Our work focuses on developing a novel approach to improving reservoir characterization using the Adjoint method applied to history matching and optimization workflows. The developed approach, termed the “Adjointbased model screening method”, can be used to reveal hidden reservoir features not captured in reservoir models. The need for the development of our model screening method is necessitated by reservoir simulation models that miss important reservoir behaviours occurring beneath the surface. The impact of such modelling practice on history matching is the extreme tweaking of reservoir parameters to fit such models to available measured data. This paper demonstrates the strength of our approach in revealing the location of hidden faults and channels using synthetic homogeneous models.

Over the course of our research, an efficient model screening approach capable of revealing hidden reservoir behaviour has been developed and subjected to synthetic homogeneous blind tests. Our model screening approach utilizes reservoir permeabilities as input to screen our synthetic homogeneous models for hidden reservoir features like faults and channels. Observed data are generated from cases containing faults and/or channels and cases without these faults/channels are defined as the starting case. The Adjoint method is then used to reveal the location of these hidden reservoir features on a grid block basis.

In order to ascertain the superiority of our model screening approach, we compared the performance of our approach to other approaches reported in literature [Capacitance Resistance Model (CRM) and Interwell Numerical Simulation Model with Front Tracking (INSIM-FT)]. Results obtained demonstrate that our Adjoint-based model screening method is capable of handling varying and constant water injection rates as opposed to other approaches mentioned that can handle only varying injection rates. In addition, besides revealing the location of channels and faults, our approach infers the degree of transmissivity of faults. The developed approach was tested with 2-D and 3-D homogeneous models and results obtained proved that regardless of model dimensionality, hidden reservoir features can be revealed.

The most significant finding is that the accuracy of the adjoint-based model screening method in revealing the location of hidden reservoir features depends on the number of wells existing in the reservoir and their arrangement.


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