Porosity estimation of a geothermal carbonate reservoir in the German Molasse Basin based on seismic amplitude inversion

The Molasse Basin is one of the most promising areas for deep geothermal exploitation in Germany and the target horizon is the aquifer in the Upper Jurassic carbonates. Carbonate deposits can be very heterogeneous even over a small area due to diagenetic processes and varying depositional environments. The preferential targets for geothermal exploitation in carbonate deposits are fault zones, reef facies and karstified areas, since they are expected to act as hydraulically permeable zones due to high porosity and high permeability. Therefore, identifying these structures and characterizing, e.g., their internal porosity distribution are of high importance. This can be accomplished using 3D reflection seismic data. Besides structural information, 3D seismic surveys provide important reservoir properties, such as acoustic impedance, from which a porosity model can be derived. In our study area in Munich we carried out a seismic amplitude inversion to get an acoustic impedance model of the Upper Jurassic carbonate reservoir using a 3D seismic data set, a corresponding structural geological model, and logging data from six wells at the ‘Schäftlarnstraße’ geothermal site. The impedance model and porosity logs were than used to calculate a porosity model. The model shows a wide porosity range from 0 to 20% for the entire reservoir zone and the lithology along the wells reveals that dolomitic limestone has the highest porosities and calcareous dolomite has the lowest porosities. The study area is cut by a large W–E striking fault, the Munich Fault, and the footwall north of it shows higher porosities and more intense karstification than the hanging wall to the south. Considering the entire study area, an increase in porosity from east to west is observed. Furthermore, we identified a complex porosity distribution in reef buildups and pinnacle reefs. The reef cores have mostly low porosities of, e.g., < 3% and the highest porosities of up to 7 to 14% are observed at the reef caps and on the reef slopes. The reef slopes show a characteristic interfingering of the reef facies with the surrounding bedded facies, which indicates a syn-sedimentary reef development with slightly varying build up growth rates. We also assessed the reservoir quality with regard to porosity distribution and determined areas with moderate to good quality for geothermal exploitation by defining porosity evaluation levels. The porosity evaluation maps show that the carbonate rocks of Berriasian to Malm ζ1 are preferential targets for exploitation, especially in the footwall of the Munich Fault and to the west of the hanging wall, because these areas are characterized by high porosities due to intense karstification of bedded and massive facies, although the latter is mainly restricted to reef caps and reef slopes

Data-Driven Framework for Understanding & Modeling Ride-Sourcing Transportation Systems

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for all trips made within the city since November 1, 2018. The data comprises the trip ends (pick-up and drop-off locations), trip timestamps, trip length and duration, fare including tipping amounts, and whether the trip was authorized to be shared (pooled) with another passenger or not. Therefore, the main goal of this dissertation is to develop a comprehensive data-driven framework to understand and model the system using this data from Chicago, in a reproducible and transferable fashion. Using data fusion approach, sociodemographic, economic, parking supply, transit availability and accessibility, built environment and crime data are collected from open sources to develop this framework. The framework is predicated on three pillars of analytics: (1) explorative and descriptive analytics, (2) diagnostic analytics, and (3) predictive analytics. The dissertation research framework also provides a guide on the key spatial and behavioral explanatory variables shaping the utility of the mode, driving the demand, and governing the interdependencies between the demand’s willingness to share and surge price. Thus, the key findings can be readily challenged, verified, and utilized in different geographies. In the explorative and descriptive analytics, the ride-sourcing system’s spatial and temporal dimensions of the system are analyzed to achieve two objectives: (1) explore, reveal, and assess the significance of spatial effects, i.e., spatial dependence and heterogeneity, in the system behavior, and (2) develop a behavioral market segmentation and trend mining of the willingness to share. This is linked to the diagnostic analytics layer, as the revealed spatial effects motivates the adoption of spatial econometric models to analytically identify the ride-sourcing system determinants. Multiple linear regression (MLR) is used as a benchmark model against spatial error model (SEM), spatially lagged X (SLX) model, and geographically weighted regression (GWR) model. Two innovative modeling constructs are introduced deal with the ride-sourcing system’s spatial effects and multicollinearity: (1) Calibrated Spatially Lagged X Ridge Model (CSLXR) and Calibrated Geographically Weighted Ridge Regression (CGWRR) in the diagnostic analytics layer. The identified determinants in the diagnostic analytics layer are then fed into the predictive analytics one to develop an interpretable machine learning (ML) modeling framework. The system’s annual average weekday origin-destination (AAWD OD) flow is modeled using the following state-of-the-art ML models: (1) Multilayer Perceptron (MLP) Regression, (2) Support Vector Machines Regression (SVR), and (3) Tree-based ensemble learning methods, i.e., Random Forest Regression (RFR) and Extreme Gradient Boosting (XGBoost). The innovative modeling construct of CGWRR developed in the diagnostic analytics is then validated in a predictive context and is found to outperform the state-of-the-art ML models in terms of testing score of 0.914, in comparison to 0.906 for XGBoost, 0.84 for RFR, 0.89 for SVR, and 0.86 for MLP. The CGWRR exhibits outperformance as well in terms of the root mean squared error (RMSE) and mean average error (MAE). The findings of this dissertation partially bridge the gap between the practice and the research on ride-sourcing transportation systems understanding and integration. The empirical findings made in the descriptive and explorative analytics can be further utilized by regional agencies to fill practice and policymaking gaps on regulating ride-sourcing services using corridor or cordon toll, optimally allocating standing areas to minimize deadheading, especially during off-peak periods, and promoting the ride-share willingness in disadvantage communities. The CGWRR provides a reliable modeling and simulation tool to researchers and practitioners to integrate the ride-sourcing system in multimodal transportation modeling frameworks, simulation testbed for testing long-range impacts of policies on ride-sourcing, like improved transit supply, congestions pricing, or increased parking rates, and to plan ahead for similar futuristic transportation modes, like the shared autonomous vehicles

