Year: 2025
Type: article
Abstract: Predicted subsurface acoustic impedance (AI) is one of the most reliable geological parameters for understanding the properties of rocks and seismic investigation of reservoir rocks. This study aims to derive an empirical relationship between the calculated AI and synthetic AIs using the petrophysical parameters of carbonate rocks, Sirte Basin, Libya. Well log data from eight oil wells located in the western Sirte Basin is used to derive the empirical equations for the Farrud member (Bayda Formation, Lower Paleocene). These derived synthetic AI equations were tested in nine wells of different oil fields with sequences from the Paleocene and Eocene ages for validation. Hence, petrophysical evaluation illustrates the Furrud member includes four lithofacies: dolomite, tight limestone, porous limestone, and anhydrite. Therefore, the results of the synthetic AIs logs closely match the actual calculated logs calculated AI in most of the tested intervals of the wells. Moreover, results of the regression analysis between calculated AI and AIs showed strong, significant correlation relationships at P value less than 0.05. The obtained significance level (P=0.00), which is below 0.05, reflects the reliability of the derived synthetic AI empirical equations in calculating the AI of carbonate rocks with the same lithofacies (dolomite and limestone) rather than anhydrite rocks, especially those that lack bulk density (ρb) or sonic (ΔT) logs in the Sirte Basin.
Source: Egyptian Journal of Petroleum
Authors: Bahia M. Ben Ghawar, Emad A. Al-Heety
Institutions: University of Tripoli, University of Anbar
Language: English
Subfield: Geophysics
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4413399362