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GeoTief Explore (3D)

Text only available in German

Integrative Maßnahmen zur systematischen Erforschung und Nutzbarmachung der Tiefen Geothermie im Wiener Becken

Das Projekt GeoTief Wien vermisst die Geologie im östlichen Raum Wiens, um das Potenzial tiefliegender Heißwasservorkommen zu erforschen. Nach 2D-Seismik-Messungen im Frühjahr 2017 werden darauf aufbauend ab Herbst 2018 weitere Messungen mittels 3D-Seismik durchgeführt, um ein dreidimensionales Bild der Wiener Geologie zu erhalten.

Ausgangssituation

Verschiedene Studien (z.B. GeoEnergie 2050) prognostizieren eine realistische Anwendungskapazität der Tiefen Geothermie in Österreich zwischen 450 MWth bis 700 MWth. Dem Großraum Wien wird einen Anteil von 40 % bis 60 % dieser Kapazitätswerte zugeschrieben. Zugleich weist der Ballungsraum Wien eines der größten Fernwärmenetze Europas auf, weshalb der angestrebten Nutzung der hydrothermalen Geothermie in der Wärme-Versorgungsstrategie Wiens eine tragende Rolle zugeordnet wird (siehe Klimaschutzprogramm der Stadt Wien und Stadtentwicklungsplan Wien, STEP 2025). Die zukünftige Nutzbarmachung dieser Wärmequelle hängt jedoch von nachhaltigen und belastbaren Explorations- und Umsetzungskonzepten ab, die heute noch nicht in dieser Form existieren.
Genau an diesem Punkt wird „GeoTief EXPLORE (3D)“ ansetzen und durch die erarbeiteten Forschungsinhalte am Beispiel des Großraum Wiens einen signifikanten Ausbau der Geothermie im Wiener Becken und in weiterer Folge für weitere Potenzialgebiete in Österreich ermöglichen.
Das Projekt setzt sich in einem ersten Schritt zum Ziel, durch die Sammlung, Bewertung und Aufbereitung geophysikalischer und seismischer Daten, das Wissen über die geothermalen Reservoire im Raum Wien signifikant zu erweitern. Hierbei werden Untergrundparameter mit Hilfe geophysikalischer Methoden generiert und zusammen mit geologischen- und lagerstättentechnischen Daten in einem gemeinsamen 3D Datenkubus zusammengefasst und visualisiert.
Die erarbeiteten Daten werden zudem hinsichtlich geologischer Parameter, vorhandener Ressourcen und möglicher Risiken (technische, wirtschaftliche und geologische) analysiert und entsprechende Beurteilungsmodelle als zentrales Projektergebnis entwickelt. Damit einher geht auch eine detaillierte Analyse zu möglichen Herausforderungen einer Integration der Tiefen Geothermie in das bestehende Wiener Fernwärmenetz. Ein wichtiger Aspekt in diesem Zusammenhang ist, dass die oben genannten Untersuchungen für das gesamte Potenzialgebiet erfolgen. Somit kann letztlich unter Berücksichtigung technischer, ökonomischer und rechtlicher Rahmenbedingungen ein bestmögliches Erschließungskonzept für die gesamte Region erarbeitet werden.

Die erarbeiteten Planungs- und Bewertungswerkzeuge liefern, vor allem durch die direkte Einbeziehung nationaler Experten und Institutionen (u.a. laufende Workshops mit der Kohlenwasserstoff-Industrie) folgende Erkenntnisse:
Ergebnisse

Ein präzises geologisches 3D-Modell des Wiener Untergrunds, das Informationen über die Lage und Größe von potentiellen wasserführenden Gesteinsschichten liefert und klärt, ob und in welchem Ausmaß die Wärme aus der Tiefe der Erde in Zukunft für Wien genutzt werden kann.

GeoTief EXPLORE (3D) (energieforschung.at)

GeoTief BASE (2D)

New research approaches for expanding the knowledge base on the exploration of geothermal energy in the deep underground of Vienna

Geothermal energy is a local, renewable and environmental friendly energy source, available 365 days a year, 24 hours per day, as baseload for district heating systems. The benefits of the usage of hydrothermal energy are being recognized in strategy concepts of the Vienna city government as well as in the rest of the country (GeoEnergie 2050, Energieautarkie 2050).

The level of knowledge about the potential reservoir rocks within the basement of the central and north-eastern Vienna Basin is insufficient, because of the fact that previous exploration activities in this region were restricted to the hydrocarbon industry focusing on other target depths.

Within this study, new attempts to explore hydrothermal reservoirs are being carried out by conducting innovative shear-wave and wide-angle seismic surveys. This method of geothermal exploration has not been tested yet for the deep target depths and neither in densely populated areas. If the results of the special seismic surveys are satisfying, this method shall be the base for upcoming exploration strategies in the Vienna Basin. The geological interpretation of the resulting seismic profiles will be combined in a next step with processed data from the hydrocarbon industry in order to review geological models respectively develop new concepts.

