Development of Buried Sensor for Mobile Ocean Bottom Broadband Seismic Observation of the Next Generation

自1999年以来，我国研制了移动宽带海底地震仪（BBOBS），并在西北太平洋和法属波利尼西亚海进行了多次实际观测。但是，通过对地震资料的评价，数据分析中重要的水平分量的长周期噪声级平均较高，且随时间的变化也较大。假设这种高噪声水平的原因是由于底部电流随时间变化导致大壳体球体的倾斜变化很小。为了解决这一问题，在没有倾斜变化的情况下进行观测的一个想法是使用能够侵入沉积物的小型和低轮廓宽带传感器。现在，我们开发了下一代BBOBS的原型（BBOBS- nx）。2008年6月，我们在R/V Kairei （JAMSTEC）与ROV Kaiko 7000II巡航期间迈出了第一步。在ROV的支持下，对上述降噪方案的降噪效果进行了实际测试。BBOBS- nx的原型安装在ROV上，位于2007年已经部署的BBOBS附近。将bbbs - nx的传感器单元与记录单元分离，并将传感器推入沉积物中。在ROV潜入之前，OBDC已经被放下，并被转移到它们附近。从BBOBS到BBOBS- nx的距离约为10米。我们将在几个月后恢复这些仪器，以获得足够的数据长度来正确评估

Since 1999, we have already developed the mobile broadband ocean bottom seismometer (BBOBS), and many practical observations in the northwestern Pacific Ocean and French Polynesian Sea have been conducted. But, through the evaluation of the seismic data, the noise level of horizontal components in long periods, those are important in data analyses, is rather high in average and its variation in time is also large. The reason of this high noise level is assumed as the small tilt variation of the large housing sphere due to a bottom current with time variation. To clear this problem, one idea of observation without the tilt variation is the use of small and low profile broadband sensor that enables to intrude into the sediment. Now, we developed a prototype of this next generation BBOBS (BBOBS-NX). In June 2008, we made a first step for it during the cruise of the R/V Kairei (JAMSTEC) with the ROV, Kaiko 7000II. It is a practical test to know achievement of the noise reduction with the idea above under support of the ROV. The prototype of BBOBS-NX was loaded on the ROV, and was located nearby the BBOBS that has already deployed in 2007. The sensor unit of BBOBS-NX was separated from the recording unit, and the sensor was pushed into the sediment. The OBDC had been dropped before the dive of the ROV, and was moved to nearby of them. The distance from the BBOBS to the BBOBS-NX is about 10m. We will recover these instruments several months later to get enough length of data to evaluate correcty