Optimization of Cement Spacer Rheology Model Using Genetic Algorithm

The primary job of cement is a critical step in successful well completion. To achieve effective cementing job, complete mud removal from the annular space is recommended. Spacer and flushers are used widely to achieve this goal. This study is about weighted cement spacer systems containing a surfactant package, weighting agent and rheological modifiers. Weighted spacer systems are utilized when a high formation fluid pressure is expected inside the wellbore. A testing program is conducted in laboratory to determine the spacer fluid rheological properties at different temperatures. The measured rheological properties are estimated using the known rheological models. Each model is firstly optimized using genetic algorithm as an optimization tool and then the rheological properties are modeled. The performance of the genetic algorithm is then tested by comparing the real laboratory data and modeled data. The results show that the polymer based spacer systems are better described using Herschel Bulkley Model. Also, it is concluded that the genetic algorithm with a good formulation can be used as an effective optimization tool to predict the rheological properties of the spacer systems.

Keywords:

Cement SpacerGenetic AlgorithmRheologyHigh-PressureHigh-Temperature