Similar to a web search engine, we have developed a microseismic search engine that can estimate an event location and the focal mechanism in less than a second to monitor the hydraulic fracturing process. The method was extended from a real-time earthquake monitoring approach for seismological applications. We first calculate the full waveforms of all possible microseismic events over a 3D grid with a known velocity model for a given acquisition geometry to create a database. We then index and rank all of the seismic waveforms in the database by following the characteristics of the phase and amplitude of the waveform through a computer fast search technology, specifically, the multiple randomized k-dimensional tree method. When a microseismic event occurs, the approximate best matches to the entry waveform are found immediately by comparing the characteristic features between the input data and the database. The method returns not just one but a series of solutions, similar to a web search engine. Thus, we can obtain a solution space that delineates the resolution and confidence level of the results. Also similar to a web search engine, the microseismic search engine does not require any input parameter or processing experience; thus, the solutions are the same for any user. Numerical tests suggest that the waveform search approach is insensitive to random and correlated noises. However, if the correlation values between the input data and best matches in the database are too low, suggesting unreliable results, the solution may be rejected automatically by applying a preset threshold. We have applied the method to real data, and found great potential for the routine real-time monitoring of microseismic events during hydraulic fracturing.
Understanding how people interact with web search results that change in real-time using implicit feedback
