Hydrate Inhibition in Gas Wells Treated with Two Low Dosage Hydrate Inhibitors
Bibliographic record
Abstract
Abstract Two low dosage gas hydrate inhibitors, antiagglomerant type and a combination antiagglomerant/kinetic polymeric inhibitor have been successfully field tested in a gas producing well. The well located in Canadian foothills posed challenges for the operators. High pressure, low bottomhole temperature and Joule-Thomson gas decompression cooling effect created favorable conditions for gas hydrates at depths below 300 meters. The well would plug-up with hydrates daily in spite of being treated with 400-500 L of methanol. The operator experienced significant monetary losses due to lost production and had to use considerable amounts of chemicals and time to clean-up hydrates from plugged tubings. The inhibitors were applied downhole in 20% to 10% methanol solution. This novel approach allowed utilization of existing solvent storage and pumping equipment so that no capital spending was required when converting the hydrate prevention program from methanol to LDHI treatment. The combination inhibitor was diluted to 20% in methanol in a stock tank and pumped into the well at the approximate rate 30 L/day. Similarly, the antiagglomerant was initially used at 20% solution in methanol and later its concentration was lowered to 10%. The daily inhibitor treatment rate was established at 45 L. Laboratory results indicate the combination product is a better hydrate inhibitor than the antiagglomerant. However, the cost analysis favors the usage of less expensive antiagglomerant in this application. Following the successful treatment of one well, several more similar gas wells throughout the field were identified and converted from methanol hydrate prevention method to antiagglomerant treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".