New Hydraulic Fracturing-Fluid Technology Increases Production in the Barnett Shale and Reduces Impact on the Environment
Bibliographic record
Abstract
Abstract Hydraulic fracturing-fluid systems are used to create fractures in hydrocarbon-producing reservoirs and to transport proppant into the fracture to support it and provide optimum production increase. Many reservoirs in North America and the world would not be economical prospects without this technology. Currently, most systems use water-soluble polymers composed of guar or guar derivatives. Additional materials are used to optimize the fluid characteristics for the application and to degrade the water-soluble polymer, making the fluid easier to recover from the well before production. The recovered fluids cannot be used again and must be disposed of in a proper manner. A new hydraulic fracturing-fluid system has been developed that can provide excellent performance during the fracturing process with post-fracture treatment-fluid recovery approaching 100%. This fluid has the added benefit of being reusable after it is recovered following the treatment and before production. The benefits of reusing the treatment fluid include the cost savings associated with recovery and reuse of chemicals, the cost savings from reduced water volume requirements for subsequent treatments, and the elimination of disposal costs. In addition, the total volume of chemicals required for fracturing operations is significantly less, reducing the demand on the environment. Reuse of this fluid system requires field analysis of the returned fluid and treatment of the fluid to preserve and maintain it for future use. To achieve the best results from the recovery, preparations should be made to capture and store the fluid for subsequent treatments. This paper presents the application of the fluid system and the concept for recycling and reuse. The results of eleven treatments in the Barnett Shale in the Fort Worth Basin using the new fluid system and the recycled fluid system are provided.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".