Optimization of cementation and tortuosity factors for improved estimation of water saturation with burial depths in the Niger Delta Basin

Abstract

The study determined the best values for Archie's cementation (m) and tortuosity (a) factors for improved estimation of water saturation with burial depths in the Niger Delta Basin. It solved the problem of wrong water saturation estimates that come from using static parameters, which do not account for the effect of burial depth and regional sedimentological factors. The study employed petrophysical and statistical methodology to enhance water saturation (Sw) estimation accuracy by optimising Archie’s parameters, specifically the cementation factor (m) with burial depth. Fifty-two core and log samples were examined from wells within the Eastern Central and Eastern Coastal Swamp Depobelts. Regression analysis was employed to estimate and calibrate the Archie parameters: tortuosity factor (a) and cementation exponent (m). The findings indicate a notable nonlinear reduction in the cementation factor with increasing depth, not in agreement with traditional predictions. The optimised parameters (a = 1.38, m = 1.54) were in agreement with measured resistivity data and surpassed several conventional models currently in use. These data affirm that the cementation factor is not constant but fluctuates dynamically with depth and depositional environment. The elevated sand concentration and diminished clay matrix of the Niger Delta's unconsolidated formations, especially the Agbada Formation, contribute to this depth-dependent behaviour. The depth-optimized model markedly improves the prediction of Sw and results in more precise estimations of stock tank oil initially in place (STOIIP). The study proposes a new empirical formation resistivity model, F = 1.38/ϕ^1.54, which accurately reflects the geological conditions of the study area. It highlights the importance of region-specific calibration in formation appraisal. The study has helped improve reserve estimation and reservoir development planning, particularly in the Niger Delta, by bridging the gap between theoretical assumptions and field data.