Methods to estimate formation shear wave slowness from multi-firings of different types of acoustic sources and multi-mode dispersion estimation systems are presented. The method includes obtaining waveform data of waves traversing through a downhole formation, where the waves are generated from multi-firings of different types of acoustic sources. The method also includes performing a multimode dispersion analysis of the waveform data for each firing of the multi-firings, and removing one or more tool waves generated from the multi-firings. The method further includes determining a formation type of the formation the waves traverse based properties of the waves and determining an initial shear wave slowness estimate of the waves. The method further includes generating a modeling of the waves, and reducing a mismatch between the modeling of the waves and a slowness dispersion of the waves to improve the modeling of the waves.

A system is described for determining a likelihood of a type of fluid in a subterranean reservoir. The system may include a processor and a non-transitory computer-readable medium that includes instructions executable by the processor to cause the processor to perform various operations. The processor may receive pre-stack seismic data having seismically-acquired data elements for geometric locations in a subterranean reservoir. The processor may determine, using the pre-stack seismic data, input features for each geometric location and may execute a trained model on the input features for determining a likelihood of a type of fluid in the subterranean reservoir and for determining a list of features affecting the likelihood. The processor may subsequently output the likelihood and the list of features.

Embodiments of the present disclosure provide a method and system for recognizing a mine microseismic event, and belong to the field of mine data processing. The method includes: converting historical microseismic data monitored by a mine microseismic monitoring system into a microseismic waveform image, and then, converting the microseismic waveform image into a four-neighborhood microseismic waveform graph structure; performing area defining on the microseismic waveform graph structure, and extracting a similar feature layer of any node in the microseismic waveform graph structure based on the defined area; and taking the microseismic waveform image as an input layer of an improved convolutional neural network model, and sequentially connecting the input layer with the similar feature layer as well as a convolutional layer, a pooling layer, a fully connected layer and an output layer which are pre-configured for the improved convolutional neural network model to form a recognition model for recognizing the mine microseismic event. By using the recognition model designed in the present disclosure, the similar feature layer can be extracted, so that the mine microseismic event is effectively recognized.

A least one seismic attribute is determined for each voxel of the seismic volume. A first horizon is selected for mapping and a sparse global grid is generated which includes the horizon, at least one constraint point identifying the horizon, and a number of points having a depth in the seismic volume. A value of at least one seismic attribute is determined for each point and their depths are adjusted based on the value of the seismic attribute. A map of the horizon can be generated based on the adjusted depths. Multiple local grids can be generated based on the sparse global grid, and the depths of the local grid points adjusted to generate a map of the horizon at voxel level resolution. The seismic volume can be mapped into multiple horizons, where previously mapped horizons can function as constraints on the sparse global grid.

Computer-implemented stratigraphic play quality generation is disclosed. Stratigraphic data can be processed from each of a plurality of respective data sources to generate conditioned stratigraphic data. From at least some of the conditioned stratigraphic data, attributes of at least one seismic sequence can be extracted, and at least one seismic surface and at least one structural element associated with at least some of the conditioned stratigraphic data can be determined. At least some of the conditioned stratigraphic data representing sedimentary layers can be correlated with seismic reflection data to ascertain a subsurface of the geologic area at a respective depth. Reservoir properties associated with the geologic area are linked to elastic properties, and a 2D model built. Moreover, 3D map can be generated that is usable for a prospective drilling plan.

A method for modelling and migrating seismic data, that includes using an acoustic wave equation and a spatial distribution of one or more earth-model parameters. The acoustic wave equation is modified by including at least one secondary source term, and based on a seismic acquisition configuration, either calculating the seismic signals that would be detected from the modelled wavefield or migrating observed seismic signals or migrating residual signals as part of an inversion.

Processes and systems for generating images of a subterranean formation from recorded seismic data obtained in a marine survey are described. Processes and systems compute reverse-time receiver-motion-corrected upgoing and downgoing pressure wavefields at different locations of corresponding upgoing and downgoing observation levels based on the recorded seismic data. The reverse-time receiver-motion-corrected upgoing and downgoing pressure wavefields are time forwarded and extrapolated to obtain a corresponding receiver-motion-corrected upgoing and downgoing pressure wavefields at locations of a static observation level. An image of the subterranean formation is generated based at least in part on the receiver-motion-corrected upgoing pressure wavefield and the receiver-motion-corrected downgoing pressure wavefield.

A method for subsurface fault extraction using undirected graphs is provided. Extracting faults in the subsurface may assist in various stages of geophysical prospecting. To that end, an undirected graph may be used in order to identify distinctive fault branches in the subsurface. Fault probability data, from seismic data, may be used to establish connections in the undirected graph. Thereafter, some of the connections in the undirected graph may be removed based on analyzing one or more attributes, such as dip, azimuth, or context, associated with the connections or nodes associated with the connections. After which, the undirected graph may be analyzed in order to extract the faults in the subsurface.

Superterranean acoustic networks, methods of forming superterranean acoustic networks, and methods of operating superterranean acoustic networks are disclosed herein. The superterranean acoustic networks include superterranean hydrocarbon infrastructure that extends above a ground surface, defines a waveguide, and contains a fluid. The infrastructure also includes a plurality of acoustic communication nodes spaced-apart along the superterranean hydrocarbon infrastructure. Each acoustic communication node of the plurality of acoustic communication nodes includes an acoustic transmitter and an acoustic receiver. The acoustic transmitter is configured to generate a generated acoustic signal and to supply the generated acoustic signal to the waveguide. Responsive to receipt of the generated acoustic signal, the waveguide is configured to propagate a propagated acoustic signal there through. The acoustic receiver is configured to receive another propagated acoustic signal, which is generated by another acoustic communication node of the plurality of acoustic communication nodes, from the waveguide as a received acoustic signal.

Logging of data by a downhole tool disposed in a borehole may be affected by tool wave effects. The tool waves appear in the first echo of casing wave arrivals and the amplitudes may be much larger than casing wave arrivals. The estimates of casing wave amplitude are biased due to these tool wave arrivals when using conventional cement-bond logging (CBL) processing. An automated adaptive inversion-based array processing for CBL evaluation using a downhole tool provides an improvement in the calculation of a bonding index.