Joint modeling and inversion of frequency-dependent dielectric constant and electrical resistivity well-log measurements has been addressed in literature in recent years. However, this problem is not studied for dual-porosity carbonate formations. Besides, the salinity and matrix dielectric constant are presumed to be known in previous studies. We have combined a model for brine dielectric constant and two laboratory-supported models for the electrical resistivity and dielectric constant of dual-porosity carbonates. Using this methodology, we replicate electrical resistivity and dielectric well-log measurements. Using a stochastic global optimization algorithm, we formulate a joint inversion workflow to estimate petrophysical properties of interest. For a constructed dual-porosity carbonate reservoir, we determine that the inversion workflow matches the forward-modeled data for the oil column, water column, and transition zone. We also found that our inversion workflow is capable to retrieve local model parameters (water-filled intergranular porosity and water-filled vuggy porosity) and global model parameters (matrix dielectric constant, lithology exponents for intergranular and vuggy pores, and salinity) with reasonable accuracy.
The controlled-source electromagnetic (CSEM) method has been successfully applied to petroleum exploration; however, less effort has been made to highlight the applicability of this technique for reservoir monitoring. This work appraises the ability of time-lapse CSEM data to detect the changes in fluid saturation during water flooding into an oil reservoir. We simulated a poorly consolidated shaly sandstone reservoir based on a prograding near-shore depositional environment. Starting with an effective porosity model simulated by Gaussian geostatistics, dispersed clay and dual water models were efficiently combined with other well-known theoretical and experimental petrophysical correlations to consistently simulate reservoir properties. The constructed reservoir model was subjected to numerical simulation of multiphase fluid flow to predict the spatial distributions of fluid pressure and saturation. A geologically consistent rock physics model and a modified Archie's equation for shaly sandstones were then used to simulate the electrical resistivity, showing up to 60% decreases in electrical resistivity due to changes in water saturation during 10 years of production. Time-lapse CSEM data were simulated at three production time steps (zero, five, and ten years) using a 2.5D parallel adaptive finite element algorithm. Analysis of the time-lapse signal in the simulated multicomponent and multifrequency data set demonstrates that a detectable time-lapse signal after five years and a strong time-lapse signal after ten years of water flooding are attainable using current CSEM technology.
Separation of fluid pore pressure and saturation using inverted time-lapse seismic attributes is a mandatory task for field development. Multiple pairs of inversion-derived attributes can be used in a crossplot domain. We performed a sensitivity analysis to determine an optimal crossplot, and the validity of the separation is tested with a comprehensive petroelastic reservoir model. We simulated a poorly consolidated shaly sandstone reservoir based on a prograding near-shore depositional environment. A model of effective porosity is first simulated by Gaussian geostatistics. Well-known theoretical and experimental petrophysical correlations were then efficiently combined to consistently simulate reservoir properties. Next, the reservoir model was subjected to numerical simulation of multiphase fluid flow to predict the spatial distributions of fluid saturation and pressure. A geologically consistent rock physics model was then used to simulate the inverted seismic attributes. Finally, we conducted a sensitivity analysis of seismic attributes and their crossplots as a tool to discriminate the effect of pressure and saturation. The sensitivity analysis demonstrates that crossplotting of acoustic impedance versus shear impedance should be the most stable way to separate saturation and pressure changes compared to other crossplots (e.g., velocity ratio versus acoustic impedance). We also demonstrated that the saturation and pressure patterns were detected in most of the time-lapse scenarios; however, the saturation pattern is more likely detectable because the percentage in pressure change is often lower than that of the saturation change. Imperfections in saturation and pressure patterns exist in various forms, and they can be explained by the interaction of saturation and pressure, the diffusive nature of pressure, and rapid change in pressure due to production operations.
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