Dust storm forecasting through coupling LOTOS-EUROS with localized ensemble Kalman filter

Super dust storms re-occurred over East Asia in 2021 spring and casted great health damages and property losses. It is essential to achieve an accurate dust forecast to reduce the damage for early warning. The forecasting system fundamentally relies on a numerical model which can forecast the full evolution of dust storms. However, large...

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...

A maximum likelihood ensemble filter via a modified cholesky decomposition for non-gaussian data assimilation

This paper proposes an efficient and practical implementation of the Maximum Likelihood Ensemble Filter via a Modified Cholesky decomposition (MLEF-MC). The method works as follows: via an ensemble of model realizations, a well-conditioned and full-rank square-root approximation of the background error covariance matrix is obtained. This...

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...

Performing data assimilation experiments with hydrodynamic models: A Java Sea case

Floods are a big problem for Jakarta; the capital of Indonesia is subsiding below mean sea level and floods will become more frequent. Flood protection and measures against subsidence are, therefore, of high importance to Jakarta’s government. One of the options they are studying is a great sea wall to regulate the water levels in Jakarta Bay....

Model-based aviation advice on distal volcanic ash clouds by assimilating aircraft in situ measurements

The forecast accuracy of distal volcanic ash clouds is important for providing valid aviation advice during volcanic ash eruption. However, because the distal part of volcanic ash plume is far from the volcano, the influence of eruption information on this part becomes rather indirect and uncertain, resulting in inaccurate volcanic ash forecasts...

Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM

Hydraulic head data is frequently used for the calibration of groundwater flow models, usually with the main objective to improve the model performance. The hydraulic parameters in a groundwater flow model depend on the underlying geometry of the subsurface and the permeability of the soil. In the current calibration routines, the geometry is...

Parallelization of Ensemble Kalman Filter (EnKF) for Oil Reservoirs

This thesis describes the design and implementation of a parallel algorithm for data assimilation with ensemble Kalman filter (EnKF) for oil reservoir management. The implemented application works on large number of observations from time-lapse seismic, which lead to a large turnaround time for the analysis step, in addition to the time...

Assimilating Soil Moisture Data into a Hydrological Model of the Volta Basin

Soil moisture is important for the Volta Basin. However, in-situ measurements of soil moisture in the Volta Basin are scarce, only remote sensing observations are available. Remote sensing observations are also provided with limited temporal and spatial resolutions. Also capabilities of the sensors are limited (e.g measuring soil moisture...

A research on the optimization of the reservoir model

With a high demand of oil, optimization of oil output in the reservoir field is urgent and significant. Practical production problems often involve large, highly complex reservoir models, with up to thousands of unknowns and many constraints. Moreover, our understanding of the reservoir is always highly uncertain, and this uncertainty can be...

A comparative performance evaluation of nonlinear observers for a fed-batch evaporative crystallization process

Different nonlinear observers are compared throughout this work where they are part of an NMPC framework used to control a fed-batch crystallization process . We study which observer-optimizer pair offers the best control performance while maintaining adequate computational burden so that a posterior real-time implementation is feasible. At the...