Rotary Wing Aerodynamics

This book contains state-of-the-art experimental and numerical studies showing the most recent advancements in the field of rotary wing aerodynamics and aeroelasticity, with particular application to the rotorcraft and wind energy research fields

Back to the Roots : Revisiting the Use of the Fiber-Rich Cichorium intybus L. Taproots

Fibers are increasingly recognized as an indispensable part of our diet and vital for maintaining health. Notably, complex mixtures of fibers have been found to improve metabolic health. Following an analysis of the fiber content of plant-based products, we found the taproot of the chicory plant (Cichorium intybus L) to be 1 of the vegetables with the highest fiber content, comprising nearly 90% of its dry weight. Chicory roots consist of a mixture of inulin, pectin, and (hemi-)cellulose and also contain complex phytochemicals, such as sesquiterpene lactones that have been characterized in detail. Nowaday, chicory roots are mainly applied as a source for the extraction of inulin, which is used as prebiotic fiber and food ingredient. Chicory roots, however, have long been consumed as a vegetable by humans. The whole root has been used for thousands of years for nutritional, medicinal, and other purposes, and it is still used in traditional dishes in various parts of the world. Here, we summarize the composition of chicory roots to explain their historic success in the human diet. We revisit the intake of chicory roots by humans and describe the different types of use along with their various methods of preparation. Hereby, we focus on the whole root in its complex, natural form, as well as in relation to its constituents, and discuss aspects regarding legal regulation and the safety of chicory root extracts for human consumption. Finally, we provide an overview of the current and future applications of chicory roots and their contribution to a fiber-rich diet.Peer reviewe

Advanced seismic characterization of a geothermal carbonate reservoir – insight into the structure and diagenesis of a reservoir in the German Molasse Basin

The quality of geothermal carbonate reservoirs is controlled by, for instance, depositional environment, lithology, diagenesis, karstification, fracture networks, and tectonic deformation. Carbonatic rock formations are thus often extremely heterogeneous, and reservoir parameters and their spatial distribution difficult to predict. Using a 3D seismic dataset combined with well data from Munich, Germany, we demonstrate how a comprehensive seismic attribute analysis can significantly improve the understanding of a complex carbonate reservoir. We deliver an improved reservoir model concept and identify possible exploitation targets within the Upper Jurassic carbonates. We use seismic attributes and different carbonate lithologies from well logs to identify parameter correlations. From this, we obtain a supervised neural-network-based 3D lithology model of the geothermal reservoir. Furthermore, we compare fracture orientations measured in seismic (ant-tracking analysis) and well scale (image log analysis) to address scalability. Our results show that, for example, acoustic impedance is suitable to identify reefs and karst-related dolines, and sweetness proves useful to analyse the internal reef architecture, whereas frequency- and phase-related attributes allow the detection of karst. In addition, reef edges, dolines, and fractures, associated with high permeabilities, are characterized by strong phase changes. Fractures are also identified using variance and ant tracking. Morphological characteristics, like dolines, are captured using the shape index. Regarding the diagenetic evolution of the reservoir and the corresponding lithology distribution, we show that the Upper Jurassic carbonate reservoir experienced a complex evolution, consisting of at least three dolomitization phases, two karstification phases, and a phase of tectonic deformation. We observe spatial trends in the degree of dolomitization and show that it is mainly facies-controlled and that karstification is facies- and fault-controlled. Karstification improves porosity and permeability, whereas dolomitization can either increase or decrease porosity. Therefore, reservoir zones should be exploited that experienced only weak diagenetic alteration, i.e. the dolomitic limestone in the upper part of the Upper Jurassic carbonates. Regarding the fracture scalability across seismic and well scales, we note that a general scalability is, due to a combination of methodological limitations and geological reasons, not possible. Nevertheless, both methods provide an improved understanding of the fracture system and possible fluid pathways. By integrating all the results, we are able to improve and adapt recent reservoir concepts, to outline the different phases of the reservoir's structural and diagenetic evolution, and to identify high-quality reservoir zones in the Munich area. These are located southeast at the Ottobrunn Fault and north of the Munich Fault close to the Nymphenburg Fault.</p

