You don't have yet the qualifications to start a PhD ? Our MSc may interest you ! 

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Post Doc opportunities

We welcome Post Doc researchers who are interested in working on RING's research topics and we support funding applications to Marie Skłodowska-Curie Actions, Fond National Suisse, and others. Find out more about RING's technologies and publications.
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PhD opportunities

PhD applications for 2024 are now open

How to apply

Application files must be sent to This email address is being protected from spambots. You need JavaScript enabled to view it. and must include:

• A cover letter, 
• A CV, including contact information for two or more referees
• A research outcome (Master’s thesis or paper) written by the candidate
• An official transcript of grades.
  
  

Project #1: Seismic wave propagation in multi-scale fractured media

 Starting date: September 2024 or later                             Deadline for applications: May 31, 2024 

Topic description

Tectonic processes and the industrial exploitation of the subsurface induce brittle deformations in the earth crust, leading to fractures at all scales. These fractures are organized in networks which are basically characterized by their density, connectivity, and distribution of aperture, length and orientation. Determining these parameters are essential for predicting the hydrogeological behavior of reservoirs or understanding the fatigue of soils and engineering structures. However, direct measurements of fracture parameters are rarely available. Apart from outcrops, cores and borehole images, fractured rocks are seen in an effective way through mechanical properties derived from mechanical tests or seismic wave data. The aim of the PhD project is to improve our understanding of the interaction between seismic waves and fractures.

Geological observations have evidenced that a power law is appropriate to describe the density of a fracture set as a function of fracture size (e.g., Bonnet et al., 2001). Nevertheless, for either theoretical or computational reasons, studies on seismic wave propagation in fractured media have been restricted to a short range of sizes so far. To overcome this limitation, the present project will build on recent progresses in non-periodic homogenization (e.g., Capdeville et al, 2010; Guillot et al, 2010; Cupillard & Capdeville, 2018; Capdeville et al, 2020) to compute effective properties of fractures following realistic power law distributions. The numerical methodology will be tested and validated against laboratory experiments on core samples.

References

Bonnet, E., O. Bour, N. E. Odling, P. Davy, I. Main, P. Cowie, and B. Berkowitz (2001). Scaling of fracture systems in geologic media, Rev. Geophys. 39, 347–383.

Capdeville, Y., L. Guillot, and J. Marigo (2010). 2-D non-periodic homogenization to upscale elastic media for P-SV waves. Geophys. J. Int. 182, 903–922.

Capdeville, Y., P. Cupillard, and S. Singh (2020). An introduction to the two-scale homogenization method for seismology, Adv. Geophys. 61, 217–306.

Cupillard, P. and Y. Capdeville (2018). Non-periodic homogenization of 3-D elastic media for the seismic wave equation. Geophys. J. Int. 213(2), 983–1001.

Guillot, L., Y. Capdeville, and J. Marigo (2010). 2-D non-periodic homogenization of the elastic wave equation: SH case. Geophys. J. Int. 182, 1438–1454.

Working environment: The successful candidate will work in the RING Team, a pluridisciplinary and diverse
group of 12-15 researchers and graduate students working at the interface of geoscience, computer science
and applied mathematics. The team is part of Ecole Nationale Supérieure de Géologie in the GeoRessources
laboratory, a research lab of Université de Lorraine and CNRS. The research team is driven by passion for
developing computer-based methods and theories for geological and geophysical modeling, serving the
geoscience community to address scientific and natural resource management challenges.

Working environment

The successful candidate will work in the RING Team, a pluridisciplinary and diverse group of 12-15 researchers and graduate students working at the interface of geoscience, computer science and applied mathematics. The team is part of Ecole Nationale Supérieure de Géologie in the GeoRessources laboratory, a research lab of Université de Lorraine and CNRS. The research team is driven by passion for developing computer based methods and theories for geological and geophysical modeling, serving the geoscience community to address scientific and natural resource management challenges.
Laboratory: GeoRessources (Nancy, France)
Location: Nancy (France), a UNESCO World Heritage city with a vibrant student life and a rich cultural agenda, only 90 minutes away from Paris, Luxembourg and Strasbourg.

