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The existing artificial intelligence model uses single-point logging data as the eigenvalue to predict shear wave travel times (DTS), which does not consider the longitudinal continuity of logging data along the reservoir and lacks the multiwell data processing method. Low prediction accuracy of shear wave travel time affects the accuracy of elastic parameters and results in inaccurate sand production prediction. This paper establishes the shear wave prediction model based on the standardization, normalization, and depth correction of conventional logging data with five artificial intelligence methods (linear regression, random forest, support vector regression, XGBoost, and ANN). The adjacent data points in depth are used as machine learning eigenvalues to improve the practicability of interwell and the accuracy of single-well prediction. The results show that the model built with XGBoost using five points outperforms other models in predicting. The R2 of 0.994 and 0.964 are obtained for the training set and testing set, respectively. Every model considering reservoir vertical geological continuity predicts test set DTS with higher accuracy than single-point prediction. The developed model provides a tool to determine geomechanical parameters and give a preliminary suggestion on the possibility of sand production where shear wave travel times are not available. The implementation of the model provides an economic and reliable alternative for the oil and gas industry.

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Remote transmission of log data is an urgent problem for service companies. Remote transmission technology of log data here refers to both the transmission solution in combination with the CifNet multi-well data management system to automate the transmission, storage, management, and retrieval of log data to reduce turn-over time. It is an applied digital signature technology to implement breakpoint transmission and error recovery and ensure the effectiveness and reliability of log data transmission.

Noncontact measurement for rotational motion has advantages over the traditional method which measures rotational motion by means of installing some devices on the object, such as a rotary encoder. Cameras can be employed as remote monitoring or inspecting sensors to measure the angular velocity of a propeller because of their commonplace availability, simplicity, and potentially low cost. A defect of the measurement with cameras is to process the massive data generated by cameras. In order to reduce the collected data from the camera, a camera using ERS (electronic rolling shutter) is applied to measure angular velocities which are higher than the speed of the camera. The effect of rolling shutter can induce geometric distortion in the image, when the propeller rotates during capturing an image. In order to reveal the relationship between the angular velocity and the image distortion, a rotation model has been established. The proposed method was applied to measure the angular velocities of the two-blade propeller and the multiblade propeller. The experimental results showed that this method could detect the angular velocities which were higher than the camera speed, and the accuracy was acceptable.

In this paper, a dynamic model of an offshore drilling riser is developed based on the Hamilton principle. The developed dynamic model is transformed into a finite element model by introducing an approximate solution which chooses the Hermite cubic interpolation function of bending beam element as the shape function. Thereafter, the standard Newmark integration is applied to numerically simulate the dynamic responses of offshore drilling risers with varied system parameters, including the length of riser, top tension ratio, and buoyant factor. Based on the results of numerical simulation, under the influences of sea wind, sea current, and the periodic excitation of sea wave, the offshore drilling riser experiences a fast lateral deflection phase in the beginning, a reciprocating deflection phase in the following long duration, and then, a periodic oscillation when it reaches the dynamic stable condition, respectively. The riser system working in deeper water with a higher top tension ratio and a lower buoyant factor shows more controllable vibration and less lateral deflection.