Two-Phase Flow in Volatile Oil Reservoir Using Two-Phase Pseudo-Pressure Well Test Method
Bibliographic record
Abstract
Abstract When the bottomhole pressure (BHP) of volatile oil reservoirs falls below the bubblepoint pressure, two phases are created in the region around the wellbore, and a single phase (oil) appears in regions away from the well. The oil relative permeability reduces towards the near-wellbore region due to increasing gas saturation. This behaviour is quite similar to a gas-condensate reservoir below the dew-point, where the gas relative permeability is reduced due to the existence of a liquid bank around the wellbore. There are numerous publications in the literature concerning the behaviour diagnostic and well deliverability calculation in the case of gas-condensate reservoirs. However, the behaviour of volatile oil reservoirs is not well understood. This paper aims at understanding the behaviour of volatile oil reservoirs. We used reservoir compositional simulations to predict the fluid behaviour below the bubblepoint, and then exported the flowing bottomhole pressure to a well test package to diagnose the existence of different mobility regions. In this study, the applicability of the two-phase pseudo-pressure method on volatile and highly volatile oil reservoirs was investigated, and it was found that this method is a very powerful tool for the prediction of true permeability and mechanical skin. Also, this method is capable of distinguishing between mechanical skin and condensate bank skin, which can be very helpful for designing after-drilling well treatment and IOR process designs. Introduction In gas-condensate reservoirs, retrograde condensation occurs when the flowing bottomhole pressure declines below the dew-point pressure, creating four regions in the reservoir with different liquid saturations. Away from the well, an outer region has the initial liquid and gas saturation. Next, nearer the well, there is a rapid increase in liquid saturation and a decrease in the gas mobility where the liquid still is immobile. Closer to the well, an inner region is formed where liquid saturation is higher than the critical condensate saturation and both oil and gas phases are mobile. Finally, in the immediate vicinity of the well, there is a region with a lower liquid saturation due to capillary number (the ratio of viscous to capillary forces) effects. Such a region has been inferred from a number of experimental core studies at low interfacial tension and high flow rates. The existence of the fourth region is important because it counters the reduction in productivity caused by liquid drop-out. The various mobility zones described above can be identified by well test analysis, using a variety of analytical and numerical models(1–3). Well test analysis is now commonly used to identify and quantify near-wellbore effects, reservoir behaviour (i.e. zones of different mobilities and storativities) and reservoir boundaries. Finding all of this information from well tests in gas-condensate reservoirs, however, is challenging. This is due to changes in the composition of the original reservoir fluid and the impact of wellbore dynamics. Nonetheless, gas-condensate flow behaviour is now reasonably well understood.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".