scholarly journals Uncertainty assessment in 3-D geological models of increasing complexity

Solid Earth ◽  
2017 ◽  
Vol 8 (2) ◽  
pp. 515-530 ◽  
Author(s):  
Daniel Schweizer ◽  
Philipp Blum ◽  
Christoph Butscher
Keyword(s):  
Information Entropy ◽  
Model Uncertainty ◽  
Model Space ◽  
Distance Measures ◽  
Geological Model ◽  
Multiple Model ◽  
Geological Data ◽  
Geological Models ◽  
Different Types ◽  
Model Geometry

Abstract. The quality of a 3-D geological model strongly depends on the type of integrated geological data, their interpretation and associated uncertainties. In order to improve an existing geological model and effectively plan further site investigation, it is of paramount importance to identify existing uncertainties within the model space. Information entropy, a voxel-based measure, provides a method for assessing structural uncertainties, comparing multiple model interpretations and tracking changes across consecutively built models. The aim of this study is to evaluate the effect of data integration (i.e., update of an existing model through successive addition of different types of geological data) on model uncertainty, model geometry and overall structural understanding. Several geological 3-D models of increasing complexity, incorporating different input data categories, were built for the study site Staufen (Germany). We applied the concept of information entropy in order to visualize and quantify changes in uncertainty between these models. Furthermore, we propose two measures, the Jaccard and the city-block distance, to directly compare dissimilarities between the models. The study shows that different types of geological data have disparate effects on model uncertainty and model geometry. The presented approach using both information entropy and distance measures can be a major help in the optimization of 3-D geological models.

scholarly journals Data assimilation and uncertainty assessment in 3D geological modeling

2017 ◽  
Author(s):  
Daniel Schweizer ◽  
Philipp Blum ◽  
Christoph Butscher
Keyword(s):  
Data Assimilation ◽  
Information Entropy ◽  
Model Uncertainty ◽  
Model Space ◽  
Distance Measures ◽  
Geological Model ◽  
Multiple Model ◽  
Geological Data ◽  
3D Geological Modeling ◽  
Model Geometry

Abstract. The quality of a 3D geological model strongly depends on the type of integrated geological data, their interpretation and associated uncertainties. In order to improve an existing geological model and effectively plan further site investigation, it is of paramount importance to identify existing uncertainties within the model space. Information entropy, a voxel based measure, provides a method for assessing structural uncertainties, comparing multiple model interpretations and tracking changes across consecutively built models. The aim of this study is to evaluate the effect of data assimilation on model uncertainty, model geometry and overall structural understanding. Several geological 3D models of increasing complexity, incorporating different input data categories, were built for the study site Staufen (Germany). We applied the concept of information entropy in order to visualize and quantify changes in uncertainty between these models. Furthermore, we propose two measures, the Jaccard and the City-Block distance, to directly compare dissimilarities between the models. The study shows that different types of geological data have disparate effects on model uncertainty and model geometry. The presented approach using both information entropy and distance measures can be a major help in the optimization of 3D geological models.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

Study of Scale-Down Method for Dense Grid Points

2013 ◽  
Vol 734-737 ◽  
pp. 3011-3015
Author(s):  
Sheng Yun Yu ◽  
Chang He Song ◽  
Hai Ying Xu
Keyword(s):  
Numerical Simulation ◽  
Geological Model ◽  
Three Dimension ◽  
Reservoir Heterogeneity ◽  
Geological Models ◽  
Scale Down ◽  
Dense Grid ◽  
Grid Points ◽  
Renormalization Method

The data of three-dimension geological models are very large, this kind of three -dimension geological model can not be directly used for numerical simulation and must be scaled down. The reservoir parameters, especially permeability, are scaled down by the simple renormalization method. The interbeds and parts of strong heterogeneity are filled back. The simple renormalization method is good through evaluation , not only it reduces the number of grid points, but also retains reservoir heterogeneity.