One of the challenges within this project is handling the large amount of gathered inventory data from different sources and newly acquired data. Thus, the 3D geodatamanagement will accompany the collection and processing of this data over the whole period of the project. In an innovative approach, this accumulated dataset shall be made available to project partners in real-time. After the end of the project this tested concept for building up a 3D geodatamanagement shall be made available to experts.

In summary, the project aims to expand the state of knowledge and methods of geothermal exploration in such a way that successful advanced exploration research can be continued in the Vienna Basin – with the ultimate goal to exploit the existing energy potential through a large number of geothermal plants within the Vienna Basin.

GeoSegment3D

Unsupervised Machine Learning Algorithms - Test Environment for Geophysical Interpretation

There are mainly two approaches of seismic interpretation of 3D seismic data. One approach is the manual interpretation of seismic data by interpreting inline, crossline and time slices. The second approach is seismic interpretation by using machine learning algorithms. In our study we focus on the second approach, where we are dealing with a certain machine learning algorithm family. Our algorithm selection are clustering algorithms. These are used to cluster seismic attributes. The aim is, to extract seismic volumes of a geological structure. To solve that a testing environment is created, which consists of a variety of synthetic seismic models. These models are built from 6 different geological models. These models are a meandering river system, a breaded river system, a fan system, a carst system, a salt dome, and a reef system. On these synthetic seismic models, different seismic attributes are calculated. For selecting the best performed seismic attributes sets, a literature database is used to find out the right attributes for the right geological condition.

After selection of seismic attribute sets the clustering algorithms are selected. Therefore 4 groups of clustering algorithms are used: The first group is the Partitional Clustering Group, the second the Hierarchical Clustering Group, the third the Density-Based Clustering Group and the forth the Probabilistic Clustering Group. Each group consists of a variety of different algorithms.

The different algorithms methods can be tested on synthetic seismic data and the best performed algorithm for a distinct purpose can be selected. Hereby in particular the amount of cluster centers and the cluster shapes of the data are important. These algorithms are used to find domains of seismic facies. These domains can be both edges or bodies of seismic facies depending on what is desired.

As a result, a matrix of best performed algorithms together with the best performed seismic attribute sets is created to add advise to use mashine learning algorithm like clustering algorithm on real seismic data. Finally, a clustered seismic volume can be extracted, were geology is, because of the synthetic seismic model known.

Finally, it can be concluded that the tests on synthetic seismic data are promising and a first step to select powerful machine learning algorithm for seismic interpretation. But of course, it is still a lot of work to do, especially for real seismic data, to do a correct verification of the cluster results.

KrisT

Determination of fracture parameters using directional seismic texture attributes to minimize the discovery risk

Optimal planning of geothermal wells is a prerequisite for the cost-effective extraction and use of heat and electricity from geothermal reservoirs. For an economical operation of geothermal projects, the depth (temperature) and the composition of the geothermal reservoir (porosity and permeability) are of immense importance. With the help of seismic surveys (2D and 3D) it is possible to map the general geological structure of the subsurface and especially of the geothermal reservoir. For many geothermal projects, the identification of fracture networks is crucial for the description of water conductivity (permeability). With the help of seismic attributes such as coherence, curvature or ant track calculations, areas of increased fracturing can be detected and thus fracture intensity distributions can be created. However, this does not provide direct information about the strike and dip of fractures. In the FFG project RiSeiTex (FFG project number 848799) the applicability of directional texture attributes based on the Grey Level Co-Occurrence Matrix (GLCM) for the determination of fracture parameters was verified.

This research project has three main objectives. The first goal is to increase the resolution by extending the possible spatial directions to 109 and 193 respectively. The second goal of this project is the cascading use of seismic attributes. The third point of this project is the software optimization of the algorithm to reduce the computing time. The results of the individual optimization steps were tested on publicly available seismic data and compared with each other. This allowed an improved visualization of areas with increased seismic variability, which in turn can correlate with the presence of fractures.

KrisT (energieforschung.at, German)

RiSeiTex

Directional seismic texture attributes to classify fractures to minimize the discovery risk

This research project focused on two project goals. The first goal is the test for the principal applicability of directional texture attributes for the interpretation of fracture intensities, as well as Striking and falling of fissures. For this purpose different GLCM based attributes were calculated in 13 possible spatial directions were calculated. By comparing the different directional GLCM attributes, it is possible to identification of preferred fracture strike and fracture fall is possible. The second goal of this research project is the adaptation of the existing algorithm to perform the computation of texture attributes in more than than 13 spatial directions. This can be achieved by extending the distance between the seismic data (sample points) to be considered. With a distance of 2 in x-, y- and z-direction the calculation can be done in 49 directions.