AAPG Bulletin, Vol.84, No.9, 1325-1339, 2000
Modeling quartz cementation and porosity in Middle Jurassic Brent Group sandstones of the Kvitebjorn field, Northern North Sea
Petrographic study of deeply buried Middle Jurassic Brent Group sandstones from the Kvitebjorn gas field in the Norwegian sector of the North Sea shows that quartz cement volumes range from less than 1% to almost 30% over short distances, and porosity ranges from 5 to 30%. A clear correlation between quartz surface area and quartz cement volume indicates that this variation is due to differences in quartz surface area available for quartz overgrowth formation, which, in turn, is a function of grain size, abundance of grain coatings, and quartz clast abundance. The correlation between quartz surface area and quartz cement volume also suggests that the quartz cementation process is a strongly precipitation rate-controlled process, and that quartz cementation can indeed be modeled quantitatively by modeling the precipitation step in the quartz cementation process. Using temperature history, detrital mineralogy, grain size, and grain coating abundance as input, quartz cement volumes were for 90% of the samples modeled to within 4% or less of observed values with the EXEMPLAR(R) diagenetic modeling program. Modeled porosities deviate from measured values by less than 3% for 75% of the samples, and the difference between measured and modeled porosities exceeds 5% for only two of the 40 samples. Deviations between modeled and measured quartz cement volumes do not correlate with distance to nearest stylolite, but a tendency for underestimating quartz cement in samples with low quartz surface areas may possibly be present. Comparison with results from modeling of quartz cementation in other sandstones shows that optimal fit between measured and modeled quartz cement volumes is not always obtained with the same values for the kinetic parameters controlling quartz precipitation rate per unit surface area as a function of temperature. The variation in optimal kinetics between data sets is probably partly due to inaccurate temperature histories, but improving the quartz surface area function may also reduce the range of optimal values for the kinetic parameters.