Geodiversity: Exploration of 3D geological model space

2013 ◽  
Vol 594 ◽  
pp. 27-37 ◽  
Author(s):  
M.D. Lindsay ◽  
M.W. Jessell ◽  
L. Ailleres ◽  
S. Perrouty ◽  
E. de Kemp ◽  
...  
Keyword(s):  
Model Space ◽  
Geological Model ◽  
3D Geological Model

scholarly journals Observer-Based Control of LPV Systems with Input Delay and Saturation and Matched Disturbances via a Generalized Sector Condition

2021 ◽  
Vol 2 ◽  
Author(s):  
Saeed Salavati ◽  
Karolos Grigoriadis ◽  
Matthew Franchek
Keyword(s):  
Model Uncertainty ◽  
Closed Loop ◽  
Loop System ◽  
Input Delay ◽  
Multiple Model ◽  
Closed Loop System ◽  
Sector Condition ◽  
Lpv Systems ◽  
Cubature Kalman Filter ◽  
Lpv System

This paper examines the control design for parameter-dependent input-delay linear parameter-varying (LPV) systems with saturation constraints and matched input disturbances. A gain-scheduled dynamic output feedback controller, coupled with a disturbance observer to cancel out input disturbance effects, was augmented with an anti-windup compensator to locally stabilize the input-delay LPV system under saturation, model uncertainty, and exogenous disturbances. Sufficient delay-dependent conditions to asymptotically stabilize the closed-loop system were derived using Lyapunov-Krasovskii functionals and a modified generalized sector condition to address the input saturation nonlinearity. The level of disturbance rejection was characterized via the closed-loop induced L2-norm of the closed-loop system in the form of linear matrix inequality (LMI) constraints. The results are examined in the context of the mean arterial pressure (MAP) control in the clinical resuscitation of critical hypotensive patients. The MAP variation response to the injection of vasopressor drugs was modeled as an LPV system with a varying input delay and was susceptible to model uncertainty and input/output disturbances. A Bayesian filtering method known as the cubature Kalman filter (CKF) was used to estimate the instantaneous values of the parameters. The varying delay was estimated via a multiple-model approach. The proposed input-delay LPV control was validated in closed-loop simulations to demonstrate its merits and capabilities in the presence of drug administration constraints.

scholarly journals Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time

2013 ◽  
Vol 10 (3) ◽  
pp. 2789-2833 ◽  
Author(s):  
X. He ◽  
T. O. Sonnenborg ◽  
F. Jørgensen ◽  
A.-S. Høyer ◽  
R. Roende Møller ◽  
...  
Keyword(s):  
Groundwater Modeling ◽  
Groundwater Age ◽  
Multiple Point ◽  
Hydraulic Parameters ◽  
Geological Model ◽  
Groundwater Model ◽  
Geological Uncertainty ◽  
Groundwater Head ◽  
Geological Models ◽  
The Impact

Abstract. Uncertainty of groundwater model predictions has in the past mostly been related to uncertainty in the hydraulic parameters whereas uncertainty in the geological structure has not been considered to the same extent. Recent developments in theoretical methods for quantifying geological uncertainty have made it possible to consider this factor in groundwater modeling. In this study we have applied the multiple-point geostatistical method (MPS) integrated in the Stanford Geostatistical Modeling Software (SGeMS) for exploring the impact of geological uncertainty on groundwater flow patterns for a site in Denmark. Realizations from the geostatistical model were used as input to a groundwater model developed from MODFLOW within the GMS modeling environment. The uncertainty analysis was carried out in three scenarios involving simulation of groundwater head distribution and groundwater age. The first scenario implied 100 stochastic geological models all assigning the same hydraulic parameters for the same geological units. In the second scenario the same 100 geological models were subjected to model optimization where the hydraulic parameters for each of them were estimated by calibration against observations of hydraulic head and stream discharge. In the third scenario each geological model was run with 216 randomized set of parameters. The analysis documented that the uncertainty on the conceptual geological model was as significant as the uncertainty related to the embedded hydraulic parameters.

scholarly journals IoT-IE: An Information-Entropy-Based Approach to Traffic Anomaly Detection in Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yizhen Sun ◽  
Jianjiang Yu ◽  
Jianwei Tian ◽  
Zhongwei Chen ◽  
Weiping Wang ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Information Entropy ◽  
Recognition Accuracy ◽  
False Positive Rate ◽  
Security Issues ◽  
Different Types ◽  
Positive Rate ◽  
Iot Devices ◽  
Abnormal Behaviors ◽  
Traffic Anomaly

