Potential Use of Water Associated with Conventional Oil Production and Sea Water as Base Fluids for Hydraulic Fracturing Operations: Effect of Water Chemistry on Crosslinking and Breaking Behaviors of Guar Gum-Based Fracturing Fluid Formulations
Bibliographic record
Abstract
Even though water consumption per hydraulic fracturing (or fracturing) job is relatively low; nearly all of the fresh water used for fracturing in California is in the regions of high water stress such as San Jouquin and Los Angeles Basins. However, water availability should not be a concern as huge volumes of water are being produced along with oil and gas from conventional formations (i.e. associated water) in the Kern County of California, a region where most of the fracturing activities take place. This associated water can potentially be used for preparing fracturing fluids in stimulating the unconventional formations. The present study reports on the relevant investigation done in this area of interest.The results suggest that associated water chemistry has limited effect on the viscosity of cross-linked formulations. However, guar gum concentration was found to affect the breaking behaviors of cross-linked fracturing fluid formulations. The new type of commercially available biodegradable breaker was found to be effective in breaking the tested cross-linked formulations at elevated temperature which was as high as 85°C (185°F). Both crosslinking and breaking behaviors of fracturing fluid formulations evaluated in this study were found comparable to the behaviors of commonly used cross-linked formulation (guar gum + 2% potassium chloride). These results suggest that both the associated water (i.e. water resulting from regional conventional oil production activites) and sea water (offshore oil fields) could serve as alternative sources of base fluid for use in fracturing jobs without putting significant burden on precious regional fresh water resources.
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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 | 0.001 |
| 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".