Abstract:
To address the growing energy demand, hydrocarbon exploration must adopt the most robust and optimized methods to uncover both untapped and previously challenging reserves, such as heterogeneous and thin layers that were difficult to access with outdated technology. While seismic reflection is a widely used and reliable technique for detailed subsurface exploration, it has its limitations. Seismic inversion, however, plays a crucial role in enhancing reservoir understanding by addressing these limitations. It does this by translating geological layer properties into elastic or acoustic impedances, thereby improving upon the shortcomings of seismic reflection data (Li et al., 2020; Liu et al., 2018; Campbell et al., 2015).
Seismic inversion converts traditional seismic data into formation elastic characteristics, allowing for direct calibration to rock properties and a better interpretation of subsurface images. Elastic properties such as p-impedance (Zp), simpedance (Zs), Vp/Vs ratio, Poisson's ratio, Lambda-rho, and Mu-rho are instrumental in assessing reservoir characteristics like lithology, fluid type, and porosity (Moghanloo et al., 2018; Hampson et al., 2005). However, seismic data can be affected by various factors including lithological variations, acquisition challenges, frequency limitations, and depositional changes (Mahmood et al., 2018; Azeem et al., 2017). Reservoir characterization becomes even more difficult when hydrocarbonbearing layers are below seismic vertical resolution (Babasafari et al., 2020).
In the study area, the thin, heterogeneous potential reservoir sands were not distinguishable using the limited frequency seismic data. This issue arises not only from the conventional seismic data missing both low and high frequencies but also from the failure of deterministic inversion methods to highlight subtle geological features (Xiang and Lubis, 2017; Ansari et al., 2014).
In the Central Indus Basin (CIB), clastic reservoirs from the Cretaceous period are widespread but show considerable heterogeneity in thickness and properties due to variable depositional environments (Ali et al., 2017). The sand intervals of the LGF are significant, consisting thin, fluvio-deltaic sand packages interbedded with shales. Mapping these thin channelized sands (thickness < ∼17 m) is crucial for understanding drainage patterns and planning future wells. In the Mubarak Block, the LGF has been productive in several wells but has posed challenges in others due to lithological complexities and layer thickness issues, leading to field uncertainties. Previous studies by Azeem et al. (2017), Toqeer et al. (2017), Anwer et al. (2017), and others have focused on petrophysical evaluations and elastic well logs that are foundational for inversion operations to derive elastic property volumes like p- impedance, Vp/Vs ratio, s-impedance, and Poisson's ratio (Dasgupta and Gofer, 2021; Mahgoub et al., 2017). However, measured elastic logs can sometimes be insufficient for accurately capturing thin heterogeneous reservoirs, potentially affected by issues such as washouts, mud filtrate invasion, or missing shear sonic logs (S-wave). To address these limitations, petro-elastic models (PEMs) are developed within the rock physics framework. These models help in precise facies delineation and capturing litho-facies in inverted elastic volumes (Shakir et al., 2021; Khan et al., 2021).
PEMs bridge geological and reservoir parameters to estimate elastic responses for more accurate quantitative interpretation (Miraj et al., 2021). Consequently, prior to seismic inversion, PEMs are developed based on in-situ reservoir parameters such as pressure, salinity, temperature, porosity, saturation, and lithology volumes to predict facies-consistent elastic responses (Gray et al., 2015; Avseth et al., 2016; Omudu et al., 2008). Thus, applying Rock Physics and seismic inversion techniques will aid in elucidating the thin, heterogeneous reservoir sand facies and their extent, which are challenging to resolve with limited seismic resolution.
