Modeling PVT Behavior of Gas-Condensate System Under Pore Confinement Effects: Implications for Rate-Transient Analysis of Gas-Condensate Shale Plays
Bibliographic record
Abstract
Abstract Rate-transient analysis (RTA) is a robust technique for evaluating reservoir/stimulation properties and for forecasting production from shale reservoirs. However, knowledge of fluid storage and flow mechanisms, and controlling rock and fluid parameters, is critical for obtaining meaningful information from RTA. It is common practice to use PVT data measured in laboratories (i.e. bulk fluid properties) for reservoir modeling and production data analysis purposes. These measurement techniques were developed for conventional reservoirs and cannot explain some of the anomalous fluid production behaviors observed for shale gas-condensate wells, such as long-term constant gas/oil ratio (GOR) trends. One explanation for this behavior is that the PVT properties of fluids are affected by confinement in nano-scale pores, and hence deviate from bulk fluid properties. In order to study the effects of pore confinement on fluid properties in shales, the simplified local density (SLD) model is used. The SLD model can be used to estimate fluid density gradients from pore wall to pore center, and therefore explicitly considers pore geometry in adsorption modeling. This model can also be used to adjust the confined fluid critical properties, phase envelope and viscosity. Significant shifts in phase envelope and fluid properties due to pore confinement are observed in this work. Importantly, the corrected equation-of-state predicts a later onset for condensate dropout in shale reservoirs than for bulk systems. The SLD model is also used to estimate adsorbed layer thickness, which in turn is used to modify flow calculations. The corrections for fluid properties, adsorbed layer thickness and non-Darcy flow are then analytically incorporated into transient linear flow analysis of nanoporous shale gas-condensate wells. Analysis of simulated cases using the "corrected" (for pore confinement effects) and "uncorrected" RTA is performed to quantify errors associated with the latter. This study demonstrates that failure to account for pore confinement effects on fluid properties and fluid flow results in errors in linear flow parameter estimation using RTA, but the error depends on the fluid composition, pore size, permeability and pressure. The effects of pore confinement should therefore be considered for proper evaluation of shale gas-condensate reservoirs using analytical or numerical methods.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".