Security issues related to the Internet of Things (IoTs) have attracted much attention in many fields in recent years. One important problem in IoT security is to recognize the type of IoT devices, according to which different strategies can be designed to enhance the security of IoT applications. However, existing IoT device recognition approaches rarely consider traffic attacks, which might change the pattern of traffic and consequently decrease the recognition accuracy of different IoT devices. In this work, we first validate by experiments that traffic attacks indeed decrease the recognition accuracy of existing IoT device recognition approaches; then, we propose an approach called IoT-IE that combines information entropy of different traffic features to detect traffic anomaly. We then enhance the robustness of IoT device recognition by detecting and ignoring the abnormal traffic detected by our approach. Experimental evaluations show that IoT-IE can effectively detect abnormal behaviors of IoT devices in the traffic under eight different types of attacks, achieving a high accuracy value of 0.977 and a low false positive rate of 0.011. It also achieves an accuracy of 0.969 in a multiclassification experiment with 7 different types of attacks.

scholarly journals Dialect borders—political regions are better predictors than economy or religion

2019 ◽  
Vol 35 (2) ◽  
pp. 276-295 ◽  
Author(s):  
Curdin Derungs ◽  
Christian Sieber ◽  
Elvira Glaser ◽  
Robert Weibel
Keyword(s):  
Quantitative Methods ◽  
Spatial Information ◽  
Distance Measures ◽  
Spatial Distance ◽  
Cultural Variation ◽  
Vast Number ◽  
Swiss German ◽  
Different Types ◽  
Dialect Variation ◽  
The Impact

AbstractThe impact of geography on language and dialect variation has been subject to a vast number of studies in linguistics, as well as the broader humanities. Most quantitative research concerning dialectology has focused on the relationship between spatial distance and change of dialects. Hypotheses regarding the impact of other geographic, cultural, and social factors have been put forth for many years but have rarely been examined with quantitative methods. In this article, we compare dialect variation in Swiss German morphosyntax with three types of social and cultural variation, namely variation in religion, administration, and economy. These different types of variation have contrasting temporal origins. Religion is, for instance, represented by the borders between Christian denominations, which are a result of the Reformation in the 16th century. In order to compare different types of spatial information in one statistical model, we introduce an approach that is robust for spatial dependencies. On one hand, our results are largely in agreement with previous studies. Spatial distance, for instance, proves to be the most important predictor of dialect variance, with distance measures that more realistically represent the potential for social contact, explaining a higher proportion of variance. On the other hand, most interestingly, we find evidence that administrative borders (i.e. political regions) more profoundly impact Swiss dialects than religion or economy. This opens the floor for the hypothesis that possibly both Swiss dialects and political regions have common origins in ancient migration movements and medieval borders between Alemannic territories.

scholarly journals Adjustment of the Exploration Grids and its use to increase the Reliability of Geological Models of Coal Deposits

2020 ◽  
Vol 174 ◽  
pp. 01063
Author(s):  
Tamara Rogova ◽  
Sergey Shaklein
Keyword(s):  
Extreme Values ◽  
Data Interpretation ◽  
New Method ◽  
Geological Data ◽  
Geodetic Networks ◽  
Specific Measurement ◽  
Geological Modelling ◽  
Coal Deposits ◽  
Geological Models ◽  
Current Procedure

The current procedure for determining the boundaries of geological domains, the allocation of which is the mandatory element of digital geological modelling, does not entirely take into account the specifics of coal deposits. Without its improvement, it is impossible to increase the reliability of geological models used in the implementation of the “Industry 4.0ˮ strategy. A new method for analysis of geological data is supposed – the adjustment of the exploration grids method. It is to determine the corrections for values of measured parameters, the use of which eliminates the uncertainty of geological data interpretation. The correction values determined by the method of conditional measurements, which used at equalization geodetic networks. Corrections are considered as an indicator of the significance of measurement and interpolation errors which occurs in the vicinity of specific measurement points. The measured values of parameters are not corrected. Geological domains are the areas with close in values corrections, whose boundaries are corrections isolines. Separate single corrections of anomalous magnitude indicate the presence of extreme values parameters.

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