• Experiences in Data Analysis: Differentiating bad from good data.
• Alternative Uses of Microseismic Signals: Case studies of methods to use waveforms used either to characterize source or path.
• Data Standards: Quantification of errors and evaluation techniques.
• Machine Learning in Microseismic: How can it help in areas such as event identification, picking, and interpretation?
• Fiber-Optic Data: Challenges and solutions for single component microseismic strain signal.
• Full-Waveform Modelling: Pitfalls, limitations and advantages of forward modelling of waveforms