The application discloses an AI real-time microseism monitoring node, which includes a processor and a data acquisition device, an AI calculation device, and a communication device connected to the processor, wherein the AI calculation device is provided with pre-trained microseism data analysis Device, and the processor is configured to perform the following operations: controlling the data acquisition equipment to acquire microseism data; turning on the AI calculation device to calculate the acquired microseism data by means of the microseism data analysis device to determine the valid event data associated with the microseism; and sending the valid event data to the remote data center through the communication device.

A network of motion sensors employs sensitive accelerometers to issue time-domain measurements of building movement from multiple locations within and between buildings and other structures. The time-domain measurements from the various motion sensors are synchronized and converted into frequency-domain measurements of building movement. Individual motion sensors can be equipped with the requisite processor and memory to synchronize and covert the time-domain measurements. The motions sensors can classify detected events into various event types, such as earthquakes, wind events, or bipedal locomotion. The sensors can also communicate with one another or other resources to calculate event probabilities. A motion sensor may, for example, receive an earthquake-verification signal responsive to an earthquake-verification request. The network of motion sensors can calculate local soil stiffness and financial loss estimations responsive to their individual or collective frequency-domain measurements.

A seismic warning system comprises: a plurality of sensors, each sensor sensitive to a physical phenomenon associated with seismic events and operative to output an electronic signal representative of the sensed physical phenomenon; a data acquisition unit communicatively coupled to receive the electronic signal from each of the plurality of sensors, the data acquisition unit comprising a processor configured to estimate characteristics of a seismic event based on the electronic signal associated with a P-wave from each of the plurality of sensors; and a local device communicatively coupled to the data acquisition unit. The plurality of sensors, the data acquisition unit and the local device are local to one another.

An ultrasonic sensor includes a transmission unit that is disposed on a first axis which is inclined with respect to a normal line of a surface of an object, a reception unit that is provided on a side opposite to the transmission unit of the object, on the first axis, and a transmission control unit that controls drive of the transmission unit. The transmission unit includes a plurality of transmission elements that transmit ultrasonic waves, and the plurality of transmission elements are arranged in a first direction that intersects the first axis in a plane including the normal line and the first axis. The transmission control unit delay-drives the plurality of transmission elements to align a direction of the ultrasonic wave that is transmitted from the transmission unit with the first axis.

A method of determining fracture complexity may comprise receiving one or more signal inputs from a fracturing operation, calculating an observed fracture growth rate based at least partially on the one or more signal inputs, calculating a predicted fracture growth rate, determining a fracture complexity value, and applying a control technique to make adjustments a hydraulic stimulation operation based at least in part on the fracture complexity value. Also provided is a system for determining a fracture complexity for a hydraulic fracturing operation may comprise a hydraulic fracturing system, a sensor unit to receive one or more signal inputs, a calculating unit, a fracture complexity unit, and a controller unit to apply a control technique to adjust one or more hydraulic stimulation parameters on the hydraulic fracturing system.

The present disclosure relates to a fracturing system comprising a functional unit, an electricity supply unit and an energy storage unit. The functional unit is configured to perform procedures of fracturing operations. The electricity supply unit is electrically connected with the functional unit and is configured to supply electrical energy to the functional unit. The energy storage unit is respectively electrically connected with the electricity supply unit and the functional unit, and is configured to store electrical energy from the electricity supply unit and supply electrical energy to the functional unit. According to the present disclosure, the energy storage unit of the fracturing system can store surplus electrical energy of the electricity supply unit and supply electrical energy to the whole fracturing system when needed, playing a role of energy storage as well as peak shaving so that the generator set and the like can maintain economic working condition for a long time, thus the system can be safe, stable, and achieve improved efficiency and economy. In addition, it is possible to generate electricity from non-carbon sources for fracturing operations and minimizes the use of internal combustion engines, which is more environment-friendly. The present disclosure can also reduce the number of generator sets and the space occupied by the generator sets so as to reduce the construction cost of fracturing operations.

Seismic data from seismic exploration surveys are mapped into a hypercube of bins or voxels in a four-dimensional space (X, Y, Offset, and Azimuth) according to Common Mid-Point (or CMP) between source and receivers. The mapped data from individual voxels or bins is then analyzed by multimodal statistics. Robust estimates of first break picks are obtained from the analysis. The first break picks are then used to as seed inputs for autopicking iteration, which proceeds to convergence. Estimates of confidence levels in the data are provided for re-picking to reduce computer processing time in successive autopicking iterations. Analysis is provided of different seismic attributes such as azimuthal velocity variations indicative of anisotropy, positioning errors of sources/receivers, geometry errors, and three dimensional distribution of inversion residuals. Analysis is also performed of standard deviation of the travel time data useful for estimating data errors in the inversion covariance matrix.

The invention provides a method of detecting a seismic event, which comprises acquiring (110) a digital signal x characteristic of a signal measured by at least one seismic sensor, and calculating (130) a time-frequency distribution for at least one section of a given duration of said signal, in a given frequency band. For each frequency of said frequency band, the calculated time-frequency distribution is normalized. The method also comprises calculating (150) the moving average of the normalized time-frequency distribution ZD, in said frequency band and in a time window, given reference L, centered on the time n; and detecting (160) a seismic event when the average exceeds a predefined threshold value. The invention also provides a corresponding detection system.

A method of characterizing a subterranean geologic formation's response to hydraulic fracturing is presented. The method includes acquiring data representing a plurality of seismic events caused by hydraulic fracturing of the subterranean geologic formation, determining, by at least one electronic processor, a plurality of seismic event moment magnitudes for respective seismic events in the plurality of seismic events, estimating, by at least one electronic processor, a first parameter representing a negative slope of a line relating seismic event frequency to seismic event magnitude for at least some of the plurality of seismic events, estimating, by at least one electronic processor, a second parameter representing an axis intercept of the line, and characterizing the subterranean geologic formation based at least in part on the first parameter and the second parameter

A data acquisition program, which includes core, image log, microseismic, DAS, DTS, and pressure data, is described. This program can be used in conjunction with a variety of techniques to accurately monitor and conduct well stimulation.