Leakoff and Flowback Experiments on Tight Carbonate Core Plugs
Bibliographic record
Abstract
Summary In this paper, we investigate the change in oil effective permeability (koeff) caused by fracturing-fluid (FF) leakoff after hydraulic fracturing (HF) of tight carbonate reservoirs. We perform a series of flooding tests on core plugs with a range of porosity and permeability collected from the Midale tight carbonate formation onshore Canada to simulate FF-leakoff/flowback processes. First, we clean and saturate the plugs with reservoir brine and oil, and age the plugs in the oil for 14 days under reservoir conditions (P = 172 bar and T = 60°C). Then, we measure koeff before (baseline) and after the leakoff process to evaluate the effects of FF properties, shut-in duration, and plug properties on regained permeability values. We found that adding appropriate surfactants in FF not only significantly reduces koeff impairment caused by leakoff, but also improves koeff compared with the original baseline for a low-permeability carbonate plug. For a plug with relatively high permeability (kair > 0.13 md), freshwater leakoff reduced koeff by 55% (from 1.57 to 0.7 md) while FF (with surfactants) reduced koeff by only 10%. The observed improvement in regained koeff is primarily because of the reduction of interfacial tension (IFT) by the surfactants (from 26.07 to 5.79 mN/m). The contact-angle (CA) measurements before and after the flowback process do not show any significant wettability alteration. The results show that for plugs with kair > 0.13 md, FF leakoff reduces koeff by 5 to 10%, and this range only increases slightly by increasing the shut-in time from 3 to 14 days. However, for the plug with kair < 0.09 md, the regained permeability is even higher than the original koeff before the leakoff process. We observed 28.52 and 64.61% increase in koeff after 3- and 14-day shut-in periods, respectively. This observation is explained by an effective reduction of IFT between the oil and brine in the pore network of the tight plug, which significantly reduces irreducible water saturation (Swirr) and consequently increases koeff. Under such conditions, extending the shut-in time enhances the mixing between invaded FF and oil/brine initially in the plug, leading to more effective reductions in IFT and consequently Swirr. Finally, the results show that the regained permeability strongly depends on the permeability, pore structure, and Swirr of the plugs.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".