Mining Project: Advanced Mining Seismicity Processing

Principal Investigator	Derrick Chambers - Request information
Start Date	10/1/2016
Objective	To refine and apply advanced event detection, location, and magnitude estimation methods that can be used to increase seismic catalog quality; and to quantify the strengths and weaknesses of each method and, based on the case studies conducted, identify features that are likely to contribute to the success or failure of each for monitoring mining-induced seismicity.
Topic Area	Ground Monitoring

Research Summary

Many mines produce seismic events as the ground responds to the extraction process. For these mines, monitoring seismicity can provide useful insights into mine design performance and help to identify and manage potential ground control hazards. However, the equipment, processing expertise, and software needed to monitor and locate mining-induced seismicity (MIS) can be prohibitively expensive. If the cost of monitoring MIS could be reduced, many more mines could have access to information that, when taken in the appropriate mechanical and geological contexts, can have a significant impact on worker safety.

Although many different types of seismic data can be useful (such as phase identification and polarity, moment tensors, source-time functions, waveform characteristics, etc.) the most widely used and easiest to understand is an event catalog. A catalog, at a minimum, is a list of seismic events with their corresponding calculated origin times, locations, and magnitudes. In order to produce a catalog, instruments must record the seismic energy radiated from the events. A group of instruments designed to record such energy is referred to as a network. In the context of this project, seismic networks that can monitor mining seismicity are divided into three classes:

• Class 1: Typically an in-mine system with sensor spacing between 10 m to 500 m. Such a system is expensive to install and maintain and only a few companies in the world offer the service. Because the sensors are densely spaced and usually close to the seismic sources, the quality of seismic catalog produced by a class 1 network is optimal.
• Class 2: A surface array above or around the mine. Typical sensor spacing is between 0.5 km and 10 km. Installation and maintenance of a class 2 network is much cheaper than a class 1 network, but produces a lower-quality catalog.
• Class 3: A regional network with typical station spacing between 10 km and 100 km. Such a network is usually operated and maintained by a government agency or university. In the United States, the data from class 3 networks are almost always available to the public, free of charge. A class 3 network produces the lowest-quality catalog, often only detecting relatively high-magnitude events with location errors of a few kilometers.

This project will focus on improving seismic catalog quality by applying and refining advanced data processing methods used in regional and global seismology that are not commonly used in mining seismicity processing. The application of such methodologies may allow mine operators to produce a catalog of a given quality with lower operational and instrumentation costs. Improving the quality of seismic data collected at mines will allow more mines to utilize the information in order to aid in assessing mine design performance and identifying potential geological hazards.

Determining if seismic catalog quality has been improved is difficult without independent knowledge of the seismicity. For this reason, mines monitored by two classes of networks will be invited to participate in the pilot phase of this project. Advanced techniques will be applied to the higher class network (which typically produces lower-quality catalogs) and the results will be compared to those obtained with traditional processing methods on the lower class network (which typically produces higher-quality catalogs). The advanced methods can then be “tuned” to reduce the differences between the lower class catalog and the higher class catalog. Doing so will allow recommendations for software for monitoring MIS on class 2 and class 3 networks to be developed in order to help mines perform these analyses. These results will also likely be translatable to a class 1 network.

The key activities of this project include soliciting mine participation, performing temporary deployments, developing or adapting software for data processing, and evaluating the geophysical methods. Finally, the feasibility of employing the methodologies in a real-time system will be assessed. If a real-time system is feasible, it will be recommended that the project be extended. The development and testing of a user-friendly real-time monitoring system will be the principal goal of the follow-on work.

---