Working environment: The successful candidate will work in the RING Team, a pluridisciplinary and diverse
group of 12-15 researchers and graduate students working at the interface of geoscience, computer science
and applied mathematics. The team is part of Ecole Nationale Supérieure de Géologie in the GeoRessources
laboratory, a research lab of Université de Lorraine and CNRS. The research team is driven by passion for
developing computer-based methods and theories for geological and geophysical modeling, serving the
geoscience community to address scientific and natural resource management challenges.

Requirements 

Candidates should hold a MSc in quantitative Earth Sciences, Geophysics or Physics, Computer Science, Geostatistics, Porous Media, Applied Mathematics, or related fields. They are passionate about science and have solid scientific writing skills. An experience in computer programming and a strong command of English language are required. French language is preferable, but not necessary.

Advisors

Paul Cupillard (GeoRessources, Université de Lorraine)

Dragan Grgic (GeoRessources, Université de Lorraine)

Location: Nancy (France), a UNESCO World Heritage city with a vibrant student life and a rich cultural
agenda, only 90 minutes away from Paris, Luxembourg and Strasbourg

Project #2: Stochastic fault and fracture modelling: towards a new model for 3D seismic interpretation

 Starting date: September 2024 or later                             Deadline for applications: May 31, 2024 

Topic description

Faults and fractures are dislocations of underground rocks, which play a critical role in many subsurface applications, e.g., when forecasting the fate of CO2 injected in subsurface reservoirs and the mechanical hazards associated to the injection (SHAO ET AL., 2021; ZHAO & JHA, 2019). Predicting the geometry of faults is often done from 3D reflection seismic images, but the interpretation is challenging because of data coverage and limited seismic bandwidth (BOTTER ET AL., 2017; JULIO, CAUMON & FORD, 2015). Additionally, fault surfaces form complex networks in three dimensions, producing for instance relatively thin relay zones and complex branching patterns (ROCHE ET AL., 2021). Therefore, interpreting fault and fracture networks from seismic images is time-consuming process which may lead to different results depending on the interpreter or the methodology (ALCALDE ET AL., 2017; ROBLEDO CARVAJAL, BUTLER & BOND, 2023). The goal of the proposed PhD is find new ways to automate the 3D seismic interpretation process and to produce fault scenarios that reflect the structural knowledge. To do this, the idea is to leverage on recent advances in the area of marked point processes. Indeed, some new models been developed specifically to characterize and model fractures and faults in two dimensions with promising results (BONNEAU, CAUMON & STOICA, 2023; BONNEAU & STOYAN, 2022; SHAKIBA ET AL., 2022; TATY-MOUKATI ET AL., 2023). To extend these models to three dimensions, we can use the general framework of the Bisous Model (STOICA, GREGORI & MATEU, 2005). In this context, the integration of geological concepts may rely on the specific choice of the statistical model and also on the choice of parameters. Therefore, the area of investigation for this PhD will also include the issue of parameter inference from incomplete interpretations with approximate Bayesian methods (STOICA ET AL., 2017, 2021). The methodology will be tested and validated against a natural 3D sample (DOWD ET AL., 2009), publicly available 3D seismic data and possibly also two-dimensional outcrop data. This PhD will be co-advised by Guillaume Caumon and Radu Stoica.

References

ALCALDE J, BOND CE, JOHNSON G, ELLIS JF & BUTLER RWH. (2017). Impact of seismic image quality on fault interpretation uncertainty. GSA Today. https://doi.org/10.1130/GSATG282A.1

BONNEAU F, CAUMON G & STOICA RS. (2023). Fracture Network Characterization Using Stochastic Simulations of Marked Point Process And Bayesian Inference. 2023 RING Meeting.

