Compositional Simulation of Condensate Banking Inside Hydraulic Fractures Coupled with Reservoir Geomechanics
Bibliographic record
Abstract
Abstract Horizontal wells with multistage hydraulic fracturing stimulation become the common practice in developing tight and shale gas reservoirs. For gas condensate reservoirs, heavier components in the gas phase start dropping and decrease the gas mobility due to a relative-permeability relationship as reservoir pressure drops below the saturation pressure. Therefore, modeling the condensate banking along hydraulic fractures becomes critical in understanding the productivity loss, the hydraulic fracturing job design as well as the field production optimization. In addition, along with pressure depletion, the stress dependent permeability must be taken into account either by an approximation derived from lab experiments inside a finite difference flow simulator or modeling separately by a finite element geomechanics code. A condensate fluid pseudoization that reduces nine hydrocarbon components to a pseudo three components mixture is presented in this paper. The control volume based multiphase multi-components thermal simulator FATS is utilized in modeling the condensate banking inside the hydraulic fractures and surrounding matrix blocks. A K-value interpolation algorithm is developed and validated by a two-phase envelope generated by an Equation of State (EOS). FATS results are validated by the EOS based reservoir simulator GEM. A compositional simulation model is coupled with reservoir geomechanics in this study to investigate the interaction of stress changes and its effects on multiphase flow along fractures. A modular coupled approach is implemented for solving the stress and flow equations at each time step by the iteration between the reservoir simulator and geomechanical module. Pressure and temperature changes occurring in the reservoir simulator are passed to the geomechanical simulator to compute the changing of stress and strain and updating porosity and permeability simultaneously. Simulation results show that fracture conductivity reduction is due to the combination of condensate banking and changing of the effective stress along hydraulic fractures.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".