A retrofit valve shutoff device comprises a coupling key for coupling with an actuator of a shutoff valve, an accelerometer for making acceleration measurements in three directions, a motor, and a processing unit. The processing unit determines the arrival of seismic P-waves when the ratio of vibrations' power in the vertical direction with respect to a sum of the vibrations' power in the three directions exceeds a first threshold. The processing unit then determines the arrival of seismic S-waves when the sum of the vibrations' power in the three directions exceeds a second threshold. The processing unit then determines the arrival of seismic surface waves when the sum of the vibrations' power in the three directions exceeds a third threshold. The processing unit then sends a signal to the motor to rotate the coupling key and the actuator of the shutoff valve to close the shutoff valve.

A solution for managing effect-generating operations is provided. Data regarding one or multiple types of effects being generated by the operations can be acquired and analyzed. When necessary, actions can be initiated to benefit affected individuals or to improve the operations, e.g., by mitigating a source of excessive effects. In an illustrative application, the effect-generating operations are train operations and the types of effects include acoustic and/or vibration effects.

A system includes a first wellbore operation controller for controlling a wellbore operation and generating a first broadcast indicating a first data topic desired for controlling the wellbore operation. The system also includes a second wellbore operation controller for generating a data stream associated with a wellbore and for generating a second broadcast indicating a second data topic that promotes the data stream. The system includes a mediator computing device that receives the first broadcast and the second broadcast and determines that the first wellbore operation controller is subscribed to the data stream by comparing the first data topic to the second data topic. In response to determining that the first wellbore operation controller is subscribed to the data stream, the mediator computing device creates a data link between the first wellbore operation controller and the second wellbore operation controller.

Aspects of the subject technology relate to systems and methods for controlling a hydraulic fracturing job. Systems and methods are provided for receiving diagnostics data of a hydraulic fracturing completion of a wellbore, accessing a fracture formation model that models formation characteristics of fractures formed through the wellbore into a formation surrounding the wellbore during the hydraulic fracturing completion with respect to surface variables of the hydraulic fracturing completion, selecting one or more subsurface objective functions from a plurality of subsurface objective functions for changing one or more of the formation characteristics of the fractures, the one or more subsurface objective functions including an objective function for cluster efficiency, the objective function for cluster efficiency including flow distribution throughout a plurality of clusters of perforations, and applying the fracture formation model based on the diagnostics data to determine values of the surface variables.

The calibration of fracture models for naturally fractured reservoirs using fracture properties from X-ray micro-computed tomography (X-ray MicroCT). A core plug is obtained from a subsurface naturally fractured hydrocarbon reservoir, and a fracture property such as fracture porosity and a fracture effective permeability of the hydrocarbon reservoir are determined. A natural fracture model is generated using reservoir parameters and fluid flow paths, and fracture properties such as fracture porosity and a fracture effective permeability are determined from the natural fracture model. The fracture properties of the natural fracture model are calibrated using the fracture properties from the X-ray MicroCT analysis of the core plug.

A method for mapping fiber optic distributed acoustic sensing (DAS) measurements to particle motion involves obtaining, from a fiber optic DAS system in a wellbore, a first set of DAS data associated with a first seismic wave; obtaining, from a discrete seismic receiver in the wellbore, measured particle motion data associated with the first seismic wave; generating training data from the first set of DAS data and the measured particle motion data; training a machine learning model using the training data; obtaining a second set of DAS data associated with a second seismic wave; and determining a predicted particle motion in response to the second seismic wave using the machine learning model applied to the second set of DAS data.

The present invention relates to a method for separating information associated with diffraction events from specular information present in the seismic data, the method comprising the steps of: obtaining an input data, wherein the input data is a pre-stacked seismic data; building velocity guides, which comprises providing a table containing velocity information for time samples for different CDPs (Common-Depth Points) indices; estimating DSR (Double Square Root) kinematic parameters, which comprises estimating kinematic parameters associated with the DSR traveltime for each sample of the input data considering an estimation aperture, which comprises the region in which the DSR traveltime adjustment to the input data will be evaluated; DSR stacking of each input data sample considering a stacking aperture, which comprises the region in which the input data amplitudes will be stacked over the DSR traveltime; and DSR spreading each sample of the pre-stacked data, comprising defining a aperture, wherein the aperture comprises the region in which the amplitudes of the DSR stacked data, obtained in the DSR stacking step over the DSR traveltime, are distributed.

A method can include receiving seismic data responsive to stimulation of an anisotropic formation via a well disposed in the formation; receiving crosswell calibrated velocity model information that spans a depth range of the anisotropic formation; locating a microseismic event generated by the stimulation based at least in part on a portion of the received seismic data and based at least in part on the crosswell calibrated velocity model information; and rendering the located microseismic event to a display with respect to one or more dimensions of the anisotropic formation.

A method and system includes acquiring a seismic dataset while fluids are injected into the subsurface with seismic data recorded at multiple sensor locations. Seismic travel times are computed between sensors and subsurface locations using a velocity model. Travel times and travel time delays between pairs of sensors may be used as input to determine a similarity coefficient associated with subsurface positions. The similarity coefficients are determined using cross correlation, semblance calculations or eigenstructure decomposition. The coefficient values are related to the acoustic response at each subsurface position and may be summed together for each position for comparison with other subsurface positions to determine the position of a fluid front moving through the subsurface. The values may be displayed to illustrate the position of fluids in the subsurface and displayed to show the time variance of the fluid position.

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.