Annular Pressure Build-up Analysis and Methodology with Examples from Multifrac Horizontal Wells and HPHT Reservoirs
Bibliographic record
Abstract
Abstract Annulus pressure build-up (APB) remains an important design consideration for many wells, not just deepwater or subsea wells. This paper outlines a step-by-step methodology for analysing APB issues applicable to any type of well. Analyses of APB scenarios for a tight chalk oil reservoir and an HPHT gas-condensate reservoir in the Danish Sector of the North Sea are used to demonstrate the methodology. APB is a potentially serious issue with HPHT wells created by annuli that heat up during production. The increased temperatures cause fluid expansion that can potentially over-stress the casing and tubing if not mitigated. Specific issues for HPHT wells are presented. The significant increase in the use of multi-stage horizontal fracturing systems with open or cased hole packers and ball or intervention operated sliding sleeves creates a fluid contraction threat. Overpressure through annulus fluid contraction caused by cooling has been rarely analysed. A case is shown to disprove a common belief that the fluid external to the sleeves equalizes with the reservoir over the time frame of the stimulation operation which prevents over-pressurization. Failure cases are presented along with the design calculations required to assess the combination of tubing ballooning, fluid contraction / expansion and transient reservoir flow. It is demonstrated that with cases of toe-to-heel stimulation combined with low reservoir permeabilities, significant transient drops in pressure external to the sleeves can occur. This can lead to tubing, sleeve or packer failures.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".