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Position: PhD in Fractured Geothermal Reservoirs
Institution: Delft University of Technology
Location: Delft, South Holland, Netherlands
Duties: Fully-funded PhD position available at TU Delft's new Energi Simulation Centre for Geoenergy, focusing on deciperhing the key controls on fluid flow in geothermal reservoirs using machine learning
Requirements: A good MSc degree or equivalent in geoscience or reservoir engineering; Strong numerate and programming skills; Sound and quantitative understanding of fluid flow in geologically complex reservoirs; Excellent interpersonal and communication skills
   
Text: Activeer hoog contrast Ga naar hoofdcontent Home van TU Delft Werken bij TU Delft Vacatures Wetenschapper PhD Tenure track Postdoc Professional Zoeken Werken bij TU Delft Vacatures Menu sluiten Wetenschapper PhD Tenure track Postdoc Professional Dit is het social media blok facebook twitter instagram youtube linkedin whatsapp whatsapp English Sluit menu Zoeken Sluit zoek Werken bij TU Delft Vacatures Job details PhD in Fractured Geothermal Reservoirs Apply Now Teaser Fully-funded PhD position available at TU Delft's new Energi Simulation Centre for Geoenergy, focusing on deciperhing the key controls on fluid flow in geothermal reservoirs using machine learning. Job description In the global north, over 40% of the total energy consumption is used for heating and cooling of buildings. Geothermal energy has the potential to significantly decarbonise energy supplies not only for heating and cooling but also for electricity generation, and therefore make a major contribution to the transition to a sustainable and just low-carbon energy future. Naturally occurring fractures often provide the primary permeability for fluid flow and heat transport in many geothermal reservoirs. However, predicting heat flow through fracture networks to assess the viability of a potential geothermal development is challenging due to the inherent uncertainties in the fracture network and its properties. To date, no systematic studies have aimed to establish the properties that fundamentally control the characteristics of heat flow in naturally fractured geothermal reservoirs. For example, it is unclear how the combination of hydraulic connectivity within the fracture network and the size of the less permeable matrix blocks impact heat flow, i.e., under which conditions heat flow in a fractured geothermal reservoir can be characterised by effective properties that approximate a single porosity system and when heat flow needs to be characterised by more complex approaches. New data from outcrop analogues for fractured reservoirs (e.g., imagery from drones or lidar for geometric attribute identification), state-of-the-art numerical simulations that resolve fractures properly in reservoir models, and machine learning techniques now enable us to characterise the type of flow behaviours that can occur in fractured geothermal reservoirs and establish the links between fracture network properties and associated flow behaviours. The hypothesis central to this PhD thesis is therefore that there is only a small number of heat flow behaviours in fractured geothermal reservoirs that can be correlated to a reasonably well constrained set of fracture network properties. More specifically, the PhD thesis aims to answer the following questions: How many endmembers/types of fracture network geometries and associated unique flow behaviours exist in geologically plausible fracture networks? What are the key fracture network characteristics that control these heat flow behaviours And are they consistent across different lithologies (e.g., carbonates, sandstone, basement rocks)? Can we estimate these key fracture network geometries and properties, and their uncertainty bounds, from the available static and dynamic reservoir data? How do we best design geothermal reservoir models that preserve the key fracture network properties and associated uncertainties? Do these new reservoir models lead to more reliable production forecasts for fractured geothermal reservoirs? This PhD project is fully funded by Energi Simulation. The you will join a vibrant and internationally renowned department working across a wide range of geoenergy challenges, and become part of the department’s newly established Energi Simulation Centre for Geoenergy, benefitting from its extensive national and international research network. In this role you will receive extensive training in geothermal reservoir engineering, fluid flow in fractured geological formations, fracture network characterisation and modelling, machine learning, geothermal reservoir simulation, and how to present the research results at conferences and in peer-reviewed results. These skills will equip you with a unique set of skills to work on range of geoenergy challenges in major energy companies, consultancies, or in academic or national research centres. Requirements The candidate we are looking for has: A good MSc degree or equivalent in geoscience or reservoir engineering Strong numerate and programming skills Sound and quantitative understanding of fluid flow in geologically complex reservoirs Excellent interpersonal and communication skills It is a plus if you have: Experience in (fractured) reservoir modelling Experience in machine learning Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements . Conditions of employment Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. TU Delft (Delft University of Technology) Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. In particular, we recognise that not every candidate will have had the same opportunities to advance their careers. We therefore pledge to fully account for any particular circumstances that the applicants may wish to disclose (e.g. parental leave, caring duties, part-time jobs to support studies, disabilities etc.). Challenge. Change. Impact! Faculty Civil Engineering & Geosciences The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty of Civil Engineering & Geosciences. To discover more about Research, Education, our Lab facilities and your possible future colleagues at the Department of Geoscience and Engineering, check out our website: www.tudelft.nl/en/ceg/about-faculty/departments/geoscience-engineering Additional information For more information about this vacancy and application procedure, please contact Sebastian Geiger at s.geiger@tudelft.nl. Application procedure Are you interested in this vacancy? Please apply before 23:59 CEST on 30 September 2022 via the application button. Please include in your application: A short motivation letter covering your research interest and relevant experience; Your CV including a list of publications if applicable and contact details for two references unless reference letters are attached; Copies of academic qualifications. We expect to hold the job interviews in October 2022. Furthermore please note: You can apply online. We will not process applications sent by email and/or post. A pre-Employment screening can be part of the selection procedure. Acquisition