Analysis and Comparison of Paraffinic Field Deposits to Cold Finger Deposits on a Brazilian Campos Basin Crude Oil
Bibliographic record
Abstract
Abstract A platform in the Campos Basin of Brazil experienced paraffin deposition issues in the inner-field flowline. The paraffin deposition rate was relatively low; however the deposited wax was hard and very sticky making pigging of the line difficult. Comprehensive advanced analyses and characterization of the crude oil and the deposit were conducted to determine the nature of the hardness and stickiness of the deposit. As part of the study, paraffin modifiers were tested to see their effect on the volume, hardness and stickiness of the deposit. The analysis on the deposit that was treated with the paraffin modifier showed a reduction in the components of the deposit that caused the hardness and stickiness of the deposit, resulting in a softer less sticky deposit that is easier to remove by pigging. FT-ICR MS analysis of the field deposit identifies an enrichment of the high molecular weight polar crude oil components that could be the reason for the stickiness of the deposit. Introduction Crude oils contain high molecular weight paraffin hydrocarbons that may precipitate out of the crude oil and form a waxy solid phase when the oil is cooled (due to heat loss to the surroundings) during production and transport operations. Resultant plugging of the pipelines and clogging of transport equipment can often be a challenging problem to control and remediate.1-5 Pigging is one method of removing paraffin deposits from the pipe wall, but pigging programs can be ineffective if the deposited paraffin is hard and sticky. This problem has been experienced by a platform in the Campos Basin of Brazil due to the hard and very sticky nature of the paraffin deposit. The pigging program for the inner-field flowline has been difficult and it is unclear if the pigging program is effective in removing all of the paraffin deposit. A better understanding of the oil composition and the paraffinic hydrocarbons present in the crude oils was sought in order to recommend chemical mitigation strategy. Crude oil sample from the field and paraffinic field deposits were collected for a comprehensive characterization with various analytical techniques, and the effect of wax crystal modifiers was qualitatively examined as potential remediation for deposition. Differential Scanning Calorimetry was employed to study the wax crystallization behavior of the crude oil and the deposit. Paraffinic hydrocarbon distribution of the fluids was characterized with High Temperature Gas Chromatography (HTGC). Efficacy of the wax crustal modifiers was evaluated with established Pour point and Cold Finger Deposition tests. Compositional information on the crude oil sample and the untreated paraffinic field deposit and the lab generated cold-finger deposits was further elucidated via high resolution Fourier transform ion cyclotron resonance mass spectrometry. Negative ion Electrospray Ionization (ESI) and Atmospheric Pressure Photoionization (APPI) coupled to 9.4T Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (FT-ICR MS) were applied to attain extensive compositional knowledge of the fluids' hydrocarbon and hetroaromatic matrix.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".