Running Two BHP Gauges to Determine Fracture Growth and Entry Pressure: A Case Study in Canada
Bibliographic record
Abstract
Abstract Hydraulic fractures are sometimes designed to start in an upper pay zone and grow into a lower pay zone(s) to avoid generation of multiple fractures during the treatment or to prevent sand production. For such treatments, there is no published methodology to confirm if the fracture actually grows into the lower pay zones. Another issue that engineers must address is that the measured pressure in the wellbore always includes the entry pressure (perforation, microannulus and/or tortuosity), complicating pressure interpretation and making fracture diagnosis difficult. This paper discusses how running two non-communicating bottomhole pressure (BHP) gauges for a fracture treatment gives reliable and useful information about height growth, and entry pressure. Moreover, the proposed configuration of BHP gauges gives a continuous, direct fracture pressure measurement without being affected by any entry pressure; i.e., the pressure immediately inside the fracture is measured. We will present a field case where such a configuration was used to confirm that the fracture originated in the upper pay zone and grew through a 7-ft thick shale to connect a lower pay zone. Two gauges were run as follows: one memory gauge below a bridge plug to monitor the lower perforated pay zone, and one surface readout gauge (real time) within the frac string to monitor the bottomhole pressure of the upper perforated zone being treated. For this case we confirmed that the fracture did indeed grow into the lower pay zone during both the minifrac and the main treatment. We were also able to measure exactly how much entry pressure was present during both the minifrac and the main treatment. In addition, conflicting pressure behaviors from the two gauges were observed during a sequence of injections and shut-ins and are explained later in the paper. The explanation leads to the conclusion that a conventional BHP measurement may yield pressure behavior that is misleading for pressure diagnostics.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".