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Record W2315921930 · doi:10.4043/otc-19869-ms

Understanding Kinetic Hydrate Inhibitor and Corrosion Inhibitor Interactions

2009· article· en· W2315921930 on OpenAlexaff
J. A. Moore, Leonard Ver Vers, Peter Conrad

Bibliographic record

VenueProceedings of Offshore Technology Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsNalco (Canada)
Fundersnot available
KeywordsCitationComputer scienceEngineeringLibrary science

Abstract

fetched live from OpenAlex

SS: Flow Assurance: Understanding Kinetic Hydrate Inhibitor and Corrosion Inhibitor Interactions Jennifer Moore; Jennifer Moore Nalco Company Search for other works by this author on: This Site Google Scholar Leonard Ver Vers; Leonard Ver Vers Nalco Company Search for other works by this author on: This Site Google Scholar Peter Conrad Peter Conrad Nalco Company Search for other works by this author on: This Site Google Scholar Paper presented at the Offshore Technology Conference, Houston, Texas, May 2009. Paper Number: OTC-19869-MS https://doi.org/10.4043/19869-MS Published: May 04 2009 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Moore, Jennifer, Vers, Leonard Ver, and Peter Conrad. "SS: Flow Assurance: Understanding Kinetic Hydrate Inhibitor and Corrosion Inhibitor Interactions." Paper presented at the Offshore Technology Conference, Houston, Texas, May 2009. doi: https://doi.org/10.4043/19869-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsOffshore Technology ConferenceOTC Offshore Technology Conference Search Advanced Search AbstractKinetic Hydrate Inhibitors (KHI) are increasingly becoming more prevalent in the oil and gas industry, thus the knowledge of how they impact other oilfield chemicals becomes important. This paper will attempt to explain how these products impact both the KHIs and corrosion inhibitors (CI) performance in the presence of each other. Application: This paper will address fundamental properties of both chemistries and how their interaction can be understood at the molecular level. Ultimately, this fundamental understanding allows for a more informed selection of KHI and CI for sub-sea applications. Results, Observations, and Conclusions: A more in-depth understanding of how KHI and CI interact with each other will allow for better selection of these products and will help develop the next generation of these chemistries. By understanding at the molecular level more favorable selection can be made and problems of negative interaction can be avoided. This work will explore the possibility of two separate mechanisms that can cause KHIs and CIs to negatively impact each other. The two mechanisms will be explored by using LC/MS (Liquid Chromatography Mass Spectrum) and SFT (Surface Tension measurement) with the results from these exploratory techniques correlated to performance testing for both KHIs and CIs we hope to gain a better grasp of the underlying issue. Significance of Subject Matter: The compatibility of the KHI with the CI is not a well-understood phenomenon and this paper will address this compatibility from a chemistry point of view. Therefore, this provides a more fundamental insight into the interactions of KHI'S and CIs.IntroductionThe oil and gas industry is relying on more and more on chemical solutions for flow assurance and corrosion inhibition, however these chemicals not only interact with the environment they can interact with each other. Several papers (Frostman, L.M et al, Fu, B, Graham, G.M et al, Swanson, T.A et al and McDonald, A.W.R et al) have addressed this interaction highlighting, negative, positive or neutral impact from a performance standpoint. A literature review revels that none have delved into the chemistry of Kinetic Hydrate Inhibitors (KHI) and Corrosion Inhibitors (CI) to explore the interaction from a more fundamental viewpoint. Klomp et al (Klomp, U et al) reports that the origins of these incompatibles are still unknown. This stems from the fact that chemical vendors are hesitant to divulge chemical compositions to the industry. This paper will discuss the interaction of the KHIs and CIs at a fundamental level with the hope that a deeper understanding of why these incompatibilities exist will then enable a better-informed decision of a particular KHI and CI for an individual asset.Hydrate inhibition has traditionally used mechanical methods to avoid hydrate formation by preventing their formation this was accomplished utilizing heated/insulated pipes or by gas dehydration. Another conventional means of preventing hydrates is utilization of Thermodynamic Hydrate Inhibitors (THIs) such as methanol and monoethyleglycol. More recently hydrate control has been achieved through the use of Low Dosage Hydrate Inhibitors (LDHI). LDHI use has allowed for lower volumes of chemical to be employed. The two types of LDHI are anti-agglometerates (AAs) and kinetic hydrate inhibitors (KHIs). AA's allow the hydrate crystals to form but manage the size of the crystals so that they can be dispersed in the hydrocarbon fluid. The surfactant molecules are able to surround the hydrate crystal and prevent crystal growth. AAs are typically used for severe hydrate conditions and long shut-in periods. On the other hand KHI's interfere with the crystal nucleation process, thus delaying the onset of hydration for a significantly longer period of time. KHI's are typically used at more moderate sub-cooling and can be used at a wide variety of water cuts. LDHI's are typically of polymer type chemistry and commonly versions of polyvinylpyrrolidone (PVP) and/or polyvinylcaprolactam as either homopolymers or co-polymers. Keywords: kinetic hydrate inhibitor, technology conference, ppm, cmc, surface tension, khi performance, corrosion rate, inhibitor, spectrum, interface Subjects: Production Chemistry, Metallurgy and Biology, Flow Assurance, Hydrates This content is only available via PDF. 2009. Offshore Technology Conference You can access this article if you purchase or spend a download.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.006
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0120.003

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.

Opus teacher head0.030
GPT teacher head0.223
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations28
Published2009
Admission routes1
Has abstractyes

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