Understanding reservoir heterogeneity using variography and data analysis: an example from coastal swamp deposits, Niger Delta Basin (Nigeria)
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Date
2020-12
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Instytut Geologii UAM
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Abstract
For efficient reservoir management and long-term field development strategies, most geologists and asset managers
pay special attention to reservoir chance of success. To minimise this uncertainty, a good understanding of reservoir
presence and adequacy is required for better ranking of infill opportunities and optimal well placement. This can be
quite challenging due to insufficient data and complexities that are typically associated with areas with compounded
tectonostratigraphic framework. For the present paper, data analysis and variography were used firstly to examine
possible geological factors that determine directions in which reservoirs show minimum heterogeneity for both discrete
and continuous properties; secondly, to determine the maximum range and degree of variability of key reservoir petrophysical
properties from the variogram, and thirdly, to highlight possible geological controls on reservoir distribution
trends as well as areas with optimal reservoir quality. Discrete properties evaluated were lithology and genetic units,
while continuous properties examined were porosity and net-to-gross (NtG). From the variogram analysis, the sandy
lithology shows minimum heterogeneity in east-west (E–W) and north-south (N–S) directions, for Upper Shoreface
Sands (USF) and Fluvial/Tidal Channel Sands (FCX/TCS), respectively. Porosity and NtG both show the least heterogeneity
in the E–W axis for reservoirs belonging to both Upper Shoreface and Fluvial Channel environments with
porosity showing a slightly higher range than NtG. The vertical ranges for both continuous properties did not show
a clear trend. The Sequential Indicator Simulation (SIS) and Object modelling algorithm were used for modelling the
discrete properties, while Sequential Gaussian Simulation (SGS) was used for modelling of the continuous properties.
Results from this exercise show that depositional environment, sediment provenance, topographical slope, sub-regional
structural trends, shoreline orientation and longshore currents, could have significant impacts on reservoir spatial
distribution and property trends. This understanding could be applied in reservoir prediction and for generating stochastic
estimates of petrophysical properties for nearby exploration assets of similar depositional environments.
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porosity, permeability, flow zone index, property modelling, shoreface, fluvial channels
Citation
Geologos 26, 3 (2020): 207-218