Taking our Public Services Back in House: A Remunicipalisation Guide for Workers and Trade Unions

This report was commissioned by Public Services International (PSI) to provide guidance to workers, trade unions and allied civil society groups interested in taking back public services into public ownership and control. In particular, this guide provides an overview of the relevant stages of remunicipalisation - the return of privatised public services into public ownership on a local and regional level – and distils lessons learnt from 50 case studies of remunicipalisation (and municipalisation) from the standpoint of trade unions

Navigating agency problems in corporate law: A Comparative study through the lens of law and economics

This interdisciplinary research explores agency problems within corporate law, through the lens of comparative law and law and economics. By expanding these distinctive yet complementary perspectives, this complex entity can be more easily understood. Here the approach departs from traditional company law strategies and instead unites an economic evaluation of legal norms with a comparative examination of various jurisdictions, thus offering a novel view on how to better solve agency problems. To discern and combine effective legal strategies from diverse jurisdictions, this research also capitalises on comparative law methodology. Based on the strengths of different legal cultures it creates a framework, grounded in law and economics - tertium comparationis -, that can be used to assess and address the second and third agency problems. After analysing the second agency problem, this research proposes the integration of shareholder costs within transaction cost theory. It recommends enhancing cost-efficiency in corporate governance, facilitated by bolstering fiduciary duties, promoting transparency, and endorsing proactive dispute resolution. A proposal emerging from this research introduces a mechanism for prosocial investors to voice their interests in the company, safeguard economic rights and empower minority shareholders. In addition to the second agency problem, the third agency problem is explored, redefining a company’s purpose to mirror public interest and balance socio-economic prosperity with environmental sustainability. The research introduces stakeholder costs in transaction cost theory, underlining the long-term value increase of incorporating stakeholder rights as monitoring costs. Here, emphasis is placed on the importance of aligning businesses with the provisional nine planetary boundaries and establishing a robust social foundation, as inspired by the Doughnut Economics model. The research suggests regulatory mechanisms to categorise businesses based on their environmental impact and advocates for all companies, irrespective of their size or sector, to adhere to high sustainability standards. In conclusion, the research combines comparative law methodology with law and economics, and proposes legal strategies that address agency problems, promote efficiency, and advocate for environmental sustainability. It exemplifies the potential of this combined approach to reshaping the corporate landscape to better reflect public interest while upholding the principles of the Doughnut Economics model

A semi-automated BPMN-based framework for detecting conflicts between security, data-minimization, and fairness requirements

Requirements are inherently prone to conflicts. Security, data-minimization, and fairness requirements are no exception. Importantly, undetected conflicts between such requirements can lead to severe effects, including privacy infringement and legal sanctions. Detecting conflicts between security, data-minimization, and fairness requirements is a challenging task, as such conflicts are context-specific and their detection requires a thorough understanding of the underlying business processes. For example, a process may require anonymous execution of a task that writes data into a secure data storage, where the identity of the writer is needed for the purpose of accountability. Moreover, conflicts not arise from trade-offs between requirements elicited from the stakeholders, but also from misinterpretation of elicited requirements while implementing them in business processes, leading to a non-alignment between the data subjects’ requirements and their specifications. Both types of conflicts are substantial challenges for conflict detection. To address these challenges, we propose a BPMN-based framework that supports: (i) the design of business processes considering security, data-minimization and fairness requirements, (ii) the encoding of such requirements as reusable, domain-specific patterns, (iii) the checking of alignment between the encoded requirements and annotated BPMN models based on these patterns, and (iv) the detection of conflicts between the specified requirements in the BPMN models based on a catalog of domain-independent anti-patterns. The security requirements were reused from SecBPMN2, a security-oriented BPMN 2.0 extension, while the fairness and data-minimization parts are new. For formulating our patterns and anti-patterns, we extended a graphical query language called SecBPMN2-Q. We report on the feasibility and the usability of our approach based on a case study featuring a healthcare management system, and an experimental user study. \ua9 2020, The Author(s)

Gas, Water and Solid Waste Treatment Technology

This book introduces a variety of treatment technologies, such as physical, chemical, and biological methods for the treatment of gas emissions, wastewater, and solid waste. It provides a useful source of information for engineers and specialists, as well as for undergraduate and postgraduate students, in the areas of environmental science and engineering