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 and device determine seismic wave information, and a computer readable storage medium implements a method for determining seismic wave information. According to the solution, the method includes determining shallow and deep geophones from top to bottom in a vertical depth direction; determining, according to horizontal component signals acquired by each of the shallow geophones and a preset function, a polarization direction of the horizontal component signal acquired to obtain an azimuth of the shallow geophone; determining, according to an event inclination angle of a scalar signal in horizontal component signals acquired by each of the deep geophones, and a correlation between the deep geophone and a forward adjacent geophone in horizontal component signal based on the event inclination angle, an azimuth of the deep geophone; and determining, according to the horizontal component signals and the azimuth of each of geophones, a radial and a tangential component of the target seismic wave.

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.

A method for classifying a microseismic event, including: analyzing microseismic event files through a combination of two fault tolerant machine learning pipelines, an acoustic machine learning pipeline and a visual machine learning pipeline; and generating a classification prediction for the microseismic event files by combining predictions from the acoustic machine learning pipeline and the visual machine learning pipeline.

A rock sample is nano-indented from a surface of the rock sample to a specified depth less than a thickness of the rock sample. While nano-indenting, multiple depths from the surface to the specified depth and multiple loads applied to the sample are measured. From the multiple loads and the multiple depths, a change in load over a specified depth is determined, using which an energy associated with nano-indenting rock sample is determined. From a Scanning Electron Microscope (SEM) image of the nano-indented rock sample, an indentation volume is determined responsive to nano-indenting, and, using the volume, an energy density is determined. It is determined that the energy density associated with the rock sample is substantially equal to energy density of a portion of a subterranean zone in a hydrocarbon reservoir. In response, the physical properties of the rock sample are assigned to the portion of the subterranean zone.

A retrofit valve shutoff device is provided that comprises a coupling key for coupling with an actuator of a shutoff valve on a fluid supply line, an inertial measurement unit for generating one or more signals in response to arrival of seismic waves, a motor for rotating the coupling key and the actuator of the shutoff valve, and a processing unit for receiving the one or more signals from the inertial measurement unit, analyzing the received signals to determine whether to close the shutoff valve, and sending a signal to the motor to rotate the coupling key and the actuator of the shutoff valve to close the shutoff valve based on the analysis of the received signals.

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.

A method of mapping micro-fractures of a fracture network comprising: introducing a capsule or coated capsule or containment into the fracture network, where in the capsules or containment comprise an explosive substance and a plurality of micro-proppant; allowing initiation of the explosive substance of some or all of the plurality of the capsules to occur, wherein initiation of the explosive substance causes detonation of the explosive substance, and wherein the detonation produces one or more micro-seismic events; and causing or allowing at least a portion of the micro-proppant to enter one or more of the micro-fractures.

Provided are embodiments for hydrocarbon reservoir development that include the following: identifying proposed well locations within a reservoir boundary, for each location, developing a well plan by: (a) identifying layers of the reservoir located below the proposed location; (b) iteratively assessing the layers (from deepest to shallowest) to identify a deepest “suitable” layer that is not dry, congested, or unsuitable for gas production; and (c) performing the following for the identified layer and the location: (i) determining a borehole configuration for the location; (ii) determining a completion type for the location; and (iii) determining a stimulation treatment for the location, where a well plan for the location (e.g., for use in developing the reservoir) is generated that specifies some or all of a well location, the target layer, a borehole configuration, a completion type, and a stimulation treatment that corresponds to those determined for the proposed well location.

An artificial intelligence calculation method and apparatus for monitoring an earthquake in real time based on edge cloud cooperation is applied to a micro-earthquake data processing system. The micro-earthquake data processing system includes an edge calculation device and a remote server in communication connection with the edge calculation device. The remote server deploys a micro-earthquake data analyzing model based on an artificial intelligence to the edge calculation device in advance. The method includes steps of receiving, by the remote server, effective event data related to the micro-earthquake from the edge calculation device; performing a transfer training to the micro-earthquake data analyzing model by the remote server according to the effective event data; and updating the model after the micro-earthquake data analyzing model that has been transfer-trained is transmitted to the edge calculation device by the remote server.