Nonlinear data reconciliation in gold processing plants

Data reconciliation in hydrometallurgy process is less common than in mineral processing, due to the more complex mathematical formulation of the problem to describe the process balances that can include multiphase and multi-component reactions and mass transfer. In this case, to avoid thermodynamic violations, the use of inequality constraints, in addition to the classical equality mass and energy balances, can be mandatory. This paper presents two case studies of data reconciliation for a gold extraction plant using the direct optimization of a nonlinear objective function and nonlinear constraints that includes equality and inequality equations. The problems are solved using a sequential quadratic programming algorithm and the results demonstrate the applicability of this approach to data reconciliation in hydrometallurgical processes generating reliable results, without mass balance or thermodynamic violations.