Microseismic monitoring of hydraulic fractures is the process of monitoring the small earthquakes induced by fluid injection during hydraulic fracture stimulation. The primary goal of microseismic monitoring is to map the source positions of microseismic events. However, in actual cases, location of the microseismic events could become problematic because a considerable part of the microseismic events show a low signal-to-noise ratio (SNR) and conventional event detection and location techniques tend to omit these events even though they may provide useful information for delineation of the hydraulic fractures. To address this problem, several improved methods are proposed in this study to increase the detectability and location accuracy of microseismic events with low signal-to-noise ratios.It has been well known that microseismic data processing generally composes of several critical steps, such as event detection, arrival picking, velocity modeling and source location. As for the event detection process, we develop a multi-channel semblance coefficient based method to identify the low SNR microseismic events. Our method utilizes a semblance coefficient to quantitatively determine the waveform similarity of windowed record segments after moveout correction, and uses it as a detector of the presence of a microseismic event. After identifying the events, a robust method is employed to pick their P-and S-wave arrival times. This method, referred to as SLPEA algorithm, is developed by integrating the differences in amplitude, polarization and statistic properties between seismic signal and ambient noise. Once the arrival times are gained, a simulated annealing (SA) based joint inversion algorithm is adopted to invert the velocity models and microseismic source positions. Innovations in this method include the use of a probability distribution function for determination of the source azimuth and a joint objective function for inversion of the velocity model and source position. The performance of the proposed methods is illustrated using field dataset recorded during an 11-stage hydraulic fracture treatment. 521 locatable microseismic events are detected from this dataset and nearly one third of them show a low signal-to-noise ratio. The source positions of these events are successfully gained through using the proposed methods, and analysis of the location results indicates that the low SNR microseismic events can reveal more details about the hydraulic fractures.

Due to its ability to degrade nitrogen oxides under ultraviolet, titanium dioxide has been applied in asphalt concrete to degrade automobile exhaust in recent years. To highlight the protection of road traffic environmental quality and mitigate automobile exhaust on human health, this study proposes combining titanium dioxide and active carbon into Sand-fog seal to form a pavement coating material with a photocatalytic function. It uses active carbon to reinforce the material’s function, and the coupling agent for modification makes it well dispersed in the Sand-fog seal. The indoor experiments were carried out at 30 °C and relative humidity of 30%. It tested the composite material’s degradation efficiency on nitrogen dioxide in relation to component proportions, coupling agents, and dosages. The study concluded that the optimal photocatalytic efficiency could be achieved when the ratio of active carbon to titanium dioxide is 0.6. After being modified by the titanate coupling agent and through Scanning Electron Microscope tests, it can be seen that materials can be well dispersed into the Sand-fog seal. When the composite material accounts for 10% of the fog seal, it can achieve the optimal photocatalytic efficiency of about 23.9%. The British pendulum tests show it has good skid resistance performance. Half a kilometer of concrete roadway was sprayed with the material coating in Tianjin, China. The photocatalytic experimental road degrades nitrogen oxides better than the original road. The method is feasible for practical implementation.

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