Florian Wellmann

Florian Wellmann
RWTH Aachen University · Computational Geoscience and Reservoir Engineering

PhD

About

131
Publications
46,875
Reads
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1,631
Citations
Introduction
Florian Wellmann is Professor at the RWTH Aachen University in Computational Geoscience and Reservoir Engineering. Florian does research in 3D Geomodelling, Geophysics and Hydrogeology with a focus on novel modeling approaches, model optimisation, joint Bayesian inversion and Machine Learning.
Additional affiliations
July 2018 - February 2020
RWTH Aachen University
Position
  • Professor
June 2014 - present
RWTH Aachen University
Position
  • Juniorprofessor
Description
  • Junior Research Group Leader, Numerical Reservoir Engineering
December 2013 - May 2014
University of Western Australia
Position
  • PostDoc Position

Publications

Publications (131)
Article
Full-text available
Continental shelves around the globe are hosts to vast reservoirs of offshore freshened groundwater. These systems show considerable complexity, often as a function of the geological heterogeneity. Data needed to characterise these systems are often sparse, and numerical models rely on generalized simplifications of the geological environment. In o...
Preprint
Quantitative predictions of the physical state of the Earth’s subsurface are routinely based on numerical solutions of complex coupled partial differential equations together with estimates of the uncertainties in the material parameters. The resulting high-dimensional problems are computationally prohibitive even for state-of-the-art solver soluti...
Article
Full-text available
GemGIS is an open-source Python package for processing spatial data for geological modeling. GemGIS wraps and extends the functionality of packages known to the geo-community such as GeoPandas, Rasterio, OWSLib, Shapely, PyGEOS, PyVista, Pandas, NumPy, the geomodelling package GemPy and others. The aim of GemGIS, as indicated by the name, is to bec...
Code
GemGIS is a Python-based, open-source spatial data processing library. It is capable of preprocessing spatial data such as vector data raster data, data obtained from online services, and many more data formats. GemGIS wraps and extends the functionality of packages known to the geo-community such as GeoPandas, Rasterio, OWSLib, Shapely, PyVista, P...
Article
Full-text available
Safety assessments in nuclear waste management typically include the analysis of thermo-mechanical (TM)-coupled processes. The TM behavior of the host rock is, among other aspects, dependent on the prevalent geological geometry. This study aims to evaluate the impact of uncertainties in geometry on the TM rock behavior. It is one of the very first...
Article
Full-text available
Geothermal energy plays an important role in the energy transition by providing a renewable energy source with a low CO2 footprint. For this reason, this paper uses state-of-the-art simulations for geothermal applications, enabling predictions for a responsible usage of this earth’s resource. Especially in complex simulations, it is still common pr...
Article
Full-text available
Virtual reality concepts have been widely adapted to teach geoscientific content, most notably in virtual field trips-with increased developments due to recent travel restrictions and challenges of field access. On the spectrum between real and fully virtual environments are also combinations of digital and real content in mixed-reality environment...
Article
Full-text available
The societal importance of geothermal energy is significantly increasing because of its low carbon-dioxide footprint. However, geothermal exploration is also subject to high risks. For a better assessment of these risks, extensive parameter studies are required that improve the understanding of the subsurface. This yields computationally demanding...
Preprint
Geological modeling has been widely adopted to investigate underground geometries. However, modeling processes inevitably have uncertainties due to scarcity of data, measurement errors, and simplification of modeling methods. Recent developments in geomodeling methods have introduced a Bayesian framework to constrain the model uncertainties by cons...
Article
Full-text available
Geological models are commonly used to represent geological structures in 3D space. A wide range of methods exists to create these models, with much scientific work focusing recently on implicit representation methods, which perform an interpolation of a three-dimensional field where the relevant boundaries are then isosurfaces in this field. Howev...
Preprint
Full-text available
Training data is the backbone of developing either Machine Learning (ML) models or specific deep learning algorithms. The paucity of well-labeled training image data has significantly impeded the applications of ML-based approaches, especially the development of novel Deep Learning (DL) methods like Convolutional Neural Networks (CNNs) in mineral t...
Article
An important basis for a reliable groundwater management is the detailed knowledge of the aquifer. We attempt here to determine groundwater flow velocity and direction of an hard rock aquifer in a groundwater protection area (Hastenrather Graben, Germany). In a common experimental set-up, we injected low salinity water in the aquifer and monitored...
Presentation
Full-text available
Deep geothermal energy is a key to lower local and global CO2 emissions caused by the burning of fossil fuels. Different initiatives aim at establishing deep geothermal energy production at the Weisweiler coal-fired power plant near the city of Aachen, Germany, in order to replace district heat generated as a side product of coal burning. But how m...
Presentation
Full-text available
