A Nondamaging Friction Reducer for Slickwater Frac Applications
Bibliographic record
Abstract
Abstract Friction reducers used in slickwater fracturing can cause damage to the formation and, especially, to natural fractures because of their chemical nature as high molecular weight polyacrylamides and because of the large volumes injected during a typical treatment. Such concerns can be addressed with two approaches: 1. developing more effective friction reducers with a) more efficient polymers and/or b) faster hydration to shorten the dormant period before friction reducers are fully hydrated, considering the fact that fluids typically travel from surface to perforation within only 3 minutes; 2. developing breakable friction reducers, which are effective during pumping but degrade under downhole conditions, leaving little residue. A new friction reducer was developed, encompassing all of these desired features. Improved hydration and more effective chemistry make it possible to achieve significant reduction of polymer loading in the field, and effective breaking downhole minimizes residue. The new friction reducer is delivered in liquid form to simplify logistics and field operations. It is very effective as a friction reducer, compatible with common chemical additives (scale inhibitors, biocides, clay stabilizers, surfactants, brines, etc) and stable under mechanical shearing. More than 30 multi-stage slickwater frac completions have been performed using this new friction reducer in tight sandstone and shale formations. The effectiveness of the friction reducer was compared with conventional ones during the field trials and will be described in the paper. The field results were corroborated by laboratory tests of the new friction reducer in water and various brines. This paper will also present chemical compatibility, breaking profiles and formation damage studies on tight sandstone and shale formation core in comparison with conventional products. Production history of field-trial wells for 30, 60, 90 days will be presented and compared to those of the offsets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".