Computer-implemented methods, apparatus, and computer programs disclosed herein are for obtaining horizon data, and comprise determining at least one extrema binary volume from a seismic data volume comprising a plurality of voxels and assigning a predetermined extrema value to each one of the found extreme voxels; determining an extrema graph from the at least one extrema binary volume; determining a neighbour graph from the extrema graphs; partitioning the nodes of the neighbour graph into a set of clusters, wherein a cluster contains a plurality of connected nodes representing extrema voxels of the at least one extrema binary volume, and each node is part of one cluster only; for each subset of the set of clusters, identifying whether or not the subset is a contradictory set of clusters according to at least one first predetermined condition; hierarchically partitioning the neighbour graph into a plurality of subgraphs, for example using a minimum cut approach, each subgraph being provided by a separate non-contradictory cluster, which is not part of any contradictory sets of clusters; and obtaining horizon data representing a plurality of horizons from the non-contradictory clusters inducing the plurality of subgraphs of the neighbour graph.

This invention provides a fiber Bragg grating (FBG) monitoring device for dynamic disasters in coal mines. It includes a data acquisition device, which is used to collect the seismic wave signal in coal mines and reflect the possibility of the current coal and gas outburst hazard through the seismic wave signal described; a data processing device, which is used to process the collected data, eliminate the interferential signal and convert the effective signal into the measured physical quantity, and then send it to the display unit or save it; a real-time processor, which is used to achieve the acquisition and processing of real-time data; a display unit, which is used for the process of acquisition, storage, display and historical data query, and the display of residual capacity; a power supply unit, which is used to provide energy for the whole monitoring device.

Techniques, systems and devices to generate a seismic wavefield solution. This includes receiving a velocity model corresponding to at least one attribute of seismic data, receiving source wavelet data corresponding to the seismic data, generating a guide image based upon at least one attribute of the velocity model, transmitting the velocity model, the source wavelet data, and the guide image to a machine learning system, and training the machine learning system into a trained machine learning system using the velocity model, the source wavelet data, and the guide image.

A method includes collecting seismic survey data and processing the seismic survey data to identify subterranean conduit coordinates. The method also includes performing a conduit plugging operations using the identified subterranean conduit coordinates. A related system includes at least one seismic source and at least one seismic receiver to collect seismic survey data in response to at least one shot fired by the at least one seismic source. The system also includes a processing unit in communication with the at least one seismic receiver. The processing unit analyzes the collected seismic survey data to identify subterranean conduit coordinates for use with conduit plugging operations.

Generally, seismic data may provide valuable information with regard to the description such as the location and/or change of hydrocarbon deposits within a subsurface region of the Earth. The present disclosure generally discusses techniques that may be used by a computing system to analyze a data set including weak-coherence signals (e.g., non-coherent blending noise). In particular, a computing system may detect portion of the weak-coherence signals of a gather due to the overlap of selected seismic source excitations and use a mask to isolate coherent signals and the other weak-coherence signals from the masked portion of weak-coherence signals. The coherent signals and other weak-coherence signals may be iteratively processed and used to predict values of the masked weak-coherence signals.

Generally, seismic data may provide valuable information with regard to the description such as the location and/or change of hydrocarbon deposits within a subsurface region of the Earth. The present disclosure generally discusses techniques that may be used by a computing system to analyze a data set including weak-coherence signals (e.g., non-coherent blending noise). In particular, a computing system may detect portion of the weak-coherence signals of a gather due to the overlap of selected seismic source excitations and use a mask to isolate coherent signals and the other weak-coherence signals from the masked portion of weak-coherence signals. The coherent signals and other weak-coherence signals may be iteratively processed and used to predict values of the masked weak-coherence signals.

Disclosed are methods, systems, and computer-readable medium to perform operations including: receiving for a plurality of common midpoint-offset bins each comprising a respective plurality of seismic traces, respective candidate pilot traces representing the plurality of common midpoint-offset bins; generating, based on the respective candidate pilot traces, a respective plurality of corrected seismic traces for each of the plurality of common midpoint-offset bins; grouping the respective pluralities of corrected seismic traces into a plurality of enhanced virtual shot gathers (eVSGs); generating, based on the plurality of common midpoint-offset bins, a common-midpoint (CMP) velocity model; calibrating the CMP velocity model using uphole velocity data to generate a pseudo-3 dimensional (3D) velocity model; performing, based on the plurality of enhanced virtual shot gathers and the pseudo-3D velocity model, a 1.5-dimensional full waveform inversion (FWI); and determining the subsurface velocity model based on the 1.5 dimensional FWI.

Aspects of the present disclosure describe dynamic road traffic noise mapping using DFOS over a telecommunications network that enables mapping of road traffic-induced noise at any observer location. DFOS is used to obtain instant traffic data including vehicle speed, volume, and vehicle types, based on vibration and acoustic signal along the length of a sensing fiber along with location information. A sound pressure level at a point of interest is determined, and traffic data associated with such point is incorporated into a reference noise emission database and a wave propagation theory for total sound pressure level prediction and mapping. Real-time wind speed using DFOS—such as distributed acoustic sensing (DAS)—is obtained to provide sound pressure adjustment due to the wind speed.

Aspects of the present disclosure describe dynamic road traffic noise mapping using DFOS over a telecommunications network that enables mapping of road traffic-induced noise at any observer location. DFOS is used to obtain instant traffic data including vehicle speed, volume, and vehicle types, based on vibration and acoustic signal along the length of a sensing fiber along with location information. A sound pressure level at a point of interest is determined, and traffic data associated with such point is incorporated into a reference noise emission database and a wave propagation theory for total sound pressure level prediction and mapping. Real-time wind speed using DFOS—such as distributed acoustic sensing (DAS)—is obtained to provide sound pressure adjustment due to the wind speed.

Techniques for generating a geological model from 3D seismic data and rock property data are disclosed. Rock property data and 3D seismic data are received. Based on the rock property data and the 3D seismic data, an adaptive geological model is generated. The adaptive geological model includes a characteristic geological property. Synthetic seismic data is generated from a first region of interest of the adaptive geological model. The synthetic seismic data is adapted to facilitate a comparison between the first region of interest and a corresponding region of interest of the received 3D seismic data. The characteristic geological property is adjusted until the comparison indicates a result that is within a predetermined threshold region of the corresponding value from the rock properties. A validated geologic model is then generated.