Parameter and state estimation of a groundwater model using the Ensemble Kalman Filter

Groundwater is an essential ingredient in farming, knowledge about how this is expected to change over time can help farmers improve yields and save water. Predictions about the groundwater level can be made using a mathematical model. This model takes into account the precipitation and evaporation, the flux towards a deeper aquifer and flux to...

Parameter Estimation and Uncertainty Quantification for Core Flooding

In light of our depleting fossil fuel reserves and the relatively `cheap' extraction of oil and in spite of the highly nonlinear nature of reservoirs, waterflooding has become big business. In recent times, the use of numerical reservoir simulation has not only become possible but has increasingly been used in the petroleum industry in the...

Forecasting hydrodynamics using data assimilation: A case study in the North Sea

The need for accurate estimation of hydrodynamic and water quality model variables arises from the UNITED project, which aims to create high-resolutional forecasting systems for monitoring the cultivation of seaweed and flat oysters and operating of the Belgian pilot of UNITED in the coastal area of the North Sea. Accurate observations of...

Application of an inverse analysis using the Ensemble Kalman Filter method to a deep excavation case: with validation of constitutive soil models

Displacement control is of utmost importance in deep excavation design and is usually based on numerical modelling, e.g. Finite Element Method (FEM). Numerical methods tend to be more conservative when analysing soil behaviour during deep excavation, whereas for practical and economic reasons this is not favoured. The inverse analysis allows for...

Modelling epidemic spreading phenomena processes on networks

Spreading processes are ubiquitous in nature and societies, e.g. spreading of diseases and computer virus, propagation of messages, and activation of neurons. Computer viruses cause an enormous economic loss. Moreover, many illnesses/diseases still causing a serious threat to public health. For example, the outbreaks of circulating influenza...

Reducing Water Level Prediction Uncertainty in a Delfland Polder using Data Assimilation

Polder areas as typical in the Netherlands require real time control on the water levels. Efficient pumping is a subject with increasing interest due to a required use of 20% green energy by 2020 set by the government. In 2010, the energy requirements already exceeded 175 GWh per year. For optimal control, water level predictions are important....

Stochastic Nodal Analysis: EnKF and PF applied to petroleum production systems

A petroleum production system is generally modelled based on the concept of nodal analysis, where the entire system is broken down into discrete elements such as near-well bore, tubing, surface choke and flow line. Operating flow rates and pressures can be estimated with a nodal analysis procedure by calculation of the intersection of...

Assimilation of soil moisture data with the ensemble Kalman filter for the intermediate scale soil moisture predictions in the Netherlands

This thesis discusses the applicability of assimilation of artificial SMAP data into a quasi steady state hydrological model to improve soil moisture estimates. The model used for this research was SIMGRO and since no real SMAP data were available at the time of the research, artificial SMAP data were used. The ensemble Kalman filter was used to...