--> Scale Dependency of Pore Space and Its Impact on Flow Dynamics Within Carbonate Reservoirs

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Scale Dependency of Pore Space and Its Impact on Flow Dynamics Within Carbonate Reservoirs

Abstract

Carbonate reservoirs commonly possess pore space that ranges in size from microporous voids at the micron scale to karst features at the meter scale. Permeability through these rocks is dependent on the size, distribution and interconnectivity of the different pore space components, which ultimately impacts how a reservoir will respond during production including where hydrocarbons flow into a borehole during primary recovery and sweep efficiency during waterflooding. While most analyses on porosity and permeability occur at the core plug scale (1-1.5” diameter), these measured values often underestimate the permeability required to match well productivity where multi-scale pore system features are present. In order to address the impact of scale dependency on flow behavior within carbonate rocks, we have developed a field-based, integrated approach on San Salvador Island, Bahamas, that couples rock characterization (i.e., stratigraphy and pore types) with measurements of porosity, permeability, and fluid flow across a broad spectrum of features. Pore space on San Salvador Island ranges from microporosity within the carbonate matrix to meter-wide karst conduits that connect interior lakes to the ocean. We use standard techniques such as MICP, minipermeameter, and routine core analysis to capture the pore space ranging from the μm- to dm-scale; however, the larger scale-dependent pore types, e.g., sinkholes and conduits, cannot be measured using these standard techniques. Instead, we use LIDAR and hydrogeology surveillance to evaluate the impact these larger features have on platform-wide porosity, permeability, and connectivity. By expanding our observations to the field-wide scale common to many producing carbonate reservoirs, we are able to evaluate how the interplay between these different pore types at multiple scales may drive reservoir performance. Such observations should be critical in guiding decisions related to field development, well planning, and reservoir management.