Surrogate-assisted reservoir history matching

In the community of petroleum engineering, the use of surrogate modelling techniques have recently gained more and more popularity to improve the efficiency of history matching. However, it is still not possible to fully utilize their potential in realistic applications. One of the challenges is to retain high accuracy while increasing the...

Dust storm emission inversion using data assimilation

Severe dust storms present great threats to the environment, property and human health over the areas in the downwind of arid regions. Several dynamical dust models have been developed to predict the dust concentrations in the atmosphere. Currently, the accuracy of these models is limited mainly due to the imperfect modeling of dust emissions....

Towards a data assimilation system for morphodynamic modeling

Currently, available models are not able to accurately predict the temporal evolution of coastal morphodynamic processes. The main reason for this, is that essential components governing this evolution are neither fully identified nor understood. Additionally, there is high uncertainty in some of the parameterizations and their input parameters....

Data Assimilation for Marine Ecosystem Models

In the presence of environmental issues caused by climate change and eutrophication, ecosystem models capable of providing accurate predictions are of considerable interest. Even the most advanced ecological models are not capable of reproducing reality perfectly, therefore it is essential to integrate them with the available observations. Data...

Quantification of the impact of data in reservoir modeling

Global energy use is increasing. As societies advance, they will continue to need energy to power residential and commercial buildings, in the industrial sector, for transportation and other vital services. To satisfy this rising demand, liquid, natural gas, coal, nuclear power and renewable fuel sources are extensively developed. Particularly...

Model-reduced gradient-based history matching

Since the world's energy demand increases every year, the oil & gas industry makes a continuous effort to improve fossil fuel recovery. Physics-based petroleum reservoir modeling and closed-loop model-based reservoir management concept can play an important role here. In this concept measured data are used to improve the geological model, while...

A Generic Software Framework for Data Assimilation and Model Calibration

The accuracy of dynamic simulation models can be increased by using observations in conjunction with a data assimilation or model calibration algorithm. However, implementing such algorithms usually increases the complexity of the model software significantly. By using concepts from object oriented programming, this thesis proposes a software...

Data assimilation in reservoir management

The research presented in this thesis aims at improving computer models that allow simulations of water, oil and gas flows in subsurface petroleum reservoirs. This is done by integrating, or assimilating, measurements into physics-bases models. In recent years petroleum technology has developed rapidly. Nowadays wells can be drilled to a depth...

Error subspace filtering for atmospheric chemistry data assimilation modeling

Abstract not available

Data assimilation in atmospheric chemistry models using Kalman filtering

The problem of air pollution around urbanized area across Europe is strongly related to ozone. Ozone is a result of photo-chemical oxidation, and therefore an indication of the presence of pollutants. Overexposure to ozone is harmful to the health, and the concentrations are therefore measured on a regular basis to check exceedance of air...

Data assimilation in air pollution modelling