Blowout is one of the most serious safety threats in deepwater drilling. Considering the characteristics of gas invasion in complex formations, gas migration and distribution, and dynamic changes in temperature inside a wellbore, a deepwater well-closing pressure determination method considering thermal-fluid-solid coupling was proposed. The model was verified using actual data, and the average error in the increase in casing pressure during the closing process was found to be 5.42%. The shut-in pressure of oil and gas wells under a transient shut-in process was analyzed. The results showed that the fluid thermal expansion caused by temperature recovery had a significant impact on the change in wellhead backpressure after well closure. Furthermore, the time required for the wellbore pressure to recover to the formation pressure varies nonlinearly with factors such as geothermal gradients, pit gains, bottom-hole pressure, and gas production indices. A pressure calculation chart was developed for deepwater drilling. The shut-in time for deepwater drilling should not be less than 15 min, and in cases where the gas production index is small and the bottomhole pressure difference is large, the shut-in time should exceed 90 min. The results can provide theoretical guidance and technical support for well shut-in processes during deepwater drilling.

Accurately estimating the gas-flow rate at a wellhead to invert the formation pressure and production capacity information can be the basis for subsequent well-killing parameter design following oil and gas-well drilling blowout and ignition. Based on the multicomponent characteristics of the blowout gas and the turbulence intensity of the blowout flame, as well as the effects of complex factors such as environmental wind direction, wind speed, and wellhead structure, a numerical model for actual drilling blowout ignition is established. Jet-flame experiments are conducted under blowout conditions to verify the accuracy of the model. The temperature and radiation fields and flame morphologies of the well jet flow flame under different lateral wind speeds, well jet flow rates, and wellhead diameters are analyzed. Previous studies have found that as the lateral wind speed increases, the maximum temperature and maximum thermal radiation intensity of the blowout flame first decrease and then increase. However, as the amount of well jet increases, although the flame influence area increases, the maximum temperature does not increase significantly, and the maximum thermal radiation intensity actually decreases. Based on experimental and numerical simulation datasets, a high-yield gas-well jet volume prediction method based on the flame height and thermal radiation intensity of the well jet flow is constructed, which has important engineering application value for achieving successful well killing following well jet ignition.

Rate of penetration (ROP) depends on interacting drilling conditions and formation properties, making prediction from sequential measurements challenging. This study develops a framework combining a temporal convolutional network (TCN), long short-term memory (LSTM), and attention for ROP prediction using logging data from the offshore BY area in China. Convolutional encoding and recurrent integration represent historical drilling sequences, while attention adaptively aggregates their hidden states. In the primary four-model comparison on a held-out depth interval, the framework achieves R² = 0.9093 and MAE = 0.8981, against 0.7474, 0.7737, and 0.7915 for LSTM, TCN, and TCN–LSTM. Configuration selection is separated from testing. The controlled comparisons needed to attribute this difference to individual components, to uniform aggregation, or to model capacity have not been completed, and the reported difference is, therefore, described as an observed comparison rather than as an established component effect. Attention weights characterize internal aggregation and are not interpreted as direct evidence of lithological change or pressure event recognition. Generalization to independent wells and practical deployment require further validation.