The Remediation of Oilfield Asphaltenic Deposits: Near-Well-Bore Application
Bibliographic record
Abstract
Abstract Asphaltene deposition in petroleum production can cause major economic and safety issues for operators. The most commonly applied solution for remediation is a prolonged solvent soak with an aromatic petroleum solvent, such as toluene or xylene. In many cases, these solvents have demonstrated a low dissolving efficiency, and a high frequency of soaks is needed, resulting in unacceptable levels of deferred production. Nalco Champion has undertaken product development research to provide an appropriate chemical solution. The work presented here describes the technology and techniques used to design chemical product packages and are applicable to both onshore and deepwater production environments. Measurement of the overall solubility parameters of the chemical - deposit interactions, and their implications for product design will be discussed. The ability of the chemical to penetrate and break up the deposit matrix will also be described, as this is a significant factor for solvating efficacy. Finally, a proof-of-concept case history showing success in remediating near-wellbore asphaltene deposits will be presented. A remediation "pill" containing three separate chemistries was designed for an early-life Anadarko Gulf of Mexico subsea well experiencing asphaltene deposition issues in the lower tubing and near-wellbore region. The three chemistries composing the pill (products A, B, and C) were shown to act synergistically in laboratory studies and were highly effective in remediating field asphaltene deposition relative to pure aromatic solvent. The different make-up chemistries of the pill were targeted primarily to near-wellbore asphaltene deposition, and succeeded in increasing near-wellbore permeability. To deliver the chemistry to the affected area, the pill was deployed topsides between two steel pigs and displaced through the subsea flow loop using dead oil into the desired well. The pill volume was large enough to allow for bullheading though the affected downhole area and approximately five radial feet into the near-wellbore region. A thirty six hour static soak was then used to allow effective penetration and dissolution of the asphaltene deposit. Multiple ensuing crude flowback samples were tested for constituent chemical residuals, as well as for asphaltene content. Post-treatment well test data showed an immediate increase in the well productivity index (PI) from 0.73 to 3.8. Oil production also increased from 1,600 STB/d to 2,900 STB/d. The positive increase in production lasted just over three months before asphaltene re-accumulation began to decrease the PI. A second identical treatment was conducted 10 months later with even better results. The benefit of this novel remediation approach relative to traditional xylene soaks was highly apparent based on historical field data. Not only did it show a much greater asphaltene solvency and further increased oil rates, but it allowed for less frequent remediation events and deferred production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".