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Details of Grant 

EPSRC Reference: EP/T004282/1
Title: CBET-EPSRC: Enhancing the CSMHyK fluid dynamics calculations via the inclusion of a stochastic model of hydrate nucleation, agglomeration and growth
Principal Investigator: Striolo, Professor A
Other Investigators:
Stamatakis, Dr M
Researcher Co-Investigators:
Project Partners:
Colorado School of Mines Halliburton
Department: Chemical Engineering
Organisation: UCL
Scheme: Standard Research
Starts: 01 December 2019 Ends: 30 November 2022 Value (£): 487,426
EPSRC Research Topic Classifications:
Fluid Dynamics Multiphase Flow
Oil & Gas Extraction
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:
Panel DatePanel NameOutcome
08 Oct 2019 Engineering Prioritisation Panel Meeting 8 and 9 October 2019 Announced
Summary on Grant Application Form
Sir Humphrey Davy discovered clathrate hydrates in 1811. Hydrates are solid structures formed by water and gases, e.g., methane. The abundance of natural gas hydrate deposits across the world could provide abundant energy resources for the future, as well as long-term CO2 storage. Natural gas hydrates can be exploited in high-tech applications including innovative water-desalination and gas-storage processes. Prof. Carolyn Koh overviewed hydrates in the book she co-authored with Prof. Dandy Sloan: Clathrate Hydrates of Natural Gases, 3rd Ed., CRC Press, 2007.

This proposal is concerned with hydrate plugs in oil & gas pipelines. Such plugs can lead to pipelines ruptures, causing spills and environmental disasters, production interruptions, and even loss of life.

The traditional approach to manage hydrates is adding thermodynamic inhibitors (THIs), e.g., methanol. THIs shift the conditions at which hydrates are stable to lower Ts and higher Ps. However, large amounts of THIs are necessary, which negatively affects both the economics of the operations and their environmental impact. Among emerging promising technologies to prevent hydrates formation in pipelines is the use of 'low dosage hydrate inhibitors' (LDHIs), effective at low concentrations.

Among other limitations, the wide applicability of LDHIs is impeded by a current lack of understanding of how LDHIs function. In fact, LDHIs performance depends on oil composition, water salinity, temperature, etc. LDHIs include kinetic hydrate inhibitors (KHIs) and anti-agglomerants (AAs). This timely project will develop a fundamental understanding regarding how AAs function.

The project builds on significant prior results. For example, Prof. Koh and her group produced extensive experimental data regarding the performance of LDHIs, and developed extensive experimental characterisation capabilities to probe AAs at different length scales (from the microscopic, using micromechanical force measurements, to the macroscopic, using flow loops). Prof. Striolo employed molecular simulations to discover possible molecular mechanisms that are responsible for the performance of LDHIs (in particular, AAs). The simulation results led to new LDHIs formulations, environmentally benign, recently disclosed in a patent application.

To widely adopt LDHIs, it is required to develop reliable models that accurately describe the likelihood of hydrate plugs formation as a function of process conditions. This project will transform the pioneering software CSMHyK, which is already coupled with the industry-standard multiphase flow simulator OLGA. CSMHyK (1) describes accurately multi-phase transport in pipelines; (2) uses reliable equations of state to predict the hydrates thermodynamic stability; and (3) employs working assumptions to predict hydrates formation. To enable the latter feature, an important parameter is the nucleation sub-cooling, which is treated as an input parameter currently estimated from experimental flow-loop results, thus lacking predictability.

To render CSMHyK predictive, it is proposed to develop a model, based on kinetic Monte Carlo (KMC), to describe quantitatively the hydrate population dynamics as a function of system conditions. The new model will allow practitioners to quantify LDHIs' effects, which is currently not possible, as well as to include molecular-level information from microscopic experiments and molecular simulations into the formulation of risk assessment.

This NSF-EPSRC Lead Agency Agreement proposal builds on an Expression of Interest submitted to EPSRC on 04/08/2018, which was approved on 19/09/2018. The project benefits from strong industrial interest, and from established collaborations. The collaboration between Striolo and Koh was enabled by their industrial partner Halliburton and by a Royal Society International Collaboration grant. Striolo and Stamatakis collaborate in a project in which KMC was implemented to study fluid transport.

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