Abstract: A method for preparing heat-conductive cement slurry for well cementation includes the following steps: S1, uniformly mixing sodium 1-butanesulfonate, sodium dodecyl diphenyl ether disulfonate and polyvinylpyrrolidone to obtain an admixture; S2, dissolving the admixture in deionized water and stirring to obtain a dispersant solution; S3, adding graphite to the dispersant solution and stirring to obtain a graphite dispersion; S4, stirring cement and deionized water in a slurry cup to obtain cement slurry; and S5, mixing and stirring the graphite dispersion and the cement slurry to obtain the heat-conductive cement slurry. The heat-conductive cement slurry can effectively improve the heat conductivity coefficient of set cement, and significantly improve the heat conductivity of the set cement, and has a broad market application prospect.

Abstract: The present invention discloses an active intelligent wellbore pressure control system, which includes a ground multi-parameter online monitoring system (86), a rotary blowout preventer (1), a wellhead back pressure compensation manifold, an automatic plugging material filling device (62), a drilling device, an MPD intelligent control system (87), a remote monitoring and control system (88), and a high-precision hydraulic calculation system (105).

Abstract: A remote intelligent active drilling pressure control system and method. The system includes a drilling pump, a rotary blowout preventer, a ground simple throttle control manifold, a wellhead back pressure compensation manifold, a graded filling device, a downhole storage-type pressure measuring device, a ground multi-parameter online monitoring system, a drilling hydraulic calculation system, an MPD intelligent control platform and a remote monitoring and control system. The present invention provides a wellbore pressure control thought of “plugging and control integration”, improves the pressure resistance of a formation by circularly plugging while drilling, realizes active control of a wellbore pressure, effectively broadens a “drilling safety density window” of the formation, and reduces the requirements on the pressure control precision of a wellbore pressure control device.

Abstract: The present invention discloses an intelligent recognition method for while-drilling safety risks based on a convolutional neural network. The method includes the following steps: 1, processing while-drilling safety risk parameter features and data, and establishing a correlation analysis model for monitoring-while-drilling parameters by using a Pearson coefficient correlation analysis method; 2, processing while-drilling safety monitoring data, analyzing a time span of each sample, constructing training sample data and test sample data, and preprocessing the samples; 3, designing a while-drilling safety risk recognition network structure; and 4, recognizing while-drilling safety risks by the trained safety risk recognition network.