Evaluating Corrosion Inhibitors For Sour Gas Subsea Pipelines
Bibliographic record
Abstract
Abstract Using subsea carbon steel pipelines to transport wet sour gas possesses huge challenges to the operators to maintain the high level of the Assets and Operating Integrity. In many cases, carbon steel is still the primary choice for the subsea pipeline material. This choice significantly reduces the capital expense, and the industry has gathered a lot of successful experience in onshore facilities to mitigate the risk of using carbon steel. In order to produce and transport wet sour gas safely, corrosion of a subsea carbon steel pipelines must be controlled to prevent leaks. The common and effective way to mitigate corrosion risk of a subsea carbon steel pipeline is to apply corrosion inhibitor continuously, and in some cases in combination of batch corrosion inhibition. Selecting right corrosion inhibitor, deterring a right dosage, applying in a right way and at right time (4R) become extremely critical to the successes of pipeline integrity management. Since simulated flow dynamics degraded certain inhibitor's performance, it is critical to include the flow parameter in the experimental evaluation of corrosion inhibitors for this application. The high surface area solids will compete against the steel surface for effective inhibitor molecules, raise the cost and reduce the effectiveness of the inhibition program. The paper describes the selection of corrosion inhibitors for protecting pipelines transporting wet gas containing relatively high concentrations of H2S and CO2, which requires special techniques and equipment. Solids generated from corrosion play a large role in performance of corrosion inhibition, particularly inhibitor adsorption, under-deposit corrosion and passivation. Localized corrosion is the primary concern rather than general wall loss in pipelines transporting wet sour gas. The corrosion inhibitor selection process simulates flow dynamics of the pipeline system in order to find the best corrosion inhibitor. The Rotating Cylinder Autoclave (RCA) and Impinging Jet (IJ) effectively demonstrate the flow dynamic performance of different corrosion inhibitors under field conditions. Corrosion product solids were examined by variety of techniques, including SEM, EDAX and particle size analysis. The results show that some corrosion inhibitors failed under flow dynamic conditions, while other do much better. The temperature effect was observable, but did not cause inhibitors to lose significant performance within operating range of the pipeline. Solids generated in these tests were characterized. They were iron sulfides with different morphologies. The high surface area framboids were found both suspended in the solution and loose adhered to the metal surface. A tight layer of iron sulfide was also observed. The layer is about 10 µm thick, impermeable and dense. It provides passivation except there are cracks and holidays, which could provide initiation spots for localized corrosion. The high surface area framboid solids will remove substantial amount of corrosion inhibitor due to adsorption. We found corrosion inhibitors that demonstrate low corrosion rates under flow dynamic conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".