This disclosure presents systems, methods, and apparatus for determining cluster efficiency during hydraulic fracturing, the method comprising: measuring acoustic vibrations in fracking fluid in a fracking wellhead, circulating fluid line, or standpipe of a well; converting the acoustic vibrations into an electrical signal in a time domain; recording the electrical signal to memory; analyzing the electrical signal in the time domain for a window of time and identifying two amplitude peaks corresponding to a fracture initiation; measuring a time between the two amplitude peaks; dividing the time by two to give a result; multiplying the result by a speed of sound in the fracking fluid to give a distance between the fracture initiation and a plug at an end of a current fracking stage of the well; and returning a location of the fracture initiation to an operator based on the distance between the fracture initiation and the plug.

Disclosed herein are earthquake detection devices capable of initiating a safety response in the event of an earthquake. The earthquake detection devices comprise a plurality of three-component accelerometers for measuring acceleration in three directions; and a processing unit for: receiving acceleration measurements from each of the plurality of accelerometers, determining if the acceleration measurements meet or exceed a predetermined threshold value and sending a signal to one or more transducers.

The invention discloses a method for exploring passive source seismic frequency resonance, which includes the following steps: Step 1: collecting, with a detector, a response signal of underground medium to form seismic time series data; Step 2, transforming the data collected in step 1 into frequency domain data, via Fourier transformation; Step 3, performing frequency domain superposition on the data at a same detection point processed through step 2, to form frequency domain amplitude superposition data; Step 4, converting, through a correction with a standard well parameter, frequency domain data processed through step 3 into depth data; Step 5, processing the data obtained in step 4 to obtain imaging data Image.sub.(d), where the imaging data Image.sub.(d) is apparent wave impedance ratio or apparent wave impedance changing as depth. The method can perform spatial and attribute imaging of the underground medium by using the seismic wave resonance principle.

A method of identifying hydrocarbon production information is disclosed. In in a first hydrocarbon management environment, a first audio signal is detected and a characteristic acoustic fingerprint is identified therefrom. The fingerprint is stored in a memory, along with identifying information associated with the first signal. A second audio signal is detected and a characteristic acoustic fingerprint is identified therefrom. The fingerprints are compared, and if the fingerprints match the identifying information of the first audio signal is assigned to the second audio signal. A notification regarding the matching of the characteristic acoustic fingerprints of the first and second audio signals is issued.

This disclosure presents systems, methods, and apparatus for determining cluster efficiency during hydraulic fracturing, the method comprising: measuring acoustic vibrations in fracking fluid in a fracking wellhead, circulating fluid line, or standpipe of a well; converting the acoustic vibrations into an electrical signal in a time domain; recording the electrical signal to memory; analyzing the electrical signal in the time domain for a window of time and identifying two amplitude peaks corresponding to a fracture initiation; measuring a time between the two amplitude peaks; dividing the time by two to give a result; multiplying the result by a speed of sound in the fracking fluid to give a distance between the fracture initiation and a plug at an end of a current fracking stage of the well; and returning a location of the fracture initiation to an operator based on the distance between the fracture initiation and the plug.

A method includes receiving over a network from one or more seismic sensors a data set characterizing a seismic event generating a seismic wave. Based on the data set, a time of arrival and intensity of the seismic wave at a predetermined location is calculated. The predetermined location has one or more mitigation devices. Whether the intensity of the seismic wave exceeds a predetermined seismic intensity threshold is determined. If the intensity of the seismic wave exceeds the predetermined seismic intensity threshold, the one or more mitigation devices are activated.

A method is described for monitoring a stimulated reservoir volume (SRV) including receiving simulation parameters, performing 3D fully coupled quasi-static poro-elastic finite difference modeling using the simulation parameters, wherein the 3D fully coupled quasi-static poro-elastic finite difference modeling is based on a rescaling of solid rock and fluid flow density parameters and generates simulated temporal quasi-static stresses, and pore pressure. In addition, simulated stresses may be used for performing calculation of the 3D rotation of the simulated stresses to principal directions; performing calculation of the temporal 3D Mohr-Coulomb (MC) failure criteria from the calculated principal stresses and the simulated pore pressure for all or selected time steps; and displaying the computed temporal MC failure criteria results on a graphical display. The method may also be used in time-lapse monitoring of the reservoir for microseismic depletion delineation.

Disclosed is a method for analyzing and predicting a main fracture orientation of a mining face based on microseismic monitoring, including: collecting microseismic data generated by a coal rock burst; carrying out a hierarchical clustering on the microseismic data to obtain target hypocenter groups, of which the target hypocenter groups comprise several types of hypocenters; acquiring focal mechanism solutions of all the target hypocenter groups in the target hypocenter group, and acquiring a hypocenter azimuth and a hypocenter dip based on the focal mechanism solutions; and carrying out the hierarchical clustering on a hypocenter location, the hypocenter azimuth and the hypocenter dip, and predicting the main fracture orientation of the mining face.

The present invention is a method to determine an azimuthal orientation of a borehole seismometer sensor performed by a computing device using a control server having a database and an arithmetic function, the computing device performing a method to determine the azimuthal orientation of a borehole seismometer sensor using long-period surface waves in microseisms, including step S100 in which a data collection unit 100 collects continuous waveform data recorded by a borehole seismometer and a reference seismometer; step S200 in which a frequency band setting unit 200 sets a frequency band to be analyzed in the collected continuous waveform data; step S300 in which a filtering unit 300 performs bandpass filtering on the frequency band to be analyzed; step S400 in which a waveform dividing unit 400 divides seismic waveform into waveform segments with preset time units; step S500 in which a phase shift unit 500 shifts the phase of the divided vertical component waveforms by 90°; step S600 in which a waveform calculation unit 600 combines the divided N′ and E′ component seismic waveforms to calculate horizontal components for rotation angles waveform between 0 and 360° from the N′ orientation; step S700 in which a correlation calculation unit 700 calculates a correlation coefficient between the horizontal and vertical component waveforms; step S800 in which a Rayleigh wave orientation determination unit 800 repeats steps S500 to S700 for each divided time domain; step S900 in which an orientation comparison unit 900 performs steps S400 to S800, respectively, with respect to the borehole seismometer data for which the sensor orientation is to be determined and the reference seismometer data for which the sensor orientation is already known; and step S1000 in which a result calculation unit 1000 averages θ determined for each time period to calculate a final result.

A method for improving a monitoring capability of a borehole-surface micro-seismic monitoring system includes selecting multiple candidate points for installing surface wireless sensors to form a natural-number-coded candidate point set and combining a fixed number of candidate points randomly selected from the candidate point set with an underground installed sensor set to form a borehole-surface micro-seismic monitoring network; carrying out multiple random selections until a certain scale of borehole-surface micro-seismic monitoring network deployment plans are generated; establishing an evaluation model for a monitoring capability of each borehole-surface micro-seismic monitoring network deployment plan according to a propagation relation equation between a micro-seismic energy and a first-arrival peak amplitude of a P-wave, forming an initial population; determining an optimal borehole-surface micro-seismic monitoring network deployment plan through a genetic algorithm; and determining an optimal surface wireless sensor deployment plan that significantly improves the monitoring capability of the borehole-surface micro-seismic monitoring network deployment plan.