Optimization of Cement Spacer Rheology Model Using Genetic Algorithm (RESEARCH NOTE)

The primary cement job is a critical step in successful well completion. To achieve effective cementing job, complete mud removal from the annular 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 in 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.