Integrated Workflow to Estimate Permeability Through Quantification of Rock Fabric Using Joint Interpretation of Nuclear Magnetic Resonance and Electric Measurements
- Artur Posenato Garcia (The University of Texas at Austin) | Yifu Han (The University of Texas at Austin) | Zoya Heidari (The University of Texas at Austin)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- Publication Date
- October 2018
- Document Type
- Journal Paper
- 672 - 693
- 2018. Society of Petrophysicists & Well Log Analysts
- 2 in the last 30 days
- 247 since 2007
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Variable depositional cycles and severe diagenesis are among the main contributing factors to the complex pore networks encountered in formations, such as carbonates. This complexity is often not reliably incorporated in conventional permeability models. Conventional methods for permeability assessment, including electrical-based models (e.g., Katz and Thompson) and nuclear magnetic resonance (NMR)-based models (e.g., Coates and Schlumberger-Doll-Research), either require characterization of the pore network or calibration efforts, such as detection of cutoff values and assessment of constant model parameters. Joint evaluation of dielectric permittivity, resistivity, and NMR measurements enables capturing pore-network connectivity, tortuosity, and pore-throat-size distribution for real-time and reliable permeability evaluation.
In this paper we (a) estimate parameters that quantify rock fabric (e.g., tortuosity, effective pore size, and pore-throat- size distribution) by joint interpretation of electrical resistivity, dielectric permittivity, and NMR measurements, (b) develop a new workflow for permeability assessment that incorporates rock fabric parameters, and (c) validate the reliability of the new workflow in pore- and core-scale domains using electrical resistivity, dielectric-permittivity, NMR, mercury injection capillary pressure (MICP), and permeability measurements. To achieve these objectives, we introduce a workflow to estimate rock fabric properties as inputs for permeability assessment. NMR measurements are used to estimate porosity and effective pore size. Dielectric-permittivity and resistivity measurements are used to estimate tortuosity and constriction factor. Then, we calculate pore-throat-size distribution from the constriction factor and effective pore size. Finally, the aforementioned rock fabric parameters are used to estimate permeability without calibration efforts.
We successfully validated the introduced workflow on core samples from different lithofacies. Estimates of pore-throat radius obtained using the new method are in agreement with those from MICP measurements. We also applied the new workflow in the pore-scale domain using directional resistivity results obtained from numerical simulations as inputs. We demonstrate that directional-permeability estimates obtained from the introduced workflow in the pore-scale domain agree well with the actual permeability of the samples obtained from numerical simulations in the x-, y-, and z-directions. The proposed workflow reduced the relative error in permeability estimates by 50% in the pore-scale domain, compared to the conventional methods based on porosity-permeability correlations. It also resulted in average relative error of less than 20% in permeability estimates in the core-scale domain. Furthermore, the new workflow eliminates the need for calibration efforts in permeability assessment by honoring and quantifying rock fabric and enables assessment of directional permeability, if directional-resistivity measurements are available.
|File Size||10 MB||Number of Pages||22|