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(2021)ThesisThe Arabian basin was subject to several tectonic events, including Lower Cambrian Najd rifting, the Carboniferous Hercynian Orogeny, Triassic Zagros rifting, and the Early/Cretaceous and Late/Tertiary Alpine orogenic events. These events reactivated Precambrian basement structures and affected the structural configuration of the overlying Paleozoic cover succession. In addition to a 2D seismic array and several drill well logs, a newly acquired, processed 3D seismic image of the subsurface in part of the basin covering an area of approximately 1051 km2 has been provided to improve the understanding of the regional tectonic evolution associated with these deformation events. In this study, a manual interpretation is presented of six main horizons from the Late Ordovician to the Middle Triassic. Faults and folds were also mapped to further constrain the stratigraphic and structural framework. Collectively, this data is used to build a geological model of the region and develop a timeline of geological events. Results show that a lower Paleozoic sedimentary succession between the Late Silurian to the Early Permian was subject to localised tilting, uplift, and erosion during the Carboniferous Hercynian Orogeny, forming a regional unconformity. Subsequent deposition occurred from the Paleozoic to the Mesozoic, producing a relatively thick, conformable, upper succession. The juxtaposition of the Silurian rocks and Permian formations allows a direct fluid flow between the two intervals. Seismic analysis also indicated two major fault generations. A younger NNW-striking fault set with a component of reverse, east-side-up displacement affected the Lower Triassic succession and is most likely related to the Cretaceous and Tertiary Alpine Events that reactivated the Najd fault system. These fault structures allow vertical migration that could act as conduits to form structural traps. Manual mapping of fault structures in the study area required significant time and effort. To simplify and accelerate the manual faults interpretation in the study area, a fault segmentation method was developed using a Convolutional Neural Network. This method was implemented using the 3D seismic data acquired from the Arabian Basin. The network was trained, validated, and tested with samples that included a seismic cube and fault images that were labelled manually corresponding to the seismic cube. The model successfully identified faults with an accuracy of 96% and an error rate of 0.12 on the training dataset. To achieve a more robust model, the prediction results were further enhanced using postprocessing by linking discontinued segments of the same fault and thus, reducing the number of detected faults. This method improved the accuracy of the prediction results of the proposed model using the test dataset by 77.5%. Additionally, an efficient framework was introduced to correlate the predictions and the ground truth by measuring their average distance value. This technique was also applied to the F3 Netherlands survey, which showed promising results in another region with complex fault geometries. As a result of the automated technique developed here, fault detection and diagnosis were achieved efficiently with structures similar to the trained dataset and has a huge potential in improving exploration targets that are structurally controlled by faults.
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(2023)ThesisThe Australian continent provides an excellent canvas to study the impacts of dynamic topography due to the flat nature of the continent. Previous work into Australian studies of biota have mainly focused on climate being the main contributor to biotic distribution and evolution. This study will investigate the influence dynamic topography contributes to this evolution of the landscape and biota through implementing three landscape evolution models (AuM1, AuM2 and AuM3), created using Badlands software. These models will establish the impacts dynamic topography has to the evolution of the Australian landscape and biota over the last 40 million years. All three models possessed the same inputs of elevation, precipitation, sea-level and erodibility regions, however differed in their dynamic topography input. The first of these models (AuM1) involves a best fit model of the Australian continent with a dynamic topography input that was an accurate depiction of the dynamic topography within the Australian continent. The second model acted as a control model, with the subtraction of a dynamic topography input. Lastly the third model (AuM3) involved the input of a varying dynamic topography inconsistent with AuM1. The comparison of these models exhibits that changes to the Australian landscape have taken place. The main finding was the deposition rate of sediment changes between AuM1 and AuM2, where AuM2 possess lower rates of deposition in the northern region. With these lower rates of sediment deposition, there was an accompanying narrower confluence angle of river channels in the northeastern region, indicating a more arid environment for those simulations without dynamic topography (AuM2). With these new findings through the numerical modelling of the Australian continent new constraints to the evolution of the Australian landscape and biota have been gained.