The analysis of uncertainties in the description of the subsurface is an important aspect for resource exploration and material storage. Because of the complexity of the subsurface and an often inhomogeneous data situation, models exhibit several aspects of uncertainties. These may be caused by the interpolation of locally sparse data and must be c...
Presentation
Full-text available
Open data and open-source code are influencing each other: the availability of open data sparks new developments for data analysis and processing. Open-source codes on the other hand have the potential to show the value of open data. This symbiotic effect is well visible in the successful recent developments in the field of machine learning, which...
Article
Fault zones (FZ) are major components of geothermal exploration concepts for the Southern German Upper Jurassic aquifer (UJA). Because these sections of possibly favorable hydraulic properties can be hidden in pumping test data, their explorational importance with respect to well productivity is still debated. In this work, the effect of hydraulica...
Article
Calibrating geothermal simulations is a critical step, both in scientific and industrial contexts, with suitable model parameterizations being optimized to reduce discrepancies between simulated and measured temperatures. Here we present a methodology to identify model errors in the calibration and compensate for measurement sparsity. With an appli...
Preprint
Full-text available
Continental shelves around the globe are hosts to vast reservoirs of offshore freshened groundwater. These systems show considerable complexity, often as a function of the geological heterogeneity. Data needed to characterise these systems are often sparse, and numerical models rely on generalized simplifications of the geological environment. In o...
Article
Full-text available
We used synthetic aperture radar offset tracking to reconstruct a unique record of ice surface velocities for a 3.2 year period (15 January 2017–6 April 2020), for the Palcaraju glacier located above Laguna Palcacocha, Cordillera Blanca, Peru. Correlation and spatial cluster analysis of residuals of linear fits through cumulative velocity time seri...
Preprint
Full-text available
Safety assessments in nuclear waste management typically include the analysis of thermo-mechanical (TM) coupled processes. The TM behavior of the host rock is, amongst other aspects, dependent on the prevalent geological geometry. This study aims to evaluate the impact of uncertainties in geometry on the TM rock behavior. It is one of the very firs...
Article
Full-text available
Three-dimensional structural geomodels are increasingly being used for a wide variety of scientific and societal purposes. Most advanced methods for generating these models are implicit approaches, but they suffer limitations in the types of interpolation constraints permitted, which can lead to poor modeling in structurally complex settings. A geo...
Conference Paper
Full-text available
Hydrothermal convection in porous media is an essential piece of physics in geothermal reservoirs, and understanding them leads to better development of geothermal energy. We analyze the validity of simulating hydrothermal convection using different formulations of partial differential equations. Using the Elder problem as a benchmark, we found out...
Conference Paper
Introduction to GemGIS - a Python package for spatial data processing for Geomodeling
Conference Paper
Implicit geological modeling for the Einstein Telescope (Meuse-Rhine Euroregion)
Conference Paper
Full-text available
Pragmatic and cost-effective representations of geological structures and features (e.g., heterogeneities, faults and folds) in full 3-D geological models are challenging. Implementations are highly dependent on the flexibility of the representation method. We investigate the use of parametric surface-based geological modelling methods for the purp...
Article
Full-text available
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 cons...
Article
Full-text available
We model hydrothermal convection using a partial differential equation formed by Darcy velocity and temperature—the velocity formulation. Using the Elder problem as a benchmark, we found that the velocity formulation is a valid model of hydrothermal convection. By performing simulations with Rayleigh numbers in the non-oscillatory regime, we show t...
Preprint
Full-text available
We model hydrothermal convection using a partial differential equation formed by Darcy velocity and temperature - the velocity formulation. Using the Elder problem as a benchmark, we found that the velocity formulation is a valid model of hydrothermal convection. By performing simulations with Rayleigh numbers in the non-oscillatory regime, we show...
Article
Full-text available
Interpolation of spatial data has been regarded in many different forms, varying from deterministic to stochas-tic, parametric to nonparametric, and purely data-driven to geostatistical methods. In this study, we propose a nonpara-metric interpolator, which combines information theory with probability aggregation methods in a geostatistical framewo...
Conference Paper
Full-text available
Deep geothermal energy is a key to lower local and global CO2 emissions caused by the burning of fossil fuels. Different initiatives aim at establishing deep geothermal energy production at the Weisweiler coal-fired power plant near the city of Aachen in order to replace district heat generated as a side product of coal burning1,2. But how much inf...
Conference Paper
Full-text available
