History Matching of Time-Lapse Deep Electromagnetic Tomography with A Feature Oriented Ensemble-Based Approach

Summary Carbonate reservoirs represent strongly complex geological structures whose main feature is that the flow dynamics primarily occurs in fractures. The complexity of the network of fractures as well as their interconnectedness may lead to unexpected flow patterns and uneven sweep efficiency. Determining the fracture distribution and reservoir properties of both matrix and fracture channels is quintessential for accurately tracking the fluid front movement in the reservoir, optimizing sweep efficiency, and maximizing hydrocarbon production. A feature oriented ensemble-based history matching workflow was introduced previously to enhance the characterization of petroleum reservoirs through the assimilation of time-lapse electromagnetic (EM) data in combination with other available measurements. Compared with seismic measurements, which provide effective information related to reservoir structure, deep EM measurements in the interwell volumes are more sensitive to distinguish between hydrocarbon fluids and water. The developed workflow calibrates model variables of interest utilizing the information of formation resistivity that is usually made available through geophysical inversion of raw EM data. Archie’s law is typically used to build a relation between formation porosity, fluid properties (e.g., water saturation and salt concentration) and formation resistivity. Instead of integrating directly the inverted EM resistivity data, which is usually of high dimensions and noisy in amplitude, the boundary or contour information extracted from the EM resistivity field is utilized through an image oriented distance parameterization combined with an iterative ensemble smoother. We are showcasing this framework on a realistic carbonate reservoir box model with a complex fracture channel network. Time-lapsed cross-well EM data was assimilated to update fracture and matrix reservoir properties, ensuring that the heterogeneity in the properties is maintained. The framework exhibited strong performance in the history matching of the complex carbonate reservoir structure. In comparison with conventional ensemble-based history matching techniques, this innovative developed approach led to significantly more accurate sweep efficiency maps, while maintaining the heterogeneity in the parameters between the fractures and the matrix. Finally, uncertainty in the saturation maps could be significantly reduced with the assistance of deep EM reservoir tomography. Carbonate reservoirs represent highly complex geological structures and are characterized by flow dynamics dominated by natural fractures. The complexity of the network of fractures as well as their interconnectedness may lead to unexpected flow patterns and uneven sweep efficiency. Determining the fracture distribution and reservoir properties of both matrix and fracture channels is quintessential for accurately tracking the fluid front movement in the reservoir, optimizing sweep efficiency, and maximizing hydrocarbon production. A feature-oriented ensemble-based history matching workflow was introduced previously to enhance the characterization of petroleum reservoirs through the assimilation of time-lapse electromagnetic (EM) data in combination with other available measurements. Compared with seismic measurements, which provide effective information related to reservoir structure, deep EM measurements in the interwell volumes are more sensitive to distinguish between hydrocarbon fluids and water due to the difference in electrical conductivity. The developed workflow calibrates model variables of interest utilizing the information of formation resistivity that is usually inferred through geophysical inversion of raw EM data. Archie’s law is typically used to describe the relation between formation porosity, fluid properties (e.g., water saturation and salt concentration) and formation resistivity. Instead of integrating directly the inverted EM resistivity data, which is usually of high dimensions and noisy in amplitude, the boundary or contour information extracted from the EM resistivity field is utilized through an image-oriented distance parameterization combined with an iterative ensemble smoother. We are showcasing this framework using a realistic carbonate reservoir box model with a complex fracture channel network. We history matched time-lapsed crosswell EM data to update fracture and matrix reservoir properties, by preserving the heterogeneity in the properties. The framework exhibited strong performance in the history matching of the complex carbonate reservoir structure. The developed innovative approach led to significantly more accurate sweep efficiency maps, while maintaining the heterogeneity in the fractures and the matrix parameters. Uncertainties in the saturation maps were also significantly reduced with the history matching of deep EM reservoir tomography data.