Mitigating Downhole Calcite and Barite Deposition in the Montney: A Successful Scale Squeeze Program
Bibliographic record
Abstract
Abstract This technical paper addresses the challenges faced by Montney producers in northwestern Alberta and northeastern British Columbia due to downhole calcite and barite deposition. These scales lead to various issues such as production declines, pressure increases, decreased pump efficiency, and equipment failures. Additionally, the presence of Naturally Occurring Radioactive Materials (NORMs) associated with barite poses health concerns and disposal expenses. Continuously applied scale inhibitors are unable to reach the pay zone in the horizontal section, which has multiple fractures in a low-porosity and low-permeability formation. In response to these challenges, a comprehensive database of water analyses for the Montney was used to understand the variability in scaling ions. Scale modeling under bottomhole and topside conditions was conducted to gain insights into scaling dynamics. Laboratory performance of a range of system-compatible scale inhibitors was evaluated using dynamic scale loop and particle size analysis through focused beam reflectance measurement (FBRM) tests. The study focused on candidate wells with pump lifespans of less than three months, and scale squeezes were performed on both beam pump and gas lift wells. Drawing upon best practices from scale squeezes in the Saskatchewan, Montana, and North Dakota Bakken Formation, a scale squeeze program was developed. Monitoring during the program involved comparative water analyses, scale inhibitor residuals, and NORM monitoring. Results showed that the scale squeezes led to increased pump lifespans for beam-pumped wells, elimination of NORM in surface equipment, reduced acid cleanouts, and minimized downtime. The success of the scale squeeze program proved the feasibility of applying this approach in the Montney and offered support for its extension to other shale plays across Western Canada and worldwide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".