scholarly journals Solution of the Problem of Natural Gas Storages Creating in Gas Hydrate State in Porous Reservoirs

Mathematics ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 36 ◽  
Author(s):  
Nail G. Musakaev ◽  
Marat K. Khasanov

Underground gas hydrate storage of natural gas is a rather promising way of creating underground storage facilities for hydrocarbon raw materials in porous reservoirs. This paper presents a solution to the problem of the formation of CH4 hydrate in a porous medium during the injection of methane into a reservoir at a temperature lower than the initial temperature of the reservoir. Self-similar solutions of the problem in axisymmetric approximation are given, describing the pressure and temperature distribution in separate reservoir regions at the formation of gas hydrate on the frontal surface. On the basis of the method of sequential change of stationary states, an analytical solution was obtained, which allowed us to determine the position of the methane hydrate formation boundary depending on different parameters for any moment of time. The limits of the applicability of the proposed model are also given. Thus, the analysis of the calculation results showed that the constructed solution allows one to sufficiently and accurately determine the values of parameters at the frontal surface for a highly permeable medium (k0 > 10−13 m2). It was proved that in the case of a highly permeable medium, the methane hydrate formation intensity will be limited by convective heat dissipation during hydrate formation.

2008 ◽  
Vol 6 ◽  
pp. 178-183
Author(s):  
M.K. Khasanov ◽  
N.G. Musakaev

The features of the gas hydrates formation at the gas injection into the porous medium initially saturated with gas and water are considered. Self-similar solutions of the axisymmetric problem describing the distribution of the main parameters in a reservoir are constructed. The solutions have been found according to which the gas hydrate formation can occur at the frontal surface or in the extended area.


2021 ◽  
Author(s):  
Celestine Udim Monday ◽  
Toyin Olabisi Odutola

Abstract Natural Gas production and transportation are at risk of Gas hydrate plugging especially when in offshore environments where temperature is low and pressure is high. These plugs can eventually block the pipeline, increase back pressure, stop production and ultimately rupture gas pipelines. This study seeks to develops machine learning models after a kinetic inhibitor to predict the gas hydrate formation and pressure changes within the natural gas flow line. Green hydrate inhibitor A, B and C were obtained as plant extracts and applied in low dosages (0.01 wt.% to 0.1 wt.%) on a 12meter skid-mounted hydrate closed flow loop. From the data generated, the optimal dosages of inhibitor A, B and C were observed to be 0.02 wt.%, 0.06 wt.% and 0.1 wt.% respectively. The data associated with these optimal dosages were fed to a set of supervised machine learning algorithms (Extreme gradient boost, Gradient boost regressor and Linear regressor) and a deep learning algorithm (Artificial Neural Network). The output results from the set of supervised learning algorithms and Deep Learning algorithms were compared in terms of their accuracies in predicting the hydrate formation and the pressure within the natural gas flow line. All models had accuracies greater than 90%. This result show that the application Machine learning to solving flow assurance problems is viable. The results show that it is viable to apply machine learning algorithms to solve flow assurance problems, analyzing data and getting reports which can improve accuracy and speed of on-site decision making process.


Author(s):  
Eugenio Turco Neto ◽  
M. A. Rahman ◽  
Syed Imtiaz ◽  
Thiago dos Santos Pereira ◽  
Fernanda Soares de Sousa

The gas hydrates problem has been growing in offshore deep water condition where due to low temperature and high pressure hydrate formation becomes more favorable. Several studies have been done to predict the influence of gas hydrate formation in natural gas flow pipeline. However, the effects of multiphase hydrodynamic properties on hydrate formation are missing in these studies. The use of CFD to simulate gas hydrate formation can overcome this gap. In this study a computational fluid dynamics (CFD) model has been developed for mass, heat and momentum transfer for better understanding natural gas hydrate formation and its migration into the pipelines using ANSYS CFX-14. The problem considered in this study is a three-dimensional multiphase-flow model based on Simon Lo (2003) study, which considered the oil-dominant flow in a pipeline with hydrate formation around water droplets dispersed into the oil phase. The results obtained in this study will be useful in designing a multiphase flow metering and a pump to overcome the pressure drop caused by hydrate formation in multiphase petroleum production.


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