1. What are the contributions in "Microseismic event location using global optimization algorithms: an integrated and automated workflow" ?
The authors perform the location of microseismic events generated in hydraulic fracturing monitoring scenarios using two global optimization techniques: Very Fast Simulated Annealing ( VFSA ) and Particle Swarm Optimization ( PSO ), and compare them against the classical grid search ( GS ).. To this end, the authors present an integrated and optimized workflow that concatenates into an automated bash script the different steps that lead to the microseismic events location from raw 3C data.. Secondly, the authors estimate their corresponding backazimuths using polarization information, and propose a simple energy-based criterion to automatically decide which is the most reliable estimate.. Finally, after taking proper care of the size of the search space using the backazimuth information, the authors perform the location using the aforementioned algorithms for 2D and 3D usual scenarios of hydraulic fracturing processes.. The authors assess the impact of restricting the search space and show the advantages of using either VFSA or PSO over GS to attain significant speed-ups.
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2. What future works have the authors mentioned in the paper "Microseismic event location using global optimization algorithms: an integrated and automated workflow" ?
In the 2D location scenario, the authors searched for two coordinates only, since the backazimuth information that they obtained automatically in a previous step, allowed us to limit the search space to a plane containing the source and the receivers array.. For this case, the authors devised a strategy to restrict the search space based on the backazimuth estimates obtained from two monitoring wells, and showed that this leads to a significant speed-up of calculations.. On the other hand, the authors showed that the proposed energy-based criterion can be used to automatically make the decision whether to use the Por S-wave backazimuth estimates, an important choice for reliability purposes.. The authors believe that these speedups, together with those obtained by restricting the search space and the energy-based criteria used to select the most reliable backazimuth estimates, might represent a key factor when processing large volumes of data.
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