Bibliographic record
Abstract
Abstract Inflow Control Devices (IDCs) were initially developed to avoid water coning problems in long horizontal wells. They have been used with success the past 15 years. There are, however, issues that needs to be resolved. A pressure drop model of the ICD is presented herein. The physical model of the ICD consists of pressure drop equations from the reservoir, through the screen, through the flow conduit, through the ICD nozzle and into the production tubing, and, pressure drop through the lower completion system. Evaluation of the model shows that for current commercial tools, turbulent flow through the ICD dominates the pressure drop, leading to a density controlled flow. This is fortunate as density varies much less than viscosity over the production life of a field. Due to the inherent non-linear nature of a production system, the pressure drop versus flow rate will vary with degree of depletion. An ICD may be optimal initially, but not when the reservoir pressure is depleted. This paper also presents a new designer IDC concept which maintains constant flow regardless of the degree of field depletion. It is based on a hydraulic feedback principle, and ensures controlled flow throughout the life of the oil field.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".