Numerical Modeling of Multi-mechanistic Gas Production from Shale Reservoirs
Bibliographic record
Abstract
Shale and ultratight gas reservoirs have recently been contributing to the energy industry and gas market to a large extent. The dynamics of shale gas transport in porous media is of practical importance in several scientific and engineering applications. The characteristics of the transport inside the pore space are governed by the mechanisms that occur at the pore level. Recent advances in computational power provide the opportunity to investigate these phenomena further. In this study, a methodology is developed to create a model in which all the major transport mechanisms involved in shale gas flow are taken into account. The mechanisms include viscous flow, gas slippage, Knudsen diffusion, competitive adsorption of different gaseous components, pore size variation and real gas effect. The model is then utilized on one hand to derive parameters such as apparent gas permeability and matrix-fracture fluid exchange term (a.k.a. shape factor) which can reduce the computational load while preserving the accuracy and on the other hand to study the response of shale gas reservoirs to the feasibility and potentials of carbon storage and enhanced gas recovery as well as phenomena such as nano-confinement and chromatographic separation. The compositional effects of shale gas can be lumped into a single component using the apparent permeability which deems to capture the relevant physics and can replace the Darcy permeability. The shape factor required for Darcy scale simulation of shale gas reservoirs obtained from the detailed numerical simulations of multi-mechanistic multi-component shale gas flow can be modeled versus dimensionless pressure to capture the transient behavior of the matrix-fracture fluid transfer in a time-independent fashion. The stronger adsorption of CO2 over CH4 to shale surface makes the partially depleted shale gas reservoirs a promising target for CO2 storage as well as enhanced natural gas recovery. Up to 55% of the injected CO2 can be trapped as adsorbed phase and up to 16% incremental methane recovery can be achieved. The phase behavior of the confined shale gas is significantly different than the behavior of the bulk fluid. Nano-confinement could shift critical properties significantly. The effect of confinement on phase diagrams and compositional variations of the gas in place was also investigated via numerical simulations. The computed apparent permeability and shape factor can be directly used in the macroscale reservoir simulators to accurately predict the performance of a shale gas reservoir and the outcomes of this study will find applications in the design and implementation of an efficient CO2 injection and investigating compositional effects in shale gas simulations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".