Hydrocarbon Flow Assurance: Low Rate and Pressure Gas Field Experience
Bibliographic record
Abstract
Abstract In the early life of most gas wells, there is sufficient reservoir pressure and flow rate to assure reliable evacuation of associated fluids from the reservoir/wellbore to the surface facility. In unconventional plays and in the case of Deep Basin gas field, this natural flow phase is usually short with a characteristic hyperbolic decline. When gas flow reaches critical velocity i.e. the minimum required velocity to lift out the liquids, pressure drop as a result of the hydrostatic head of liquid that is being left behind in the wellbore, increases till the well eventually stops flowing. Reduced rates and ultimate recovery due to liquid loading has significant impact on the economics of tight gas developments. The methods (timer cycling, foam, plunger, velocity string) presented in this paper are relevant to many low rate and low pressure gas wells. These methods have been used singly or in combination to optimally utilize the reservoir's energy for long term flow assurance. Cost, rate and estimated ultimate recovery of the deliquification decision have been key driving factors in the pursuit of effective hydrocarbon flow. Challenges and lessons learned thus far for deliquification decisions in Deep Basin are discussed, including the criteria/requirements for each method, inflow performance, wellbore hydraulics, water dynamics (formation and condensed water), scale deposition, associated secondary benefits/complications and field data showing impact.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".