Identifying and Modeling Evaporite Facies using Well Logs: Characterising the Devonian Elk Point Group salt giant

• Author / Creator

  Lord, Elaine

• Over the last century, study of evaporite deposits has evolved from modeling chemical successions and studying outcrops of insoluble material, to sedimentologic study of drill core paired with geochemical analysis. In this thesis, I add to published scientific literature on the Prairie Evaporite Formation, a succession of Middle-Devonian evaporate deposits in the Central Alberta Basin of Alberta, Canada. I combine new well log interpretation with sedimentologic studies in the literature to define six new evaporite facies in the Prairie Evaporite Formation, and present a new facies identification scheme that correlates wireline log signatures to core log data. Wireline log data from 994 wells and logs of seven cores in the Central Alberta Basin are compiled to assess stratigraphic relationships, lithological facies, textural features, and insoluble marker beds within the Prairie Evaporite Formation. This analysis identifies seven unique facies sequences within each cycle of the Prairie Evaporite in the Central Alberta Basin. I have produced 3D-facies models for each cycle in order to map facies distribution across the Central Alberta Basin and assess the change in depositional environments through time and across the basin. I infer water cyclicity and climate in the basin during the middle Devonian based on these depositional environments: modeled facies reflect a nearshore environment in the west and southwest Central Alberta Basin and an increasingly shallow and concentrated epeiric sea basinward. I speculate that application of this facies correlation scheme to other evaporite deposits of the world is possible, but requires calibration by correlation of wireline log data to core log data.

• Subjects / Keywords

  • Potash
  • Evaporite
  • Central Alberta Basin
  • Salt
  • Prairie Evaporite
  • Sedimentology
  • First salt
  • Sylvite
  • Halite
  • Elk Point

• Graduation date

  Spring 2020

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-m0jp-7g10

• License

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