The recognition of submarine cable magnetic anomaly (SCMA) signals is a challenging task in magnetic signal data processing. In this study, a multi-task convolutional neural network (MTCNN) model is proposed to simultaneously recognize abnormal signals and locate abnormal regions. The residual block is added to the shared feature backbone to improve the ability of the network to extract high-level features and maintain the gradient stability of the model in the training process. The long short-term memory (LSTM) block is added to the classification branch task to learn the internal relationship of the magnetic anomaly time series, so as to improve the network’s ability to recognize magnetic anomalies. Our proposed model can accurately recognize the SCMA signals collected in the East China Sea and the South China Sea. The classification accuracy and the ability to locate the abnormal regions are close to the manual labeling of human analysts. The newly developed model can help analysts reduce the probability of missing and misjudging submarine cable magnetic anomalies, improve the efficiency and accuracy of interpretation, and could even be deployed to an unmanned platform to realize the automatic detection of SCMAs.

The Central Red Sea Rift is a natural laboratory to study the transition from rifting to spreading. Based on new reflection seismic profiles and gravity modeling, we examined the crustal structure, tectonic evolution, breakup mechanism, and future evolution of the Central Red Sea Rift. Along this rift axis, the breakup of continental lithosphere is discontinuous and the oceanic crust is limited to the axial deeps. The punctiform breakup and formation of deeps is assisted by mantle upwelling and topographic uplift, but the nucleation is directly controlled by the normal-fault system. The discontinuities spaced between axial deeps within the relatively continuous central troughs are presently axial domes or highs and will evolve into new deeps with tectonic subsidence. Isolated deeps will grow and connect with each other to become a continuous central trough, before transitioning into a unified spreading center.