Geological models, as 3-D representations of subsurface structures and property distributions, are used in many economic, scientific, and societal decision processes. These models are built on prior assumptions and imperfect information, and this aspect results in uncertainties about the predicted structures and property distributions, which will a...
Preprint
Full-text available
Structural geomodeling is a key technology for the visualization and quantification of subsurface systems. Given the limited data and the resulting necessity for geological interpretation to construct these geomodels, uncertainty is pervasive and traditionally unquantified. Probabilistic geomodeling allows for the simulation of uncertainties by aut...
Preprint
Geothermal simulations are widely used in both scientific and applied industrial contexts. Typically, the temperature state is evaluated on the basis of the heat equation, with suitable parameterizations of the model domain and defined boundary conditions, which are calibrated to obtain a minimal misfit between measured and simulated temperature va...
Article
Full-text available
One of the biggest challenges in Computational Geosciences is finding ways of efficiently simulating high-dimensional problems. In this paper, we demonstrate how the RB method can be gainfully exploited to solve problems in the Geosciences. The reduced basis method constructs low-dimensional approximations to (high-dimensional) solutions of paramet...
Preprint
Full-text available
Abstract. Interpolation of spatial data has been regarded in many different forms, varying from deterministic to stochastic, purely data-driven to geostatistical, and parametric to non-parametric methods. In this study, we propose a stochastic, geostatistical estimator which combines information theory with probability aggregation methods for minim...
Chapter
Der geologische Untergrund ist bedeutend für eine Vielzahl industrieller und technischer Anwendungen: sowohl als Lagerstätte mineralischer und nichtmineralischer Rohstoffe, als auch als Speicher, sowie als Planungsgrundlage für untertägige Infrastruktur – und in diesem Rahmen auch zunehmend im Kontext der Stadtplanung und des in den Untergrund erwe...
Article
Full-text available
Abstract Fault zones in the Upper Jurassic aquifer of the North Alpine Foreland Basin are generally regions with possibly increased hydraulic properties. They are consequently often part of the geothermal exploration concepts in this area and a primary target for the drilling operation. Data from this aquifer, gathered in pump tests, however, show...
Article
Full-text available
We present a probabilistic machine learning approach to determine lithologies for the wireline data from the Springbok Sandstone formation in the Surat Basin. Deterministic inversions of the data are compared to the new machine learning approach in order to develop a generic method for wireline log inversions. The approach is designed to combine th...
Article
Full-text available
Loop is a new open source 3D geological and geophysical modelling platform in full development. The new platform consists of 4 main work packages: • Knowledge Management: use of AI techniques for knowledge extraction from literature, maps and reports using geological ontology. Geological rules will be encoded to ensure proper knowledge extraction....
Article
Full-text available
Abstract Hydrothermal convection in porous geothermal reservoir systems can be seen as a double-edged sword. On the one hand, regions of upflow in convective systems can increase the geothermal energy potential of the reservoir; on the other hand, convection introduces uncertainty, because it can be difficult to locate these regions of upflow. Seve...
Article
Full-text available
Uncertainties are common in geological models and have a considerable impact on model interpretations and subsequent decision-making. This is of particular significance for high-risk, high-reward sectors. Recent advances allows us to view geological modeling as a statistical problem that we can address with probabilistic methods. Using stochastic s...
Preprint
Full-text available
One of the biggest challenges in Computational Geosciences is finding ways of efficiently simulating high-dimensional problems. In this paper, we demonstrate how the RB method can be gainfully exploited to solve problems in the Geosciences. The reduced basis method constructs low-dimensional approximations to (high-dimensional) solutions of paramet...
Article
Full-text available
The link between remotely sensed surface vegetation performances with the heterogeneity of subsurface physical properties is investigated by means of a Bayesian unsupervised learning approach. This question has considerable relevance and practical implications for precision agriculture as visible spatial differences in crop development and yield ar...
Article
Full-text available
Uncertainties are common in geological models and have a considerable impact on model interpretations and subsequent decision making. This is of particular significance for high-risk, high-reward sectors, such as hydrocarbon exploration and production. Recent advances allows us to view geological modeling as a statistical problem that we can addres...
Article
Full-text available
The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications, ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research and applications in geological surveys. A wide range of methods exis...
Book
Preprint available here: https://publications.rwth-aachen.de/record/754773/files/754773.pdf
Article
Full-text available
This paper presents a novel perspective to understand the spatial and statistical patterns of a cone penetration dataset and identify soil stratification using them. Both local consistency in physical space (i.e., along depth) and statistical similarity in feature space (i.e., logQt – logFr space or the Robertson chart) between data points are cons...