Bibliographic record
Abstract
Abstract Slick water hydraulic fracturing treatments are the preferred method for tight shale plays as they enhance the complexity of fracture networks that are needed to produce economic wells in unconventional formations. At their most basic, these treatments use a polyacrylamide friction reducer to allow for higher pumping rates, but may also include additives such as clay controls, flowback enhancers, scale inhibitors and others. Although traditional slick water treatments are effective, they are limited on several factors that would improve production and - potentially - decrease the cost of a treatment. Such limitations include poor proppant carrying capacity, inconsistent proppant pack distribution, and excessive water volume requirements. Modifying the treatment design of a traditional slick water by adding a novel chemical to the proppant and 5-20% nitrogen, the limitations of this type of stimulation fluid can be reduced. Improving the performance of the slick water treatment is completed by modifying the proppant's surface properties. A novel surfactant preferentially coats the surface of the proppant (including ceramics and resin-coated proppants), hydrophobically modifying the surface of the solids. The enhanced surface properties of the proppant creates an attraction between the proppant surface and nitrogen gas, in effect, surrounding the particle with a thin layer of gas and thus increasing the buoyancy of the proppant in water. These enhanced properties allow for improved proppant distribution, deeper proppant penetration within the complex fracture network, increased proppant pack volume, and increased maximum proppant concentration that can be placed. Improving proppant placement and increasing the volume that the proppant occupies within the fracture enhances the extent of the conductive fracture network, improving the productivity of the well. Laboratory results of regain conductivity, flow model, and sand suspension testing will be presented. A field case study will be provided based on treatments that were pumped in the Cardium formation in the Western Canadian Sedimentary Basin. The case study will illustrate how operational efficiencies and cost savings are possible without affecting production. Advantages include using less water while minimizing the occurrence of screenouts. Data will show that by adding this new technology to treat the proppant, production was enhanced significantly, greater than 30% in the case study provided.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".