Options
Bean, Christopher J.
Preferred name
Bean, Christopher J.
Official Name
Bean, Christopher J.
Research Output
Now showing 1 - 3 of 3
- PublicationDiffraction imaging of sedimentary basins: An example from the Porcupine Basin(Copernicus, 2021-04-30)
; ; ; ; iffraction imaging is the technique of separating diffraction energy from the source wavefield and processing it independently. As diffractions are formed from objects and discontinuities, or diffractors, which are small in comparison to the wavelength, if the diffraction energy is imaged, so too are the diffractors. These diffractors take many forms such as faults, fractures, and pinch-out points, and are therefore geologically significant. Diffraction imaging has been applied here to the Porcupine Basin; a hyperextended basin located 200km to the southwest of Ireland with a rich geological history. The basin has seen interest both academically and industrially as a study on hyperextension and a potential source of hydrocarbons. The data is characterised by two distinct, basin-wide, fractured carbonates nestled between faulted sandstones and mudstones. Additionally, there are both mass-transport deposits and fans present throughout the data, which pose a further challenge for diffraction imaging. Here, we propose the usage of diffraction imaging to better image structures both within the carbonate, such as fractures, and below.460 - PublicationAn Outlook on Seismic Diffraction Imaging Using Pattern Recognition(EAGE Publications BV, 2018-06-11)
; ; ; ; A seismic image is formed by interactions of the seismic wavefield with geological interfaces, in the form of reflections, diffractions, and other coherent noise. While in conventional processing workflows reflections are favoured over diffractions, this is only beneficial in areas with uniform stratigraphy. Diffractions form as interactions of the wavefield with discontinuities and therefore can be used to image them. However, to image diffractions, they must first be separated from the seismic wavefield. Here we propose a pattern recognition approach for separation, employing image segmentation. We then compare this to two existing diffraction imaging methods, plane-wave destruction and f-k filtering. Image segmentation can be used to divide the image into pixels which share certain criteria. Here, we have separated the image first by amplitude using a histogram-based segmentation method, followed by edge detection with a Sobel operator to locate the hyperbola. The image segmentation method successfully locates diffraction hyperbola which can then be separated and migrated for diffraction imaging. When compared with plane-wave destruction and f-k filtering, the image segmentation method proves beneficial as it allows for identification of the hyperbolae without noise. However, the method can fail to identify hyperbolae in noisier environments and when hyperbolae overlap.293Scopus© Citations 7 - PublicationWave height quantification using land based seismic data with grammatical evolutionAccurate, real time, continuous ocean wave height measurements are required for the initialisation of ocean wave forecast models, model hindcasting, and climate studies. These measurements are usually obtained using in situ ocean buoys or by satellite altimetry, but are sometimes incomplete due to instrument failure or routine network upgrades. In such situations, a reliable gap filling technique is desirable to provide a continuous and accurate ocean wave field record. Recorded on a land based seismic network are continuous seismic signals known as microseisms. These microseisms are generated by the interactions of ocean waves and will be used in the estimation of ocean wave heights. Grammatical Evolution is applied in this study to generate symbolic models that best estimate ocean wave height from terrestrial seismic data, and the best model is validated against an Artificial Neural Network. Both models are tested over a five month period of 2013, and an analysis of the results obtained indicates that the approach is robust and that it is possible to estimate ocean wave heights from land based seismic data.
423