Mohanty, Manasi Manjari (2018) Numerical Simulation of CO2 Sequestration to Enhance Methane Recovery using Multipoint Geostatistics. PhD thesis.
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Coal beds are extremely complicated porous medium with characteristics of heterogeneity, dual porosity and stress sensitivity. In the past decades, great achievements have been made to the simulation models of pressure depletion coal bed methane (CBM) recovery process and CO2 sequestration and enhanced coal bed methane (ECBM) recovery process. However, some important mechanisms are still not properly included. Among them, the most important is the influence of geo-mechanics. Due to its influence on the coal bed permeability, being the key parameter for the success of methane recovery process, changes drastically with alterations of in situ stresses and strains. In present reservoir simulators, the change of coal bed permeability is estimated with analytical models. Due to the assumptions and over simplifications analytical models have their limitations or problems in application.
In this research, in order to properly estimate the changes of permeability and porosity in the simulation of CO2 sequestration and ECBM recovery process, comprehensive permeability and porosity models have been developed with minimum assumptions and corresponding established simulation methods. Firstly, a set of porosity and permeability modeling using multipoint statistics simulation procedure is followed and application to these models in reservoir simulations is proposed. Using the models and simulation procedure, a sensitivity study mainly on the parameters related to change in coal bed permeability and deformation has been made for the CBM recovery process. On this basis of understanding, simulation of 2 phases flow (CO2 & CH4) for improving methane recovery is done by COMSOL software.
At last the porosity and permeability models and the simulation procedure are successfully applied. Simulation is completed by using Principal Component Analysis (PCA) and CO2 sequestration by using COMSOL software.
|Item Type:||Thesis (PhD)|
|Uncontrolled Keywords:||CO2 Sequestration; K-means clustering; multiple-point geo-statistics; Principal Component Analysis(PCA); Training image; 2 Phases Flow (CO2 & CH4)|
|Subjects:||Engineering and Technology > Mining Engineering > Mine Water|
Engineering and Technology > Mining Engineering > Mining Geomechanics
|Divisions:||Engineering and Technology > Department of Mining Engineering|
|Deposited By:||IR Staff BPCL|
|Deposited On:||22 Feb 2019 21:05|
|Last Modified:||22 Feb 2019 21:05|
|Supervisor(s):||Pal, B. K.|
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