Publications

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Marine renewable energy devices require mooring and foundation systems that suitable in terms of device operation and are also robust and cost effective. In the initial stages of mooring and foundation development a large number of possible configuration permutations exist. Filtering of unsuitable designs is possible using information specific to the deployment site (i.e. bathymetry, environmental conditions) and device (i.e. mooring and/or foundation system role and cable connection requirements). The identification of a final solution requires detailed analysis, which includes load cases based on extreme environmental statistics following certification guidance processes. Static and/or quasi-static modelling of the mooring and/or foundation system serves as an intermediate design filtering stage enabling dynamic time-domain analysis to be focused on a small number of potential configurations. Mooring and foundation design is therefore reliant on logical decision making throughout this stage-gate process. The open-source DTOcean (Optimal Design Tools for Ocean Energy Arrays) Tool includes a mooring and foundation module, which automates the configuration selection process for fixed and floating wave and tidal energy devices. As far as the authors are aware, this is one of the first tools to be developed for the purpose of identifying potential solutions during the initial stages of marine renewable energy design. While the mooring and foundation module does not replace a full design assessment, it provides in addition to suitable configuration solutions, assessments in terms of reliability, economics and environmental impact. This article provides insight into the solution identification approach used by the module and features the verification of both the mooring system calculations and the foundation design using commercial software. Several case studies are investigated: a floating wave energy converter and several anchoring systems. It is demonstrated that the mooring and foundation module is able to provide device and/or site developers with rapid mooring and foundation design solutions to appropriate design criteria.

Desirable outcomes for geologic carbon storage include maximizing storage efficiency, preserving injectivity, and avoiding unwanted consequences such as caprock or wellbore leakage or induced seismicity during and post injection. To achieve these outcomes, three control measures are evident including pore pressure, injectate chemistry, and knowledge and prudent use of geologic heterogeneity. Field, experimental, and modeling examples are presented that demonstrate controllable GCS via these three measures. Observed changes in reservoir response accompanying CO2 injection at the Cranfield (Mississippi, USA) site, along with lab testing, show potential for use of injectate chemistry as a means to alter fracture permeability (with concomitant improvements for sweep and storage efficiency). Further control of reservoir sweep attends brine extraction from reservoirs, with benefit for pressure control, mitigation of reservoir and wellbore damage, and water use. State-of-the-art validated models predict the extent of damage and deformation associated with pore pressure hazards in reservoirs, timing and location of networks of fractures, and development of localized leakage pathways. Experimentally validated geomechanics models show where wellbore failure is likely to occur during injection, and efficiency of repair methods. Use of heterogeneity as a control measure includes where best to inject, and where to avoid attempts at storage. An example is use of waste zones or leaky seals to both reduce pore pressure hazards and enhance residual CO2 trapping.

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We propose a porous materials analysis pipeline using persistent homology. We rst compute persistent homology of binarized 3D images of sampled material subvolumes. For each image we compute sets of homology intervals, which are represented as summary graphics called persistence diagrams. We convert persistence diagrams into image vectors in order to analyze the similarity of the homology of the material images using the mature tools for image analysis. Each image is treated as a vector and we compute its principal components to extract features. We t a statistical model using the loadings of principal components to estimate material porosity, permeability, anisotropy, and tortuosity. We also propose an adaptive version of the structural similarity index (SSIM), a similarity metric for images, as a measure to determine the statistical representative elementary volumes (sREV) for persistence homology. Thus we provide a capability for making a statistical inference of the uid ow and transport properties of porous materials based on their geometry and connectivity.

We use helium released during mechanical deformation of shales as a signal to explore the effects of deformation and failure on material transport properties. A dynamic dual-permeability model with evolving pore and fracture networks is used to simulate gases released from shale during deformation and failure. Changes in material properties required to reproduce experimentally observed gas signals are explored. We model two different experiments of 4He flow rate measured from shale undergoing mechanical deformation, a core parallel to bedding and a core perpendicular to bedding. We find that the helium signal is sensitive to fracture development and evolution as well as changes in the matrix transport properties. We constrain the timing and effective fracture aperture, as well as the increase in matrix porosity and permeability. Increases in matrix permeability are required to explain gas flow prior to macroscopic failure, and the short-term gas flow postfailure. Increased matrix porosity is required to match the long-term, postfailure gas flow. Our model provides the first quantitative interpretation of helium release as a result of mechanical deformation. The sensitivity of this model to changes in the fracture network, as well as to matrix properties during deformation, indicates that helium release can be used as a quantitative tool to evaluate the state of stress and strain in earth materials.

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Greater Aneth oil field, Utah’s largest oil producer, was discovered in 1956 and has produced over 483 million barrels of oil. Located in the Paradox Basin of southeastern Utah, Greater Aneth is a stratigraphic trap producing from the Pennsylvanian (Desmoinesian) Paradox Formation. Because Greater Aneth is a mature, major oil field in the western U.S., and has a large carbonate reservoir, it was selected to demonstrate combined enhanced oil recovery and carbon dioxide storage. The Aneth Unit in the northwestern part of the field has produced over 160 million barrels of the estimated 386 million barrels of original oil in place—a 42% recovery rate. The large amount of remaining oil made the Aneth Unit ideal to enhance oil recovery by carbon dioxide flooding and demonstrate carbon dioxide storage capacity.

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