Investigating uplift in the South-Western Barents Sea using sonic and density well log measurements

Abstract:

Sediments in the Barents Sea have undergone large amounts of uplift due to Plio-Pleistoncene deglaciation as well as Palaeocene-Eocene Atlantic rifting. Uplift affects the reservoir quality, seal capacity and fluid migration. Therefore, it is important to gain reliable uplift estimates in order to evaluate the petroleum prospectivity properly. To this end, a number of quantification methods have been proposed, such as Apatite Fission Track Analysis (AFTA), and integration of seismic surveys with well log data. AFTA usually provides accurate uplift estimates, but the data is limited due to its high cost. While the seismic survey can provide good uplift estimate when well data is available for calibration, the uncertainty can be large in areas where there is little to no well data.

We estimated South-Western Barents Sea uplift based on well data from the Norwegian Petroleum Directorate. Primary assumptions include time-irreversible shale compaction trends and a universal normal compaction trend for a specified formation. Sonic and density logs from two Cenozoic shale formation intervals, Kolmule and Kolje, were used for the study. For each formation, we studied logs of all released wells, and established exponential normal compaction trends based on a single well. That well was then deemed the reference well, and relative uplift can be calculated at other well locations based on the offset from the normal compaction trend. We found that the amount of uplift increases along the SW to NE direction, with a maximum difference of 1,447 m from the Kolje FM estimate, and 699 m from the Kolmule FM estimate. The average standard deviation of the estimated uplift is 130 m for the Kolje FM, and 160 m for the Kolmule FM using the density log. While results from density logs and sonic logs have good agreement in general, the density log provides slightly better results in terms of higher consistency and lower standard deviation. Our results agree with published papers qualitatively with some differences in the actual amount of uplifts. The results are considered to be more accurate due to the higher resolution of the log scale data that was used.