Phase Behavior of Hydrocarbons in Shale Nanomatrix-Fracture System: Experiment and Simulation
Bibliographic record
Abstract
Abstract Currently, the methods of nanofluidic chip and molecular dynamics simulation have been widely applied to characterize the effect of nanoscale confinement on the fluid phase behavior in shale rocks. However, most of the published literatures just concentrate on the pure nanoscale pores. Actually, in shale rocks, the phase transition phenomenon of fluids is happened in a nanomatrix–fracture system, which highly differs from the pure nanoscale pores. In this work, we combine the methods of experiment and simulation to address the phase behavior of hydrocarbons in a nanomatrix–fracture system, which can effectively represent the actual pore space of fluids in shale. A new experimental device for the fluid phase behavior is firstly developed in this study, which is based on the conventional PVT test equipment. But for this newly-proposed device, the test cell is separated into two connected spaces. During experiment, one of them is filled with nanoporous material to represent the shale nano-matrix, and the other one is used to simulate the fracture system. Then, by using this device, through a step-wise reduction on the test cell volume, the bubble point pressure of a hydrocarbon mixture (C1/C8) is tested. The applied nanoporous materials in this study include MCM-41 (pore size: 4 nm) and SBA-15 (pore size: 2.5 nm). Through a comparison, the effect of nanopore size is analyze. Thereafter, the obtained experimental data are compared against the simulation results of our previous proposed mathematical model to discuss the effect of fracture system. Simultaneously, a set of Grand Canonical Monte Carlo (GCMC) simulation runs are also performed for the microscopic mechanisms for the nanoconfinement effect on fluid phase behavior. The obtained bubble point pressures of C1/C8 mixture in the SBA-15 and MCM-41 porous systems are 4.65 MPa and 4.80 MPa respectively. They are lower than the that of the pure bulk fluids (5.07 MPa). It can be found that with the nanopore size reduces, the deviation is obviously increased. Then, the experimental data is compared with the calculation results of our mathematical model (4.22 MPa and 4.37 MPa), it is found that without the consideration of fracture system, the bubble point pressure of hydrocarbons can be underestimated. Furthermore, based on the GCMC simulation results, it is found that the wettability characteristics of shale rock can significantly impact the phase behavior of hydrocarbons, while the pore size distribution in shale typically controls fluid phase transitions during production. This study provides a novel experimental method to characterize the fluid phase behavior in nanoporous shale rocks. Some important new insights are obtained to understand the complicated phase transition phenomenon in shale reservoirs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".