Porosity prediction using 3D seismic genetic inversion at F3 Block, offshore Netherlands

Abstract

Seismic and well information have been incorporated with a genetic inversion workflow using a supervised neural network in the F3 block, offshore Netherlands with a view to properly predicting porosity distribution within the selected reservoirs. This would provide spatial distribution of porosity within the field. Petrophysical parameters were estimated for the identified reservoirs (FS4, FS8, XYZ and ABC) across the four wells (F02-01, F03-02, F03-04 and F03-06) ranging from 780 to 1500 ms. Acoustic impedance (AI) and porosity cubes were
generated using a genetic neural network. Thereafter, acoustic and porosity maps were extracted for the selected reservoirs. The results of the inversion reflect that the acoustic impedance in the region varies from 2000 to 6000 kPa.s/m, indicating unconsolidated and less compacted formation within the study area. Porosity within the selected reservoirs varies from 0.25 to 0.40, which reflects very good to excellent porosity values within the study area. The plot of porosity from well (F02-01) and the predicted porosity from genetic inversion reveals a relatively good correlation coefficient of 68%. The hydrocarbon regions within the F3 block are in the Upper Jurassic – Lower Cretaceous strata which are found below the interval available for this study. The study underscores that the genetic inversion algorithm has proven effective in predicting porosity within the study area.