The challenge of optimizing hydrocarbon reservoir performance lies in constructing an accurate characteristic map, which is produced by costly historical data matching and non-uniqueness issues. In this study, we introduce an algorithm that addresses these challenges by employing a cross-gradient method to simultaneously derive a meaningful rock physics model and integrate it into a more general objective function. By incorporating data misfit and cross-gradient regularization terms, this approach enhances reservoir model accuracy and improves seismic imaging, enabling more informed decision-making in reservoir management and production optimization.
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