability is broadly existing in tight/shale hydrocarbon reservoirs and it has profound impact on water blocking. In this paper, formation damage caused by water-based fracturing fluid leak-off in mixed-wet tight oil/gas reservoirs is studied. Sensitivity of water blocking on rock wettability, capillarity and permeability is analyzed and early time production is optimized to remediate the damage of formation productivity caused by water blocking. The sensitivity of the water blocking behavior is studied by using a multi-phase dual-wettability model. Results from the reservoir simulations demonstrated that a well-resting period varying from one to twelve months can significantly affect early productivity rate and reduce flow-back of fracturing fluid in mixed-wet reservoirs. The damage to productivity due to water blocking will be reduced along production in a single-wet reservoir, however this damage is irreversible in a mixed-wet formation. The results also indicate that minimizing water leak-off in the formation is crucial in both single wet and mixed wet reservoirs. The mixed wettability of an unconventional tight reservoir is considered in this study, and a multi-phase dual-wettability model is applied to study the water blocking in such formation. The results of this study can provide meaningful guide for hydraulic fracturing and early production in mixed-wet unconventional tight reservoirs.
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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".