Abstract

Net to gross (NTG) is an important parameter in evaluating the volumes of hydrocarbon in place (VHIP) in reservoirs, and proper evaluation of this parameter will lead to significant accuracy in the estimated reserves. The use of conventional petrophysical log evaluations often does not provide sufficient resolution for net sand analysis of reservoirs, especially in laminated reservoir rocks. The uncertainties associated with log-derived net-to-gross estimates arise from the petrophysical shale volume (Vsh) cutoffs used in deriving the net sand count over a reservoir interval. One way of improving the net-to-gross estimates is by using a model that calibrates log-derived net to gross to a core equivalent, which is the more accurate representation of net sand counts. In this study, a model for calibrating log-derived net to gross to a core equivalent based on genetic units and facies associations of reservoir rocks in three wells (wells 7, 36, and K008) was established. Ultraviolet core photographs show a good contrast between hydrocarbon-stained sandstones and shales, and combining it with white light-slabbed core images facilitated a manual net sand count of the core photographs on a bed-by-bed basis. Petrophysical shale volume (Vsh) cutoff derived from two volumes of shale indicators was applied to generate net sand counts, which were used to get log-derived net-to-gross values. Then, the net to gross from core images and petrophysical clay volume (Vsh) analysis were compared by facies associations, and this comparison yielded a reliable core-calibrated net-to-gross model, which reduces the uncertainties in net-to-gross values estimated from Vsh cutoffs. The results show that for the distributary channel sands, net to gross derived using Vsh cutoff results in an underestimation of net to gross by about 6–10 % when compared with the core-calibrated net to gross, while for the upper shoreface units, Vsh cutoff overestimates net to gross by about 7–10 % when compared to its core-calibrated equivalent.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.