Blar i Studentoppgaver (TN-IER) på forfatter "Schulte, Lothar"
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Applying Geological Process Modeling to a turbidite system in the northern North Sea
Nguyen, Hoang (Masteroppgave/UIS-TN-IER/2019;, Master thesis, 2019-06)In recent years, several mathematical methods, especially those based on geostatistics, have been used in reservoir characterization. The reliability of the static models derived from these techniques depends on available ... -
Comparison of facies models based on stochastic versus deterministic AVO inversion
Pindel, Adrian (Masteroppgave/UIS-TN-IER/2020;, Master thesis, 2020)This thesis compares facies models based on deterministic AVO inversion – which is a standard approach in the industry, and stochastic AVO inversion – which is a newer, less popular approach, but according to literature, ... -
Fracture analysis and modelling of the South Arne field
Adlakha, Khushal (Masteroppgave/UIS-TN-IER/2018;, Master thesis, 2018-06-14)Fractures are paramount elements in reservoirs, and they are omnipresent in almost all outcrops. The importance of fractures lies in their ability to provide permeable pathways and consequently increase the reservoir ... -
Geometrical and kinematical analysis of an extensional fault-propagation fold in the Wisting Field, Norwegian Barents Sea
Aksland, Marte (Master thesis, 2021)The Wisting field is located on the Bjarmeland Platform northeast of the Maud Basin and adjacent to the Hoop Fault Complex. It is Norway’s northernmost oilfield to be developed. 3D high resolution P-Cable seismic data from ... -
Low- versus high-resolution assessment of reservoir compartmentalization in the Wisting field, Norwegian Barents Sea.
Butar, Orlando (Master thesis, 2021)Wisting is Norway’s northernmost oil field under development. With ~500 mmboe in shallow marine to fluvial Upper Triassic to Middle Jurassic reservoirs, which are highly faulted and just 250-300 m below sea bottom, this ... -
Machine learning based seismic classification for facies prediction
Alvi, Aigul Taimour (Master thesis, 2023)This thesis explores the performance of machine learning (ML) methods for predicting facies from seismic attributes for 2D and 3D datasets. It focuses on building, training, and testing four supervised methods: Logistic ... -
Ml-based porosity modeling tested on synthetic and subsurface data
Salomonsen, Einar (Master thesis, 2022)This thesis investigates if synthetic porosity models are useful as a basis for comparison between machine learning (ML) approaches to porosity prediction. In addition to the ML methods, the sequential gaussian simulation ... -
Porosity prediction from seismic data of the F3 block, offshore Netherlands, through seismic inversion and machine learning
Umar, Muhammad (Master thesis, 2022)Porosity is a key rock property that influences reservoir quality and plays an important role in petroleum exploration and production. The most common sources of information for reservoir characterization are well and ... -
Quantitative seismic interpretation using converted PS waves: A case study from the Oseberg South Field, North Sea
Frette, Lars Ulsund (Masteroppgave/UIS-TN-IER/2018;, Master thesis, 2018-06)The converted wave (PS) seismic in combination with the compressional wave (PP) seismic may help in better description and understanding of subsurface stratigraphic and structural features. Since compressional and shear ... -
Time dependent signal of a chalk field: The South Arne Field, Danish North Sea
Tomasgaard, Mathias (Masteroppgave/UIS-TN-IER/2018;, Master thesis, 2018-06)Time-lapse seismic analysis is applied to a producing chalk field, with the aim to understand the field time-varying behaviour with respect to reservoir structure and fluid migration. The study area is the South Arne field ...