Gas-Condensate Relative Permeability Curves Determined from Separator Test Data: Britannia Field Case Study
Bibliographic record
Abstract
Abstract This paper presents a methodology for determination of gas-oil relative permeability curves using well performance data from retrograde condensate wells. Computations are based on PVT, producing gas-oil ratio, flowing bottom-hole pressure and material balance. The methodology presented was successfully applied to Britannia wells across the field, and findings were verified with numerical simulation to show proper modeling of condensate banking. Production performance of Britannia wells is monitored through back-pressure curves, constructed by plotting single-phase pseudo-pressure difference versus flow rate on log-log scale, using individual well separator test data. As condensate accumulates near the wellbore, reducing productivity, well performance deteriorates (points move left) from the established pseudo steady state (pss) deliverability line. Once productivity deterioration becomes negligible, the well performance response shows a linear trend. The empirical deliverability equation, delta pseudo-pressure versus flow rate log-log, yields a linear relationship with a slope of (1/n). Using this relationship, n is determined from the observed well deliverability line, shifted left due to condensate blockage. The coefficient C is then calculated at the pss deliverability line by assuming that the coefficient n remained unchanged. With accurate gas-oil relative permeability data included in the two-phase pseudo-pressure integral, plotting delta two-phase pseudo-pressure versus flow rate for separator test points should develop an alignment with the pss deliverability line. An objective function is defined as the difference between the delta pseudo-pressure, determined using the empirical deliverability equation, and the measured delta two-phase pseudo-pressure for separator test flow rates. The process outlined in this paper aims to find a gas-oil relative permeability curve that produces the best alignment, that is, the minimum objective function. In complex fields, e.g. Britannia, multiple gas-oil relative permeability curves might be needed to model condensate banking. In the absence of relative permeability data, the presented approach could provide valuable information on relative permeabilities.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".