Ensemble data assimilation methods for estimating fault slip and future earthquake occurrences

In this dissertation, I explore ensemble data assimilation methods to enhance our capability to forecast earthquakes and slow slip events, focusing on the critical challenge posed by limited information on the current stress state of faults. <br/>At the outset, the research acknowledges the inherent limitations in our current understanding of...

Options for the Implementations of Data Assimilation for Geotechnics

Data assimilation methods have been implemented on a slope stability problem, and the performance of different constitutive models and data assimilation schemes has been investigated. In the first part, a data assimilation scheme called the ensemble Kalman filter (EnKF) is implemented using a finite element model (FEM) and its performance with...

Estimating the occurrence of slow slip events and earthquakes with an ensemble Kalman filter

Our ability to forecast earthquakes and slow slip events is hampered by limited information on the current state of stress on faults. Ensemble data assimilation methods permit estimating the state by combining physics-based models and observations, while considering their uncertainties. We use an ensemble Kalman filter (EnKF) to estimate...

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...

An efficient ensemble Kalman Filter implementation via shrinkage covariance matrix estimation: exploiting prior knowledge

In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter via shrinkage covariance matrix estimation. Our filter implementation combines information brought by an ensemble of model realizations, and that based on our prior knowledge about the dynamical system of interest. We perform the combination of...

Continuous-discrete smoothing of diffusions

Suppose X is a multivariate diffusion process that is observed discretely in time. At each observation time, a transformation of the state of the process is observed with noise. The smoothing problem consists of recovering the path of the process, consistent with the observations. We derive a novel Markov Chain Monte Carlo algorithm to sample...

Data assimilation: Application of a particle filter on bathymetry simulations by the morphological model Delft3D

Predictions of the morphology of coastal areas are used to make decisions on coastal defence and nature conservation. To predict this morphology, simulations made by morphological models are used. To base decisions on this morphology predictions, we want the uncertainties in these predictions to be small. The goal of this research is to get a...

Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter

This thesis explores the usage of the particle filter as a data assimilation technique to estimate subsurface processes, such as reservoir volume change from space-geodetic PS-InSAR surface measurements. The specific research area is Groningen, where subsidence is induced by hydrocarbon and salt production.<br/>The satellite radar PS-InSAR...

Sequential reduction of slope stability uncertainty based on temporal hydraulic measurements via the ensemble Kalman filter

A data assimilation framework, utilising measurements of pore water pressure to sequentially improve the estimation of soil hydraulic parameters and, in turn, the prediction of slope stability, is proposed. Its effectiveness is demonstrated for an idealised numerical example involving the spatial variability of saturated hydraulic...

A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from...

A Study of the Influence of Measurement Volume, Blending Ratios and Sensor Precision on Real-Time Reconciliation of Grade Control Models

The mining industry continuously struggles to keep produced tonnages and grades aligned with targets derived from model-based expectations. Deviations often result from the inability to characterise short-term production units accurately based on sparsely distributed exploration data. During operation, the characterisation of short-term...

A particle filter-based data assimilation framework for discrete event simulations

With the advent of new sensor technologies and communication solutions, the availability of data for discrete event systems has greatly increased. This motivates research on data assimilation for discrete event simulations that has not yet fully matured. This paper presents a particle filter-based data assimilation framework for discrete event...

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....

Reduction of uncertainty in stability calculations for slopes under seepage

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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....