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Direct fluid indicator analysis is used for identifying the fluid type in porous rocks from seismic data. The predictability of fluid types from such methods differs between cases. A large variety of attributes can potentially be relevant for such analyses, and combinations of such will increase the reliability of the resulting predictions.

This master thesis will explore how combination of different attributes can improve the predictability of DFI analyses in the greater Fram area, and what geological factors constrain the applicability of DFI methods. The work will include analyses of North Sea fields with easily identifiable fluid contacts and then transition to areas where the fluid indicators are less clear. The work will include analyses of seismic data, including AVO. Attribute extraction from seismic data will be performed based on interpreted seismic horizons that are provided by Equinor. Analyses of the extracted attribute maps will include programming in Matlab / Python.

The desired outcome of the work is (a) an automated workflow which flags areas of interest and (b) a workflow for quality assurance of results that stem from use of the automated workflow.

Proposed course plan during the master's degree (60 ECTS):
Autumn courses:
GEOV 272 (10) Seismic Interpretation | ºÚÁϳԹÏ×ÊÔ´
GEOV 274 (10) Environmental and Reservoir Geophysics | ºÚÁϳԹÏ×ÊÔ´
GEOV 276 (10) Introduction to Theoretical Seismology | ºÚÁϳԹÏ×ÊÔ´

Spring courses:
GEOV 218 (10) Rock Physics | ºÚÁϳԹÏ×ÊÔ´
GEOV 302 (10) Data analysis in earth science | ºÚÁϳԹÏ×ÊÔ´
GEOV 375 (10) Advanced Applied Seismic Analysis | ºÚÁϳԹÏ×ÊÔ´

External data
Seismic data and interpreted surfaces from Equinor

Student

Isha Bhelay Gahlla

Supervisors

Christian Hermanrud (main supervisor)

Tor Naustdal Helgheim, Equinor

Øyvind Skjæveland, Equinor

Isabelle Lecomte, ºÚÁϳԹÏ×ÊÔ´-GEO