We present a simulation study of a mature reservoir for CO2Enhanced Oil Recovery (EOR)development. This project is currently recognized as the world's largest project utilizing post-combustion CO2 from power generation flue gases. With a fluvial formation geology and sharp hydraulic conductivity contrasts, this is a challenging and novel application of CO2 EOR. The objective of this study is to obtain a reliable predictive reservoir model by integrating multi-decadal production data at different temporal resolutions into the available geologic model. This will be useful for understandingflow units, heterogeneity features and their impact on subsurface flow mechanisms to guide the optimization of the injection scheme and maximize CO2 sweep and oil recovery from the reservoir.

Our strategy consists of a hierarchical approach for geologic model calibration incorporating available pressure and multiphase production data. The model calibration is carried out using regional multipliers whereby the regions are defined using a novel Adjacency Based Transform (ABT) accounting for the underlying geologic heterogeneity. To start with, the Genetic Algorithm (GA) is used to match 70-year pressure and cumulative production by adjusting pore volume and aquifer strength. Water injection data for reservoir pressurization prior to CO2 injection is then integrated into the model to calibrate the formation permeability. The fine-scale permeability distribution consisting of over 7 million cells is reparametrized using a set of linear basis functions defined by a spectral decomposition of the grid connectivity matrix (grid Laplacian). The parameterizationrepresents the permeability distributionusing a few basis function coefficients which are then updated during history matching. This leads to an efficient and robust workflow for field scale history matching.

The history matched model provided important information about reservoir volumes, flow zones and aquifer support that led to additional insight to the prior geological and simulation studies. The history matched field-scale model is used to define and initialize a detailed fine-scale model for a CO2 pilot area which will be utilized for studying the impact of fine-scale heterogeneity on CO2 sweepand oil recovery. The uniqueness of this work is the application of a novel geologic model parameterization and history matching workflow formodeling of a mature oil field with decades of production history and which is currently being developed with CO2 EOR.

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