in response to this vacancy is not appreciated. Faculty/Department Faculty of Civil Engineering and Geosciences Job Type PhD Scientific field Natural sciences Hours per week 38 Salary € 2.541,00 - € 3.247,00 Desired level of education University graduate Vacancy number TUD02652 Method of applying Via system Teaser Fully-funded PhD position available at TU Delft's new Energi Simulation Centre for Geoenergy, focusing on deciperhing the key controls on fluid flow in geothermal reservoirs using machine learning. Job description In the global north, over 40% of the total energy consumption is used for heating and cooling of buildings. Geothermal energy has the potential to significantly decarbonise energy supplies not only for heating and cooling but also for electricity generation, and therefore make a major contribution to the transition to a sustainable and just low-carbon energy future. Naturally occurring fractures often provide the primary permeability for fluid flow and heat transport in many geothermal reservoirs. However, predicting heat flow through fracture networks to assess the viability of a potential geothermal development is challenging due to the inherent uncertainties in the fracture network and its properties. To date, no systematic studies have aimed to establish the properties that fundamentally control the characteristics of heat flow in naturally fractured geothermal reservoirs. For example, it is unclear how the combination of hydraulic connectivity within the fracture network and the size of the less permeable matrix blocks impact heat flow, i.e., under which conditions heat flow in a fractured geothermal reservoir can be characterised by effective properties that approximate a single porosity system and when heat flow needs to be characterised by more complex approaches. New data from outcrop analogues for fractured reservoirs (e.g., imagery from drones or lidar for geometric attribute identification), state-of-the-art numerical simulations that resolve fractures properly in reservoir models, and machine learning techniques now enable us to characterise the type of flow behaviours that can occur in fractured geothermal reservoirs and establish the links between fracture network properties and associated flow behaviours. The hypothesis central to this PhD thesis is therefore that there is only a small number of heat flow behaviours in fractured geothermal reservoirs that can be correlated to a reasonably well constrained set of fracture network properties. More specifically, the PhD thesis aims to answer the following questions: How many endmembers/types of fracture network geometries and associated unique flow behaviours exist in geologically plausible fracture networks? What are the key fracture network characteristics that control these heat flow behaviours And are they consistent across different lithologies (e.g., carbonates, sandstone, basement rocks)? Can we estimate these key fracture network geometries and properties, and their uncertainty bounds, from the available static and dynamic reservoir data? How do we best design geothermal reservoir models that preserve the key fracture network properties and associated uncertainties? Do these new reservoir models lead to more reliable production forecasts for fractured geothermal reservoirs? This PhD project is fully funded by Energi Simulation. The you will join a vibrant and internationally renowned department working across a wide range of geoenergy challenges, and become part of the department’s newly established Energi Simulation Centre for Geoenergy, benefitting from its extensive national and international research network. In this role you will receive extensive training in geothermal reservoir engineering, fluid flow in fractured geological formations, fracture network characterisation and modelling, machine learning, geothermal reservoir simulation, and how to present the research results at conferences and in peer-reviewed results. These skills will equip you with a unique set of skills to work on range of geoenergy challenges in major energy companies, consultancies, or in academic or national research centres. Requirements The candidate we are looking for has: A good MSc degree or equivalent in geoscience or reservoir engineering Strong numerate and programming skills Sound and quantitative understanding of fluid flow in geologically complex reservoirs Excellent interpersonal and communication skills It is a plus if you have: Experience in (fractured) reservoir modelling Experience in machine learning Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements . Conditions of employment Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2541 per month in the first year to € 3247 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation. TU Delft (Delft University of Technology) Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration. In particular, we recognise that not every candidate will have had the same opportunities to advance their careers. We therefore pledge to fully account for any particular circumstances that the applicants may wish to disclose (e.g. parental leave, caring duties, part-time jobs to support studies, disabilities etc.). Challenge. Change. Impact! Faculty Civil Engineering & Geosciences The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management. Click here to go to the website of the Faculty of Civil Engineering & Geosciences. To discover more about Research, Education, our Lab facilities and your possible future colleagues at the Department of Geoscience and Engineering, check out our website: www.tudelft.nl/en/ceg/about-faculty/departments/geoscience-engineering Additional information For more information about this vacancy and application procedure, please contact Sebastian Geiger at s.geiger@tudelft.nl. Application procedure Are you interested in this vacancy? Please apply before 23:59 CEST on 30 September 2022 via the application button. Please include in your application: A short motivation letter covering your research interest and relevant experience; Your CV including a list of publications if applicable and contact details for two references unless reference letters are attached; Copies of academic qualifications. We expect to hold the job interviews in October 2022. Furthermore please note: You can apply online. We will not process applications sent by email and/or post. A pre-Employment screening can be part of the selection procedure. Acquisition in response to this vacancy is not appreciated. Back to list Send job to a friend Print this page Apply Now Five reasons to work at the TU Delft 1. Impact: for a better society at a top international university 2. Open international community with multidisciplinairy teamwork 3. Excellent facilities for research, education and innovation 4. Room for personal growth 5. Good employment conditions Read more! Read more! Technische Universiteit Delft Dit is het social media blok Postbus 5 2600 AA Delft Tel: 31 (0)15 27 89111 Activeer hoog contrast Zoeken /* */ AddThis Sharing Sidebar Hide Show Close
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