Hydraulic Fracture Containment in the Bakken With a Synthetic Polymer Water Based Fracture Fluid
Bibliographic record
Abstract
Abstract Hydraulic fracturing in the Bakken oil reservoir on the Canadian side of the Williston basin involves a risk of connection to the overlying water bearing formations. The Bakken reservoir is a tight dolomitic siltstone which requires multiple stage hydraulic fracturing in horizontal wells to achieve economic oil production rates. Within ten to fifty meters above the Bakken reservoir there often is a higher permeability water bearing interval in the Lodgepole limestone formation. If hydraulic fractures connect to the higher permeability interval in the Lodgepole, then water production and associated handling costs would greatly increase. Any loss of fracture fluid and proppant to the Lodgepole could also reduce effective fracture length within the Bakken and subsequently lead to lower oil production rates. To minimize the potential negative impact of partial hydraulic fracture growth out of zone, several strategies have been used. Some of these strategies include reduction of pump rate, slurry volume and fluid viscosity. Minimizing fluid viscosity without significantly reducing proppant suspension can be a challenge. To address this issue, a unique synthetic polymer water based fluid system with excellent proppant suspension characteristics has been field tested. This system has a viscosity between that of linear gel and typical crosslinked systems and has a unique breaking process. This fluid system has been used in multiple Bakken wells for over one year and field production results will be reviewed to demonstrate the effectiveness of the combined strategies in reducing water/oil ratios. The impact on oil production rates will also be reviewed. The paper will furthermore outline several challenges with deployment in the field. Fracture geometry simulation will be used to demonstrate the expected sensitivity of fracture containment to fracture fluid viscosity and pump rate.
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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 | 0.000 |
| 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".