Petrophysics analysis provides different ways of estimating permeability. These methods include RQI- FZI, NMR based Timur-Coates or SDR equations, different methods of estimating permeability based on Stoneley wave and many more. In the well with comprehensive logging suite, it is possible to provide permeability estimation close to dynamic test results. However, modeling of the permeability in 3D represents a significant challenge, especially in the cases where significant lateral variations of properties are observed. In the majority of cases, seismic data provides the only continuous source of information for the inter-well spacing. Seismic inversion results, namely acoustic impedance and compressional to shear velocity ratio (Vp/Vs) provide hard data for the analysis. Required properties, such as total porosity, free fluid porosity and bounded water volume were estimated using stochastic algorithm described in Vorobiev et al (2024b). The stochastic algorithm uses anisotropic rock physics model described in Vorobiev et al (2024a). This algorithm uses dispersed, laminated clay volumes and saturation in addition to calibration parameters such as clean sand, clay porosity, minerals elastic moduli etc. as the inputs. As soon as stochastic algorithm converges, total porosity, bulk volume of movable and bound fluid can be used to calculate permeability using Timur-Coates equation (Timur 1968). In the study case production data suggested poor communication between two producers. Geological correlation and standard seismic interpretation have not found any potential barriers between the wells. The workflow was applied in two steps. The first step was feasibility analysis using well data. This stage includes anisotropic rock-physics model calibration, stochastic algorithm testing using sonic logs and density based acoustic impedance and Vp/Vs ratio to extract total porosity, movable and bounded fluid volumes and finally Timur-Coates equation calibration. The second step is to apply stochastic algorithm and calibrated Timur-Coates equation to the seismic inversion results. The step includes QC of the inversion results and investigation of the vertical resolution differences between seismic inversion data and well logs. Workflow application reveals that two wells separated by a zone with deterioration of the reservoir properties, best indicator for this tighter zone is derived from inversion based permeability cube. Several papers were published previously, discussing estimation of permeability using seismic inversion results. Most commonly it is rather methods employing correlations between acoustic impedance and porosity or using artificial neural nets. The proposed novel method employs stochastic algorithm based on analytical rock physics solution and calibrated Timur-Coates equation.
Vorobiev et al. (Sat,) studied this question.
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