2019 May 07

Location: Coors Tech

Attending

Jihyun Andy Thomas Antoine Bin Iga

Key takeaways

  • The well log GAN project to be a tutorial-like paper in Geophysics
  • Well log GAN peeps will meet weekly over the summer (TBD)
  • In-person meetings to resume on campus in Fall semester

Problems

  • Data still needs to be better cleaned
  • Identify other potential well data types besides resistivity
  • Check the units of the well data
  • Hani’s like a Pokemon, We gotta catch em.

Updated notes on well log paper

  • Scope of paper
    • Stick to CNN-based GAN
    • Multi-dimensional training data after 1D success
    • Tone is tutorial-like
  • Motivation
    • lack of geosci training data
    • well logs are simple and high fidelity
    • ubiquitous
    • oil,water,mining
    • generator
    • no petro-phys model/simulator
    • act as a prior for inversion
      • mention gradients?
    • links different types of logs
    • well log data recovery
    • unsupervised
  • Contributions of paper
    • published curated dataset
    • published trained network
    • GAN tutorial
    • foothold into further GAN work
  • Outline of paper
    • Intro
      • Geology of Kansas - postpone to Fall
      • GAN background - Andy, Jihyun, Bin, and Iga
      • RILD background - Andy
    • Methods
      • QC/data cleaning - Andy
      • GAN - Andy, Jihyun, Bin, and Iga
      • Cross-validation - Thomas
      • spatial stats
      • wavelet transform
      • Fourier transform
      • PCA
    • Results
      • QC/data cleaning - Andy
      • GAN - Andy, Jihyun, Bin, and Iga
      • Cross-validation - Thomas
      • spatial stats
      • wavelet transform
      • Fourier transform
      • PCA
    • Discussion
      • each result item
      • Answer: What did/didn’t the network learn
      • speculation on use cases
      • recommendations for changes
      • predictions/future work
  • Task leader breakdown
    • Jihyun: Gan literature review
    • Thomas: statistical analysis
    • Andy: Data cleaning
      • may need help
      • Download zipped las files from KGS (link on mlgp website)
      • check units: depth and Ohm-m
      • Do our best to handle well geometry
      • ID Nans
      • Handle NaNs
      • ID most popular aliases
      • write functions in .py file
      • Function 1
        • takes: a well log, mneumonic
        • returns mask for nan, depth
      • Function 2
        • takes: data, mask, depths
        • returns: ‘clean’ data
      • Interpolate over no more than 10 ft

Agenda for next meeting

  • Go get a burger
  • Communicate work done over the summer
  • Line up potential speakers from GP department for the fall

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