Value of information in parameter identification and optimization of hydrocarbon reservoirs

This paper describes a recently introduced methodology to perform value of information (VOI) analysis within a closed-loop reservoir management (CLRM) framework, and adds a first step to improve the computational efficiency of the procedure. CLRM is a combination of model-based optimization and model-parameter identification applied to large-scale models of subsurface hydrocarbon reservoirs. The approach is illustrated with a simple two-dimensional model of an oil reservoir produced with water injection. The results are compared with previous work on other measures of information valuation. We show that our method is a more complete, although also more computationally intensive, approach to VOI analysis in a CLRM framework. We recommend it to be used as the reference for the development of more practical and less computationally demanding tools for VOI assessment in real fields.