A New Model for Describing the Adsorption of Asphaltenes on Porous Media at a High Pressure and Temperature under Flow Conditions
Bibliographic record
Abstract
Asphaltenes may generate production loss in oil reservoirs, because of several factors related to the interaction between the asphaltene molecules, aggregates, and the reservoir rock. Consequently, this could alter the wettability of the rock surface, increase the viscosity of the crude oil, and reduce the permeability of the porous media. In a previous study, we have developed the solid–liquid equilibrium (SLE) model based on Chemical Theory to describe the adsorption behavior of asphaltenes onto porous and nonporous solid surfaces. However, the SLE model neglects the effect of pressure on the interactions of asphaltene–asphaltene and asphaltene–aggregate–solid surfaces of the reservoir rock primarily under reservoir conditions (RC). Thus, in this study, to account for the effect of pressure, a modification to the previously developed SLE equation is presented. In this study, a novel and original model—called the SLE-RC model of adsorption—has been proposed to describe the adsorption mechanism mainly under reservoir conditions, for which the pressure and temperature effect has been evaluated. This model describes the temperature–pressure−dependent adsorption isotherms with five parameters: the maximum amount adsorbed, the constant of the i -mer reactions, Henry’s law constant, the molar volume, and the solubility parameter of the asphaltenes. The proposed model has been validated with adsorption tests on porous media under flow conditions at different pressures and temperatures. The dynamic adsorption experiments were performed at different asphaltene concentrations (100–2000 mg/L), pressures (6.89–17.24 MPa), and temperatures (313–353 K). The SLE-RC model was successful validated using more than five experimental data describing the adsorption isotherms of the asphaltene onto a packed bed of silica sand at high pressure and temperature and following a Type III behavior with root-mean-square errors (RMSE%) below 2%. In addition, the packed sands used in the adsorption tests were analyzed based on surface and color changes using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX) analysis, and polarized light microscopy (PLM); the results were in agreement with the SLE-RC model parameters.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".