Confined Behavior of Hydrocarbon Fluids in Heterogeneous Nanopores by the Potential Theory
Bibliographic record
Abstract
Abstract Nanopores in tight and shale reservoirs have been confirmed by numerous studies. The nanopores are not only the primary storage space of oil and gas, but also the main transport channels of confined fluids. Although considerable efforts have been devoted to study the confined behavior of hydrocarbon fluids in nanopores, most of them have a local smooth-surface assumption. The effect of pore heterogeneity is still lacking. In this paper, in order to effectively simulate the nanopore complexity, we propose the assumptions of furrowed surface and sinusoidal surface to represent the heterogeneous nanopores (or rough nanopores) in tight and shale rocks. Then, based on these assumptions, the multicomponent potential theory of adsorption (MPTA) is coupled with the Peng-Robinson equation of state (PR EOS) to investigate the behavior of hydrocarbon fluids in rough nanopores. In this theory, considering the different types of nanopore heterogeneity, the geometrical heterogeneity is modeled by a spatial deformation of the potential field, and the chemical heterogeneity is modeled by an amplitude deformation of this field. The fluid-fluid interactions are modeled by the PR EOS, and the fluid-surface interactions are modeled by a Steel 10-4-3 potential for slit-like nanopres and a modified Lennard-Jones (LJ) 12-6 potential for cylindrical nanopores. Then a prediction process for the behavior of methane, ethane, propane and their mixtures is performed. The results are compared against the experimental data of their adsorption isotherms from publishd literatures to validate the accuracy of the theory and process. Then, the effect of pore heterogeneity on the confined behavior of methane, ethane, propane is quantitatively studied. Results indicate that for the experimental data considered in this work, the theory for heterogeneous nanopores is capable of predicting the confined behavior of hydrocarbons in a wide range of pressure and temperature. The developed mathematical model can well predict the confined behavior of fluids both in slit-like and cylindrical nanopores. Compared with the results of a smooth pore surface, the geometrical heterogeneity can significantly affect the thermodynamic properties of hydrocarbon fluids, but the chemical heterogeneity cannot strongly distort the confined behavior of fluids. The effect of geometrical heterogeneity on the confined behavior of fluids mainly depends on the effective pore size. In hydrocarbon fluids, as the composition of heavy components increase, the effect of heterogeneity on the confined behavior of fluids is reduced. Also, as the nanopore size reduces, the effect of pore heterogeneity on the confined behavior of fluids is enhanced. For fluid mixture, compared with smooth surfaces, it is observed that for heterogeneous surface, the mole fraction of the heavy component in the vicinity of pore wall can increase significantly, and that of the light component is reduced. This investigation makes it possible to completely characterize the confined behavior of a confined fluid in heterogeneous nanopores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".