Paul Baville

Thesis topic:  Complexe sedimentary basin models uncertainties assessment by simulating stochastically well correlations from log and core data using the Dynamic Time Warping algorithm.

Thesis supervisor: Guillaume Caumon (Univ. Lorraine - RING Team)

Thesis co-supervisors: Cédric Carpentier (Univ. Lorraine - CNRS) & Marcus Apel (Equinor)

Thesis monitoring committee:  Antoine Tabbone (Univ. Lorraine - Loria) & Dirk Knaust (Equinor)

Research Topics:

  • Stochastic detection of stratigraphic sequences from well data.
  • Stochastic multi-wells correlation from well data.

Achievements (2019 - 2020):

  • Magnetostratigraphic time-to-depth multi-well correlation using the Dynamic Time Warping on well-log data.
  • Facies correlation based on lithostratigraphic and chronostratigraphic associations based on the paleo-environment (transport direction, paleo-depth, paleo-distality ...) using Dynamic Time Warping on well-log data.

Achievements (2018 - 2019):

  • Stochastic detection of stratigraphic sequences from well data (Gamma Ray log) using discrete wavelet transform (Haar functions).
  • Sedimentological interpretation of well core samples and creation of different well logs based on these different interpretations (Petrophysical facies, genetic facies …) + parasequence interpretations.
  • Facies transition probability computation to constraint stochastic correlations using observed data.
  • Stochastic multi-well correlation from well data (Gamma Ray log + genetic facies interpretation on core samples) using Dynamic Time Warping algorithm to compute the n-best correlations.

Contact Information

E-Mail :This email address is being protected from spambots. You need JavaScript enabled to view it.
Phone number:+33 3 72 74 45 19
Cell:+33 6 67 67 09 58
ENSG office number:F221