Integrated Shear-Log Prediction and Elastic Attribute Analysis for Lithology, Fluid, and Reservoir Quality Discrimination in the JOO Field, Niger Delta
Abstract
Effective reservoir characterization in clastic systems depends on robust rock physics analysis to reliably predict lithology, delineate facies, discriminate fluids, estimate reservoir properties, and support volumetric assessment. A persistent challenge is elastic non-uniqueness, where different lithology–fluid combinations produce similar seismic and log responses. This problem is pronounced in the JOO Field, a mature hydrocarbon-producing field in the Coastal Swamp depobelt of the Niger Delta with ∼200 MMboe recoverable resources, where shale intervals exhibit velocity responses comparable to gas-saturated sands, particularly in the absence of measured shear logs. To address shear log unavailability and reduce lithology–fluid ambiguity, this study integrates modified Gassmann shear log prediction with 3D post-stack seismic data and comprehensive well logs from four wells. We used predicted elastic logs to carry out rock physics analysis using elastic attribute crossplots and Lamé-parameter diagnostics to decouple fluid effects from lithological controls across the SFKO reservoir interval. Density–Gamma Ray crossplots provided first-order lithological separation of sands (2.0–2.35 g/cm3; 25–60 API), heteroliths (1.25–1.9 g/cm3; 60–75 API), and shales (2.25–2.5 g/cm3; >75 API). The weak Density–GR correlation (R2 ≈ 0.13) reflects strong reservoir heterogeneity rather than poor lithological discrimination. Vp/Vs–Acoustic Impedance (AI) crossplots, constrained by shale volume (Vsh ≤0.4) and quartz content (≤0.6), effectively resolved hydrocarbon sands (Vp/Vs 1.69–1.81; AI 6,350–8,300 g/cm3·m/s), brine sands (Vp/Vs 1.7–1.95; AI ≤8,500 g/cm3·m/s), and shales (Vp/Vs 1.8–2.05). Lamé-parameter attributes provided superior separation, with MuRho–Density crossplots constrained by Han's Dual Input model and LambdaRho–MuRho crossplots confirming lower λρ values (11–35 GPa·g/cm3) in hydrocarbon sands. Gas-bearing zones correspond to the lowest Density and λρ domains. These elastic responses are validated by reservoir properties, where high-quality sands exhibit 20–40% porosity and permeability of 2,500–7,000 mD, contrasting with shale and heterolithic facies (≤19% porosity; <2,000 mD). Overall, the integrated workflow robustly delineates lithology, fluid type, and reservoir quality, improving pre-drill prediction, fluid contact identification, and resource estimation, with direct applicability to similar Niger Delta reservoirs and analogous depositional settings globally.