Evolution of gas kick and overflow in wellbore and formation pressure inversion method under the condition of failure in well shut-in during a blowout

With ongoing development of oil exploration and techniques,there is a significant need for improved well control strategies and formation pressure prediction methods.In this paper,a gas-liquid transient drift flow model was established according to the gas-liquid two-phase flow characteristics during the gas kick.A Roe scheme was used for numerical calculation based on the finite volume method.The changes of bottom-hole pressure,casing pressure,the development law of cross-sectional gas holdup,and gas velocity,along with the vertical well depth,were analyzed through simulation examples.The time-series characteristics of mud pit gain were obtained by adjusting the formation parameter.The complex nonlinear mapping relationship between the formation parameters and the mud pit gain was established.The long short-term memory network(LSTM)of deep learning was used to obtain a formation pressure inversion when the blowout is out of control and the well cannot be shut-in.Experimental data from a well were used to verify the gas-liquid two-phase transient drift flow model based on the finite volume method,demonstrating that this method is reliable,with greatly improved prediction accuracy.This approach provides theoretical support for the early monitoring of gas kick during drilling,and for well-killing design and construction after uncontrolled blowout.

A novel predictive model of drag coefficient and settling velocity of drill cuttings in non-Newtonian drilling fluids

In oil and gas well drilling operations,it is of great significance to accurately predict the drag coefficient and settling velocity of drill cuttings in non-Newtonian drilling fluids.In this paper,the free-falling of 172 groups of spheres and 522 groups of irregular-shaped sand particles in Newtonian/non-Newtonian fluids were investigated experimentally.It was found that the drag coefficient calculated based on Newtonian correlations can result in a significant error when the particle settles in the non-Newtonian fluid.Therefore,predictive models of drag coefficient were established respectively for different types of fluids.The validity of the proposed drag coefficient model of spheres was verified by comparing it with the previous works.On this basis,the drag coefficient model of irregular-shaped sand particles was established by introducing a shape factor.The models do not use the shape factor that requires detailed threedimensional shape and size information.Instead,two-dimensional geometric information(circularity)is obtained via image analysis techniques.The present new models predict the settling velocity of sand particles in the power-law fluid and Herschel-Bulkley fluid accurately with a mean relative error of5.03%and 6.74%,respectively,which verifies the accuracy of the model.