Methods and systems including computer programs encoded on a computer storage medium, for utilizing equivalent linear velocity for first arrival picking of seismic refraction. In one aspect, a method includes receiving data for the shot gather record, generating a diving wave equation curve for a particular parameter pair of multiple parameter pairs, and integrating the shot gather record data corresponding to the diving wave equation curve over a selected range of offsets of the shot gather to generate an equivalent linear velocity value for the particular parameter pair and the shot gather record data, selecting, from the equivalent linear velocity values for the plurality of parameter pairs, a greatest equivalent linear velocity value of the equivalent linear velocity values, the greatest equivalent linear velocity value corresponding to a first-arrival parameter pair, and determining, using the first-arrival parameter pair, a set of first-arrival onsets for the selected sub-range of offsets.

A multi-wavefield seismic detection method and system based on construction noise of a shield machine. Multi-wavefield seismic information such as a body wave and a surface wave formed during propagation of a seismic wave generated by excitation in a stratum is obtained by using noise information caused by the construction of a shield machine as a seismic source, a stratum velocity model along a tunnel is constructed through joint inversion, and reflection wave information or the like is used for migration imaging, to eventually implement relatively accurate detection of a geological condition in front of a tunnel face of shield construction.

A method for determining microseismic events. The method may include measuring a seismic travel time of a microseismic event with a fiber optic line disposed in a first wellbore, forming a probability density function for the microseismic event based at least in part on the seismic travel time measurement, modifying the probability density function by applying one or more constraints to form a modified probability density function, identifying one or more most probable source locations from the modified probability density function, and forming a microseismic event cloud from the one or more most probable source locations.

Embodiments of the present disclosure provide a method and system for recognizing a mine microseismic event, and belong to the field of mine data processing. The method includes: converting historical microseismic data monitored by a mine microseismic monitoring system into a microseismic waveform image, and then, converting the microseismic waveform image into a four-neighborhood microseismic waveform graph structure; performing area defining on the microseismic waveform graph structure, and extracting a similar feature layer of any node in the microseismic waveform graph structure based on the defined area; and taking the microseismic waveform image as an input layer of an improved convolutional neural network model, and sequentially connecting the input layer with the similar feature layer as well as a convolutional layer, a pooling layer, a fully connected layer and an output layer which are pre-configured for the improved convolutional neural network model to form a recognition model for recognizing the mine microseismic event. By using the recognition model designed in the present disclosure, the similar feature layer can be extracted, so that the mine microseismic event is effectively recognized.

A seismic monitoring system includes a plurality of seismic monitors and a processing device operatively coupled to the plurality of seismic monitors. The processing device receives recordings of waveforms of motion detected at the plurality of seismic detectors in a geographic area. The processing device applies the respective recordings to corresponding positions of the seismic detectors in a three-dimensional geological model that describes its elastic attributes and tests a plurality of moment tensors at a plurality of locations. Based on the testing, the processing device determines a globally convergent source location and moment tensor in the three-dimensional model based on the testing.

A method for determining and tracking an edge of first breaks is provided. The method includes obtaining seismic data associated with subsurface formations, the seismic data relating to a vibration contacting a plurality of portions of the subsurface formations, processing the seismic data to produce processed seismic data comprising one or more attributes, wherein the processed seismic data defines an edge characterizing a plurality of onset times, iteratively performing, using a level sets algorithm, a plurality of tracking operations on the processed seismic data to identify the edge characterizing a plurality of first breaks' onset times, and determining the edge as first breaks.

The present disclosure provides a physics-based and data-driven integrated method for rock burst hazard assessment, including the following steps: determining an initial stress concentration coefficient by conducting grid discretization on an assessment region, and assigning a value to each of grid nodes using a Weibull distribution function; obtaining a stress concentration coefficient value of each grid node under physics-based models; introducing seismic wave CT detection data to obtain stress concentration coefficient distribution in the assessment region under the integration of a seismic wave CT detection and its derived characterization stress model; introducing microseismic data to obtain stress concentration coefficient distribution in the assessment region under the integration of a microseismic damage reconstruction stress model; and assessing the degree of rock burst hazard according to the size of the stress concentration coefficient value.

A method for monitoring precipitation of magnetospheric particles includes detecting charged magnetospheric particles by a particles detector, processing the detection data to associate a respective estimate or measurement of kinetic energy with the detected magnetospheric particles, obtaining a first count value N.sub.H associated with a relatively higher estimate or measurement of kinetic energy, obtaining a second count value N.sub.L associated with a relatively lower estimate or measurement of kinetic energy, detecting a relative variation of the second count value N.sub.L with respect to the first count value N.sub.H, determining that an impulsive event of precipitation of charged magnetospheric particles (MPP event) in the magnetosphere occurred, assigning to the MPP event geomagnetic longitude and time, defining one or more groups of MPP events occurred in a time range at a same geomagnetic longitude, and identifying a group of MPP events indicative of an activity of terrestrial origin.

A method for monitoring hydraulic fracturing range of a surface vertical shaft is provided by the present disclosure, belonging to the technical field of ultrahigh-pressure hydraulic fracturing monitoring of the coal mine vertical shafts. The method comprises the following steps: connecting, by an eight-thread communication cable, a high-precision portable micro-seismic monitoring acquisition instrument to a high-sensitivity deep hole sensor, and performing uphole-crosshole-downhole monitoring simultaneously, specifically as follows: providing uphole-crosshole-downhole monitoring holes respectively, and installing deep hole geophones in the monitoring holes; then laying communication cables uphole-crosshole-downhole to connect the geophones to the portable high-precision micro-seismic acquisition instrument respectively; then performing high-precision positioning on the fissure development range by monitoring recorded events and time, thus determining the directions and ranges of a main fracture and secondary induced fractures of hydraulic fractures.

A method of detecting an event by: obtaining a first sample data set; determining a frequency domain feature(s) of the first sample data set over a first time period; determining a first threshold for the a frequency domain feature(s) using the first sample data set; determining that the frequency domain feature(s) matches the first threshold; determining the presence of an event during the first time period based on determining that the frequency domain feature(s) matches the first threshold; obtaining a second sample data set; determining a frequency domain feature(s) of the second sample data set over a second time period; determining a second threshold for the frequency domain feature(s) using the second sample data set; determining that the frequency domain feature(s) matches the second threshold; and determining the presence of the event during the second time period based on determining that the frequency domain feature(s) matches the second threshold.