Case study reveals complex mineralogy and reservoir properties via seismic inversion and rock physics.
Unconventional reservoirs exhibit significant heterogeneity and complex mineralogy. Variations in production from horizontal wells underscore the challenges posed by these source rocks. Seismic inversion is a crucial tool for understanding spatial variability. By integrating rock physics models with seismic results, we can identify lateral variations in elastic lithofacies, mineral composition, kerogen content, and porosity. Additionally, reservoir pressure estimation is vital for successful production. In this study, we present lithoclassification results and predictions of reservoir properties and pore pressure derived from prestack Amplitude-Variation-with Angle (AVA) inversions in the Midland Basin, West Texas. Despite significant lateral variation in unconventional reservoirs, mature kerogen-rich shales hold substantial hydrocarbon reserves. Identifying optimal locations for horizontal wells—based on reservoir and completion quality—is crucial for maximizing production. Reservoir Quality (RQ), determined by mineralogy, porosity, and kerogen content, defines reservoir potential. Completion Quality (CQ), influenced by factors like pore pressure, ensures effective hydraulic fracturing. An illustrative example is the Sprayberry and Wolfcamp formation in the Permian Basin, West Texas. In this case study, pre-stack AVA inversion was performed from Clearfork to Atoka formations in the Midland basin. Acoustic impedance and Vp/Vs ratio guided litho-classification. Petrophysical interpretation, combined with elastic properties, generated a probability density function (PDF) from well data. Applying PDFs to Seismic AVA inversion yielded lithological descriptions and associated probabilities. Additionally, a rock physics model, incorporating effective stress estimation, predicted reservoir properties (e.g., clay volume, carbonate content, kerogen, porosity, and pore pressure) based on AVA inversion results and lithological information.
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Dasgupta et al. (2025) studied this question.
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