It has long been known that temperature during circulation and after cement placement is one ofthe most important parameters for the design of a slurry and the success of cement jobs. Since API co"elations do not take into account important parameters affecting the temperature evolution, simulators,which are sensitive to little known parameters, have been developed. This has made validation difficult or unconvincing, as there always exists a set of input parameters that can match observed temperature on a particular well. It has also significantly limited the widespread use of temperature simulators for field operations.In this paper we present a cementing temperature simulator which has been developed taking this inherent difficulty iilto account. The validation was performed by testing against 30 jobs from the API database, selected based on data completeness.With this simulator, temperature prediction has been considerably improved over the API method. The standard deviation, maximum overestimation and maximum underestimation have been reduced on the thirty API jobs.This model applies equally well to onshore and offshore,vertical and deviated wells, and takes into account other variables that affect temperatures while cementing.
It has long been known that temperature during circulation and after cement placement is one ofthe most important parameters for the design of a slurry and the success of cement jobs. Since API co"elations do not take into account important parameters affecting the temperature evolution, simulators,which are sensitive to little known parameters, have been developed. This has made validation difficult or unconvincing, as there always exists a set of input parameters that can match observed temperature on a particular well. It has also significantly limited the widespread use of temperature simulators for field operations.In this paper we present a cementing temperature simulator which has been developed taking this inherent difficulty iilto account. The validation was performed by testing against 30 jobs from the API database, selected based on data completeness.With this simulator, temperature prediction has been considerably improved over the API method. The standard deviation, maximum overestimation and maximum underestimation have been reduced on the thirty API jobs.This model applies equally well to onshore and offshore,vertical and deviated wells, and takes into account other variables that affect temperatures while cementing.
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