Abstract

Early identification of zones with possible good production (“sweet spots”) in shale plays is important to optimize the return on capital investment. Analyzing elastic rock properties helps in the identification of sweet spots in the Vaca Muerta Formation. The vertical and lateral heterogeneity of total organic carbon (TOC) and carbonate content are two critical factors that partly control the geomechanical response of the rock. Unconventional reservoirs have low permeability, making it necessary to define brittle zones to stimulate the rock and induce fractures to produce. This leads to the definition of mineralogy ranges that help discriminate brittle and ductile rock based on rock properties. This study is based on a 3D seismic survey and several vertical pilot wells with full log suites. Horizon interpretations and logs are used to build a low-frequency model that together with prestack seismic data is input for seismic inversion. Inversion results predict Poisson's ratio (v) directly, and TOC, carbonate content, density (ρ), and Young's modulus (E) are obtained through a neural network approach. The product (Eρ) is an alternative parameter to describe brittle rock when ρ cannot be obtained reliably. As elastic parameters, E and v are related to the geomechanical response of the rock, aiding in the discrimination of brittle and ductile rock. An inverse relationship between TOC and E is observed and quantified, but the relationship is very poor with v. Likewise, a direct relationship between carbonate content and E is identified but not with v. E plays the largest role in the identification of brittle rock within the Vaca Muerta Formation. Rock-physics relationships to describe sweet spots (zones with hydrocarbon presence and brittle rock) differ between shale plays around the world. The detailed 3D model from seismic inversion and clustering makes it possible to determine the best zones for placement of schematic horizontal wells.

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