BONNEAU F & STOYAN D. (2022). Directional Pair‐Correlation Analysis of Fracture Networks. Journal of Geophysical Research: Solid Earth 127(9). https://doi.org/10.1029/2022JB024424

BOTTER C, CARDOZO N, LECOMTE I, ROTEVATN A & PATON G. (2017). The impact of faults and fluid flow on seismic images of a relay ramp over production time. Petroleum Geoscience 23(1):17‑28. https://doi.org/10.1144/petgeo2016-027

DOWD PA, MARTIN JA, XU C, FOWELL RJ & MARDIA KV. (2009). A three-dimensional fracture network data set for a block of granite. International Journal of Rock Mechanics and Mining Sciences 46(5):811‑818. https://doi.org/10.1016/j.ijrmms.2009.02.001

JULIO C, CAUMON G & FORD M. (2015). Sampling the uncertainty associated with segmented normal fault interpretation using a stochastic downscaling method. Tectonophysics 639:56‑67. https://doi.org/10.1016/j.tecto.2014.11.013

ROBLEDO CARVAJAL F, BUTLER RWH & BOND CE. (2023). Mapping faults in 3D seismic data – why the method matters. Journal of Structural Geology:104976. https://doi.org/10.1016/j.jsg.2023.104976

ROCHE V, CAMANNI G, CHILDS C, MANZOCCHI T, WALSH J, CONNEALLY J, SAQAB MM & DELOGKOS E. (2021). Variability in the three-dimensional geometry of segmented normal fault surfaces. Earth-Science Reviews 216:103523. https://doi.org/10.1016/j.earscirev.2021.103523

SHAKIBA M, LAKE LW, GALE JFW & PYRCZ MJ. (2022). Multiscale spatial analysis of fracture arrangement and pattern reconstruction using Ripley’s K-function. Journal of Structural Geology 155:104531. https://doi.org/10.1016/j.jsg.2022.104531

SHAO Q, MATTHAI S, DRIESNER T & GROSS L. (2021). Predicting plume spreading during CO2 geo-sequestration: benchmarking a new hybrid finite element–finite volume compositional simulator with asynchronous time marching. Computational Geosciences 25(1):299‑323. https://doi.org/10.1007/s10596-020-10006-1

STOICA RS, DEACONU M, PHILIPPE A & HURTADO-GIL L. (2021). Shadow Simulated Annealing: A new algorithm for approximate Bayesian inference of Gibbs point processes. Spatial Statistics 43:100505. https://doi.org/10.1016/j.spasta.2021.100505

Working environment, context and location

The successful candidate will work in the RING Team, a pluridisciplinary and diverse group of 12-15 researchers and graduate students working at the interface of geoscience, computer science and applied mathematics. The RING team is part of Ecole Nationale Supérieure de Géologie and of the GeoRessources laboratory, a research lab of Université de Lorraine and CNRS. The successful PhD Student will also closely interact with the Institut Elie Cartan de Lorraine (IECL). Both labs are located in Nancy,(France), a UNESCO World Heritage city with a vibrant student life and a rich cultural agenda, only 90 minutes away from Paris, Luxembourg and Strasbourg. The research team is driven by passion for developing computer-based methods and theories for geological modeling, serving the geoscience community to address scientific and natural resource management challenges in the context of the energy transition.
The PhD scholarship is sponsored by an international consortium companies and research institutes. This scholarship offers many opportunities regarding the orientation of the future career of successful candidates (industrial or academic). It has a strong industry partnership culture and values collaboration and scientific exchange.

Requirements

The ideal candidate is passionate about science, has a solid background in applied mathematics, statistics and physics, and has strong scientific writing skills. An experience in computer programming is required. A background or a proven interest in geoscience is appreciated but not mandatory. Candidates should hold a MSc in Geophysics or Physics, Computer Science, (quantitative) Earth Sciences, Geostatistics, Applied Mathematics, or related fields. A strong command of English language is required. French language is preferable, but not necessary.

Advisors 

Guillaume Caumon (RING-GeoRessources, Université de Lorraine)

Radu Stoica (IECL, Université de Lorraine)