A CPP Model to Asphaltene Precipitation; Mapping p-p Interactions onto an Equation of State
Bibliographic record
Abstract
Abstract Asphaltene may destabilize during the oil recovery, transportation, and processing and cause significant flow assurance problems that negatively affect the operational expenditures (OPEX). Modeling investigation of asphaltene precipitation and consequently deposition is a vital research component in flow assurance requiring the accurate description of the phenomena under various operational conditions. The structure of asphaltene molecules and the presence of heteroatoms play a significant role in the intermolecular forces and the mechanism of asphaltene aggregation. Nevertheless, the intermolecular forces, e.g., polar forces, and their addition to thermodynamic modeling of asphaltene phase behavior still need investigation. While the traditional equation of state (EoS), e.g., cubic EoS, does not provide any special treatment to polar energy, the π-π interaction and polar effect can be mapped into the EoS using a separate polar term. In this research, we use cubic EoS, cubic plus polar (CPP) EoS, and molecular dynamics (MD) (three different modeling approaches) to analyze the effect of asphaltene structure and operational conditions on the precipitation phenomenon. Comparing the error associated with correlation and prediction results of the models, we show that the CPP approach using optimization to tune parameters of the EoS is the most reliable approach, followed by CPP EoS using MD to find dipole moment for the aryl-linked core asphaltene structure. The CPP EoS and MD optimizing island structure for asphaltene is the third-best model, and SRK EoS is a less efficient approach. Considering the values for dipole moment and molecular weight of asphaltene, along with correlation and prediction ability of the techniques, it is revealed that polar forces can be considered in a separate term in addition to van der Waals force to increase the model efficiency. Moreover, the aryl structure with a 750 g/mol molecular weight and one/two thiophene/pyridine group is the most proper asphaltene structure.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".