Summary
In this paper, we present a method of modeling surge pressures and wave propagation that can occur during well execution. The surge pressures have an effect on formations [i.e., formation fracture resulting in mud losses and nonproductive time (NPT)]. Knowing the amplitude of surge pressure in advance can lead to operation redesign to avoid losses. Swab- and surge-pressure waves can occur at numerous events during well execution. For example, during liner operations, pressure waves can occur at dart landing or plug shearing, liner-hanger setting, or clearing a plugged shoe-track component. It is possible for surge-pressure waves to create fractures in shale and sand layers (i.e., when surge-pressure-wave amplitude exceeds formation fracturing resistance).
A transient-state physical model is built to compute pressure-wave propagation through drillstring, casing, and open hole to predict the amplitude of a surge-pressure wave and to warn when a fracture might occur in the formation, to avoid mud losses and NPT.
In the model, continuity and energy partial-differential equations (PDEs) are built for a cylindrical fluid element contained in an elastic hollow cylinder. The method of characteristics is applied to convert the PDEs to ordinary-differential equations (ODEs). The ODEs are solved numerically to compute pressure distribution along well depth and in time. The model is implemented as a graphical-user-interface (GUI) tool to be used by drilling engineers at the design phase of a well to avoid losses. The GUI tool is targeted to address different scenarios that take place during the cementation process. To date, the transient-state physical model has been applied successfully in various applications, such as monodiameter technology, running casing, and perforating operations. Two cases are studied, one for a well in the Gulf of Mexico (GOM) where mud losses have been reported, and the other for a well in Malaysia where no mud losses have occurred. Pressure-wave computations are performed with the GUI tool for the two cases. The results of both cases are presented in this paper and show that formation fracture can be predicted by the GUI tool and subsequent losses can be avoided.
