Temperature measured from a permanent downhole gauge in a well after the well shut-in provides a unique perspective for surveillance and production management purposes. For example, in deepwater environment, production engineers need to know the temperature status of a shut-in well before it is being restarted since different temperature profiles along the wellbore may need very different restarting strategies for flowing assurance purposes. A number of "rule-of-thumb" or complicated numerical simulations are either not reliable or impractical. This paper presents a semi-analytical model to estimate the temperature transient behavior after the well shut-in. The model is solved numerically through inverse Laplace transform and integration. This solution gives temperature distribution profile and history in any location along the radial direction for a given production time and shut-in duration. To make it more general for other wells, an empirical correlation is provided through regression on the calculated type curves. The difference between this semi-analytical solution with other previous efforts will be discussed. The applications of the solution to this model are multiple folders. For example, we can use the solution to predict the temperature behavior after the well shut-in, which can be used for flow assurance purposes. Furthermore, matching the calculated temperature with the measured temperature at the same location will yield the well local heat transmissibility coefficient. Some field examples are provided to demonstrate these applications.

The electric heating process for lifting heavy oil has been widely applied. However, research on its temperature field laws mostly focuses on onshore heavy oil wells, while research offshore is limited. Therefore, based on the energy conservation equation and heat transfer theory, a transient one-dimensional wellbore temperature model coupled with the temperature and viscosity of heavy oil and considering the effect of time was developed. In order to verify the accuracy of the model, the results of the previous model were used for comparison with the present model, and the results showed that the model has good accuracy. The results show that a reasonable selection of the process parameters of electric heating can increase the production of heavy oil while saving development costs and improving the economic benefits of the oilfield. The conclusions and recommendations of this paper can provide a theoretical basis and guiding suggestions for the optimal design of process parameters for lifting heavy oil using an offshore electric heating process.