Coupling mechanism analysis of CO2 non-Darcy flow in multi-scale reservoirs: A case study of the life-cycle process of fracturing-development in shale oil reservoirs
Bibliographic record
Abstract
With policy support for carbon capture, utilization, and storage (CCUS), an integrated approach that combines energy storage fracturing, CO 2 -enhanced oil recovery (EOR), and storage emerges as a promising direction for the shale oil industry. The process of energy storage fracturing induces significant changes in the pressure and saturation of the medium. However, conventional simulations often overlook the effects of fracturing and shut-in operations on the seepage field and production performance. Furthermore, fractured shale reservoirs exhibit complex non-Darcy flow characteristics due to intricate pore structures and multi-scale porous media. A comprehensive understanding of flow mechanisms is essential for effective reservoir development and CO 2 storage. This study establishes a multi-component simulation model that encompasses the life-cycle of fracturing, shut-in, production, and CO 2 huff-n-puff processes, thereby ensuring the continuity of the seepage field. The model accounts for the effect of nano-confinement on phase behavior by modifying the equation of state. Furthermore, the flux term is adjusted to incorporate Maxwell–Stefan diffusion, pre-/post-Darcy flow, and stress sensitivity. The embedded discrete fracture model (EDFM) is employed to simulate multiphase flow within multi-scale media, and the results from the validation model align satisfactorily with those derived from ECLIPSE. Mechanism analysis indicates that the interaction of multiple mechanisms significantly influences both production and storage performance. Under the multi-mechanism coupling, the cumulative oil production increased by 12.01%, while the utilization and storage factors increased by 62.93% and 8.93%, respectively. The role of molecular diffusion in shale oil reservoirs may be overstated, contributing only a 0.26% enhancement in oil production. Simulation results show that the energy storage fracturing strategy can increase oil production and net present value by 12.47% and 15.07%, respectively. Sensitivity analysis indicates that the CO 2 injection rate is the main factor affecting the recovery factor, followed by CO 2 injection time and the number of cycles, with fracturing fluid volume having the least impact. This study develops a multi-process, multi-mechanism simulation framework for multi-scale shale oil reservoirs. This framework provides a robust evaluation system for CCUS-EOR, facilitating informed decision-making in fracturing stimulation, development planning, and parameter optimization.
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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) | 0.001 | 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".