• Efficient Dimensionality Reduction Methods in Reservoir History Matching 

  Bratvold, Reidar Brumer; Hanea, Remus Gabriel (Peer reviewed; Journal article, 2021-05)

  Production forecasting is the basis for decision making in the oil and gas industry, and can be quite challenging, especially in terms of complex geological modeling of the subsurface. To help solve this problem, assisted ...

• Forecast of investment in renewable energy with consideration of dependency of investment in renewable energy and oil and gas prices 

  Waqar, Muhammad (Master thesis, 2021)

  Renewables are taking up the role of increasing importance in the energy industry, especially with the recent wave of the drop in prices of oil and gas. Therefore, oil and gas companies are gradually positioning themselves ...

• Upper Jurassic to Lower Cretaceous source rocks in the Norwegian Barents Sea, part I: Organic geochemical, petrographic, and paleogeographic investigations. 

  Cedeno Motta, Andres Felipe; Ohm, Sverre Ekrene; Escalona Varela, Alejandro; Marin Restrepo, Dora Luz; Olaussen, Snorre; Demchuk, Thomas (Peer reviewed; Journal article, 2021-09)

  This study provides a subregional to regional characterization of organofacies changes within the two members of the Upper Jurassic to Lower Cretaceous Hekkingen Formation (i.e. Alge and Krill) by integrating geochemical ...

• Multi-Attribute Seismic Analysis Using Unsupervised Machine Learning Method: Self-Organizing Maps 

  Mansoor, Syeda Vania (Master thesis, 2021)

  Seismic attributes are a fundamental part of seismic interpretation and are routinely used by geoscientists to extract key information and visualize geological features. By combining different findings from each attribute, ...

• A Decision Analysis Framework for Offshore Green Ammonia Project Investments 

  Valberg, Vegard (Master thesis, 2021)

  Ammonia has great importance to our daily lives – it is used in household cleaning products and to make agricultural fertilizers. Recently it has attracted attention from the energy sector, since it can be used as a ...

• Sequence Stratigraphic Evaluation of Lower Goru Sequence (Massive Sands) and Sembar in Block ‘X’, Lower Indus Basin, Pakistan 

  Syed Muhammad Ahmed Hassan (Master thesis, 2021)

  Block ‘X’ is situated in the prolific oil- and gas-producing Lower Indus Basin of Sindh Province, Pakistan where the Sembar-Goru Petroleum System features high-quality prodeltaic to open marine source rocks in the Lower ...

• Conditional data generation for an improved diagnosis in prostate cancer 

  Parvez, Omer (Master thesis, 2021)

  Prostate Cancer is the second most common cancer in men worldwide, the fourth most commonly occurring cancer overall and the sixth leading cause of cancer death among men worldwide. Early detection of prostate cancer is ...

• Unsupervised Learning for Prostate Tumor Detection 

  Habib Ullah (Master thesis, 2021)

  The detection of a lesion in the prostate can be a challenging task and is crucial for the early diagnosis of Prostate Cancer (PCa). Magnetic Resonance Imaging (MRI) examination provides a comfortable and precise solution ...

• Investigation of torsional drillstring motion using finite element model 

  chevuri rishyank (Master thesis, 2021)

  In the thesis , a four degree of freedom dynamic drill string model suitable for prediction of self-excited torsional vibrations is modeled using the finite element method. The drill string equation of motion subjected to ...

• Reinforcement Learning for Automated Power Grid Operation: Can a machine be trained to operate a power grid? 

  Bueno, Rebecca Santana (Master thesis, 2021)

  The increasingly high demand and amount of renewable energy sources in the power grid have added more complexity to power grid operations. The electrical power system must ensure that the generated power and the consumed ...

• 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 ...

• Multiple Wave Approximation Algorithm for Solving Hyperbolic Partial Differential Equations 

  Tong, Sian Huey (Master thesis, 2021)

• Numerical modelling of reverse circulation cementing with density unstable displacements in eccentric annulus 

  Bjelland, Anders (Master thesis, 2021)

  This dissertation investigates the mechanics involved in reverse circulation cementing (RCC) with numerical modelling. Numerical simulations are done by utilising a computational fluid dynamics (CFD) software (OpenFOAM). ...

• Use of Machine Learning For Stuck Pipe Prediction 

  Wijayaseelan Winusan (Master thesis, 2021)

• Investigating the Effect of Injection Rate and Oil Viscosity on Oil Recovery during Waterflooding 

  Yeboah,Kofi Kankam (Master thesis, 2021)

  For over a century, waterflooding of oil reservoirs have been performed to improve oil recovery for two reasons: to provide pressure support to the reservoir and to displace the oil entrapped in the pores of the rock. ...

• Machine Learning techniques for Prediction of Rock Properties from Reservoir Well Logs 

  Skjeldal, Miranda Ebsworth (Master thesis, 2021)

  Estimation of reservoir parameters is important in reservoir evaluation and estimation of petroleum volume. Reservoir parameters such as oil saturation, water saturation and porosity are derived from petrophysical logs or ...

• Predicting appointment attendance at an outpatient clinic 

  Upreti Megh (Master thesis, 2021)

  Abstract Background and aim: No-show, refers to patients who do not show up in the scheduled appointment, which is a serious problem for many years in the hospital. Also, the no-show rates differ in countries because of ...

• A study of machine learning models application for porosity prediction using petrophysical well logs. Case Study: The Brent Group – Statfjord field 

  Benjamin Chinedu Nelson (Master thesis, 2021)

  The use of machine learning algorithms for predictive analytics is making a growing impact in the field of petroleum geosciences. With the increasing cost and time-related factors for obtaining accurate porosity measurements ...

• Optimization of a smart water composition for Enhanced Oil Recovery study by wettability alteration in carbonates at high temperature. 

  Ullah, Hidayat (Master thesis, 2021)

  Seawater due to its wettability modifying qualities has proved to be an excellent injection fluid in chalk. At high temperature seawater alter wettability towards more water-wet conditions thus improving the overall oil ...

• Machine learning based shale volume prediction from the Norwegian North Sea 

  Ali, Mohammed (Master thesis, 2021)

  Petroleum geosciences, like other fields, has entered the era of new advanced technologies to handle problems related to complex massive data sets and decision making. The growing quantity of subsurface datasets has created ...

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