Evaluation of Kinetic Hydrate Inhibitor Performance by High-Pressure Differential Scanning Calorimetry
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Bibliographic record
Abstract
Abstract Rocking-cell, autoclave, and flow-loop testing are traditionally used for evaluating KHI performance. These testing methods commonly require large quantities of chemicals, can be time consuming, and require a large number of replicate runs to statistically evaluate KHI performance. It is highly desired to develop a test method for screening KHIs in a quicker manner than traditional methods. This paper discusses a new potential method for evaluating KHI performance, which utilizes a high-pressure differential scanning calorimeter to study the nucleation of hydrates in a stable water-in-oil test matrix. Although the limits of the DSC method do not allow testing under exact field conditions, nor under shear conditions, it could be used to facilitate quicker initial screening of KHIs during product development, and determine compatibility trends with other production chemicals/fluids. Since hydrate formation is a stochastic event a large number of traditional experiments are required to account for the dispersion of nucleation times. To provide a higher statistical output a stable water-in-oil test matrix was used in DSC testing. A low water-cut was used to generate a stable emulsion with a monomodal water droplet size of <10 µm. The low water-cut and small monodisperse droplet size inhibits inter-droplet interactions. Additionally, the small monomodal droplet size combined with the limited inter-droplet interactions, promotes a uniform probability and largely independent formation of each droplet to hydrate. Providing a high statistical output for each test, as each droplet nucleation can be compared to a single rocking-cell or autoclave experiment. The overall time frame for obtaining KHI performance trends is thus drastically reduced from traditional test methods. The HP-DSC method has been evaluated in parallel studies performed by Nalco and CSM to examine hydrate nucleation trends with uninhibited and KHI inhibited fluids. The data from a select number of KHI inhibited experiments will be shown to illustrate the ability to discern between an uninhibited and inhibited system. The paper will also compare the similarity in performance trends in HP-DSC and traditional hydrate testing methods performed by Nalco. Introduction Chemical inhibition with kinetic hydrate inhibitor (KHI) is a common practice for management of natural gas hydrates during production of petroleum fluids. KHIs work to inhibit hydrate formation by delaying the nucleation and crystal growth phases of hydrate formation. Traditional laboratory test methods for evaluating KHI performance are conducted in high-pressure autoclaves, rocking-cells, and flow loops. These traditional test methods for KHI evaluation require a large number of runs and relatively long test times, to achieve statistically viable data. This is a direct result of the inherent dispersion in hold-times caused by the stochastic nature of hydrate formation. Where hold-time is the time hydrate formation occurs once inside the thermodynamically favorable hydrate formation region. During KHI development the longer test times and high number of replicate runs required result in an extended duration for identifying and developing improvements in KHI technologies. Therefore, it is desirable to develop a rapid method for screening KHI performance. Using a high-pressure differential scanning calorimeter (HP-DSC) new methods for studying hydrate nucleation and KHI performance were explored in collaboration with the Center for Hydrate Research at Colorado School of Mines (CSM).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it