石油与天然气研究

抽象的

Current Overview and way forward for the use of Machine Learning in the Field of Petroleum Gas Hydrates

Negi BS

Gas hydrates represent one of the main inflow assurance challenges in the oil painting and gas assiduity as they can lead to plugging of channels and process outfit. In this paper we present a literature study performed to estimate the current state of the use of machine literacy styles within the field of gas hydrates with specific focus on the oil painting chemistry. A common analysis fashion for crude canvases is Fourier transfigures Ion Cyclotron Resonance Mass Spectrometry (FT- ICR MS) which could be a good approach to achieving a better understanding of the chemical composition of hydrates, and the use of machine literacy in the field of FT- ICR MS was thus also examined. Several machine literacy styles were linked as promising, their use in the literature was reviewed and a textbook analysis study was performed to identify the main motifs within the publications. The literature hunt revealed that the publications on the combination of FT- ICR MS, machine literacy and gas hydrates are limited to one. Utmost of the work on gas hydrates is related to thermodynamics, while FT- ICR MS is substantially used for chemical analysis of canvases. Still, with the combination of FT- ICR MS and machine literacy to estimate samples related to gas hydrates; it could be possible to ameliorate the understanding of the composition of hydrates and thereby identify hydrate active composites responsible for the differences between canvases forming plugging hydrates and canvases forming transmittable hydrates.