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This presentation on the UKCCSRC Call 1 project, Flexible CCS Network Development, was presented at the Workshop1ES, 30.04.14. Grant number: UKCCSRC-C1-40.
Data identifying landscape areas (shown as polygons) attributed with type of mass movement e.g. landslip. The scale of the data is 1:50 000 scale. Onshore coverage is provided for all of England, Wales, Scotland and the Isle of Man. Mass movement describes areas where deposits have moved down slope under gravity to form landslips. These landslips can affect bedrock, superficial or artificial ground. Mass movement deposits are described in the BGS Rock Classification Scheme Volume 4. However the data also includes foundered strata, where ground has collapsed due to subsidence (this is not described in the Rock Classification Scheme). Caution should be exercised with this data; historically BGS has not always recorded mass movement events and due to the dynamic nature of occurrence significant changes may have occurred since the data was released. The data are available in vector format (containing the geometry of each feature linked to a database record describing their attributes) as ESRI shapefiles and are available under BGS data licence.
The images in this dataset are a sample of Doddington Sandstone from a micro-computed tomography (micro-CT) scan acquired with a voxel resolution of 6.4µm. This dataset is part of a study on the effects of Voxel Resolution in a study of flow in porous media. A brief overview of this study summarised from Shah et al 2015 follows. A fundamental understanding of flow in porous media at the pore-scale is necessary to be able to upscale average displacement processes from core to reservoir scale. The study of fluid flow in porous media at the pore-scale consists of two key procedures: Imaging reconstruction of three-dimensional (3D) pore space images; and modelling such as with single and two-phase flow simulations with Lattice-Boltzmann (LB) or Pore-Network (PN) Modelling. Here we analyse pore-scale results to predict petrophysical properties such as porosity, single phase permeability and multi-phase properties at different length scales. The fundamental issue is to understand the image resolution dependency of transport properties, in order to up-scale the flow physics from pore to core scale. In this work, we use a high resolution micro-computed tomography (micro-CT) scanner to image and reconstruct three dimensional pore-scale images of five sandstones and five complex carbonates at four different voxel resolutions (4.4ìm, 6.2ìm, 8.3ìm and 10.2ìm, scanning the same physical field of view. S.M.Shah, F. Gray, J.P. Crawshaw and E.S. Boek, 2015. Micro-Computed Tomography pore-scale study of flow in porous media: Effect of Voxel Resolution. Advances in Water Resources July 2015 doi:10.1016/j.advwatres.2015.07.012 We gratefully acknowledge permission to publish and funding from the Qatar Carbonates and Carbon Storage Research Centre (QCCSRC), provided jointly by Qatar Petroleum, Shell, and Qatar Science & Technology Park. Qatar Petroleum remain copyright owners
This presentation on the UKCCSRC Call 1 project, UK Bio-CCS CAP, was presented at the Cranfield Biannual, 22.04.15. Grant number: UKCCSRC-C1-38.
This poster on the UKCCSRC Call 1 project, Mixed Matrix Membrane Preparation for PCC, was presented at the Nottingham Biannual, 04.09.13. Grant number: UKCCSRC-C1-36.
This presentation on the UKCCSRC Call 1 project, Flexible CCS Network Development, was presented at the Cranfield Biannual, 22.04.15. Grant number: UKCCSRC-C1-40.
This is a blog (Update, 22.01.14) on the UKCCSRC Call 1 project, Mixed Matrix Membrane Preparation for PCC. Grant number: UKCCSRC-C1-36.
This presentation on the UKCCSRC Call 1 project, Oxyfuel and EGR Processes in GT Combustion, was presented at the Cardiff Biannual, 11.09.15. Grant number: UKCCSRC-C1-26.
This presentation on the UKCCSRC Call 1 project, Flexible CCS Network Development, was presented at the Workshop1, 30.04.14. Grant number: UKCCSRC-C1-40.
This project will tackle one of the key technical challenges facing the development of commercially viable CO2 transport networks: modelling the phase behaviour of impure carbon dioxide, under the conditions typically found in carbon capture from power stations, and in high-pressure (liquid phase) and low-pressure (gas phase) pipelines. Models for phase behaviour are known as equations of state (EoS). EoS vary in their mathematical form, accuracy, region of validity and computational complexity. Because different applications have different requirements, there is no single EoS that is ideal for all applications. This project will use cutting-edge computer algorithms to automatically reparameterise EoS for CCS modelling. This flexible technique will allow a user to specify their requirements and re-derive model parameters matched to their needs. Our algorithms will directly produce functional forms for EoS from experimental data, thus fully automating the derivation of EoS. This will enable users to rapidly produce bespoke EoS that are tailored to their particular application, and will enable these models to continually evolve as new measurements become available, ensuring that experimental advances are rapidly converted into improved CCS modelling and, ultimately, better performance and efficiency of real CCS processes. Grant number: UKCCSRC-C1-22.