Seismicity dataset of Ghana obtained by Deep Learning

This data repository presents waveforms, earthquake bulletin, and supporting data for a set of detected earthquakes on the Ghana Digital Seismic Network (GHDSN), consisting of 6 broadband sensors deployed in southern Ghana from 2012 to 2014.
The earthquakes and their corresponding P and S arrival phases were detected using the EQTransformer tool, a Deep Learning model for simultaneous earthquake detection and phase picking.
The data set comprises waveforms of 73 detected local earthquakes and a bulletin of 559 arrival times (292 P and 267 S phases) in SEISAN format.
Additionally, some preliminary results of processing this earthquake data are presented:
1) An accurate, updated crustal velocity model for the region obtained by performing a joint inversion on the hypocentral parameters and Vp and Vp/Vs for a 6-layers model,
2) 3D live figures graphically representing the hypocentral parameters of the detected earthquakes and active zones in this period,
3) an occurrence time sequence for the detected events, and 4) some statistical information of the earthquakes detected.
This dataset is essential as it provides researchers interested in further processing the waveform of the detected events to derive more detailed information about the mechanism of the seismogenic sources and active faults in the area.

本数据集仓库提供了加纳数字地震台网（Ghana Digital Seismic Network, GHDSN）所识别到的一系列地震的波形数据、地震目录与辅助数据集。该台网由6台宽频带传感器组成，于2012年至2014年间部署在加纳南部地区。
本次识别的地震及其对应的P波、S波到时震相，均通过EQTransformer工具完成——该工具是一款可同时实现地震检测与震相拾取的深度学习模型。
本数据集包含73个已识别本地地震的波形数据，以及一份采用SEISAN格式编制的震相到时表，共收录559条到时记录（其中P波震相292条，S波震相267条）。
此外，本数据集还附带了本次地震数据的部分初步处理成果：
1. 针对该区域构建的高精度更新版地壳速度模型：通过对6层地壳模型的震源参数、纵波速度（Vp）以及波速比（Vp/Vs）开展联合反演得到；
2. 可直观展示本次识别地震的震源参数与该时段活动构造带分布的交互式三维可视化图件；
3. 本次识别地震的发震时间序列；
4. 本次识别地震的相关统计信息。
本数据集具有重要科研价值，可为希望对已识别地震波形开展进一步处理的研究人员提供支撑，以获取该区域震源机制与活动断裂带的更为详细的相关信息。