Development of a Resistivity Model That Incorporates Quantitative Directional Connectivity and Tortuosity for Enhanced Assessment of Hydrocarbon Reserves
- Artur Posenato Garcia (University of Texas at Austin) | Zoya Heidari (University of Texas at Austin)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- October 2018
- Document Type
- Journal Paper
- 1,552 - 1,565
- 2018.Society of Petroleum Engineers
- Hydrocarbon Reserves, Electrical Measurements, Rock Fabric, Directional Pore Connectivity
- 12 in the last 30 days
- 163 since 2007
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Success of the strategies to exploit hydrocarbon reservoirs depends on the availability of reliable information about pore structure and spatial distribution of fluids within the pore space. Reliable quantification of directional pore-space connectivity and characterization of pore architecture are, however, challenging. The objectives of this paper include (1) quantifying the directional connectivity of pore space [connected pore volume (PV)] and rock components, (2) identifying geometry-defined fabric features that contribute to the pore-connectivity variations within the same formation (e.g., tortuosity, constriction factor) and introducing analytical/numerical methods and mechanistic models to estimate them, and (3) improving assessment of hydrocarbon saturation by introducing a new resistivity model that incorporates the directional pore-space-connectivity factor.
We introduce a new resistivity model that minimizes calibration efforts and improves assessment of hydrocarbon saturation in complex formations by incorporating a directional connectivity factor. The directional pore-space connectivity is defined as the geometry and texture of the porous media resulting from sedimentary and diagenetic processes, and is estimated with pore-scale images. The directional connectivity factor is a function of electrical tortuosity, and, therefore, we introduce a mechanistic equation that incorporates geometrical features of the pore space to accurately estimate electrical tortuosity. Then, we validate the new tortuosity model against results obtained from a semianalytical streamline algorithm in 3D pore-scale images from each rock type of interest in the formation. The actual electrical tortuosity obtained from numerical simulations is calculated with the geometry of the streamlines associated with the electric current and the corresponding time of flight (TOF) of electric charges.
We successfully applied the introduced method to two carbonate formations. The results confirm that the introduced directional-connectivity factor can detect rock-fabric features, through quantifying the connected PV and tortuosity, and that it is a function of the directional-diffusivity coefficient. The quantification of rock fabric and pore-space connectivity improves the estimation of hydrocarbon saturation by 43% compared with conventional methods. The use of such a parameter for rock-fabric characterization from pore-scale images helps to decrease the need for calibration efforts in the interpretation of borehole geophysical measurements. Just a few cuttings from different rock types are sufficient for the proposed method.
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