Methods and systems, including computer programs encoded on a computer storage medium can be used for adaptive multi-scale geological modeling and well integration. The systems and methods are used to integrate seismic mapping data and well data for a subsurface region that includes a reservoir. The specification describes an example algorithm that is used to adaptively identify and isolate natural length scales in a seismic map. The identified natural length scales are then used to determine appropriate filtering of well information and ultimately achieve an automatic integration of orientation information from seismic map and well information.

A method includes receiving modelled seismic data that is to be recognized by the at least one classification and/or segmentation processor. The modelled seismic data can be represented within a transform domain. The method includes generating an output via the at least one processor based on the received modelled seismic data. The method also includes comparing the output of the at least one processor with a desired output. The method also includes modifying the at least one processor so that the output of the processor corresponds to the desired output.

Seismic exploration methods and data processing apparatuses employ a deep neural network to remove seismic interference (SI) noise. Training data is generated by combining an SI model extracted using a conventional model from a subset of the seismic data, with SI free shots and simulated random noise. The trained DNN is used to process the entire seismic data thereby generating an image of subsurface formation for detecting presence and/or location of sought-after natural resources.

A method for generating a high-resolution pseudo-reflectivity image of a subsurface region includes receiving seismic data associated with a subsurface region and captured by one or more seismic receivers, constructing a velocity model of the subsurface region based on the received seismic data, performing a seismic migration of the received seismic data based on the constructed velocity model to obtain migrated seismic data, computing polarized normal vectors associated with one or more subsurface reflectors of the subsurface region based on the migrated seismic data, and generating a pseudo-reflectivity image of the subsurface region based on both the computed polarized normal vectors.

Systems and methods are disclosed for identifying and displaying geostructural properties as a function of lithology, horizons, and faults interpreted from well and seismic data. Exemplary implementations may include obtaining an initial fracture distribution grid model; obtaining training structural deformation data; obtaining training subsurface lithology parameter data; obtaining training fracture attribute data; and training the initial fracture distribution grid model to generate a trained fracture distribution grid model.

A method is disclosed that includes obtaining a seismic data set and a seismic wave propagation velocity model and approximating the seismic wave propagation velocity model as a plurality of layers each bounded by a first and second bounding depth. For each of the plurality of layers, the method includes: simulation of the propagation of a seismic wave through the layer using a two-way seismic wave propagation simulator; forming an over-determined system of linear equations relating at least one mono-frequency component of the seismic wave at the first depth to one mono-frequency component at the second depth; and determining a plurality of one-way seismic wave propagation operators by inverting the over-determined system of linear equations. The method further includes processing the seismic data set using the one-way seismic wave propagation. A system and a non-transitory computer readable medium for implementing the method are also disclosed.

The present disclosure provides a physics-based and data-driven integrated method for rock burst hazard assessment, including the following steps: determining an initial stress concentration coefficient by conducting grid discretization on an assessment region, and assigning a value to each of grid nodes using a Weibull distribution function; obtaining a stress concentration coefficient value of each grid node under physics-based models; introducing seismic wave CT detection data to obtain stress concentration coefficient distribution in the assessment region under the integration of a seismic wave CT detection and its derived characterization stress model; introducing microseismic data to obtain stress concentration coefficient distribution in the assessment region under the integration of a microseismic damage reconstruction stress model; and assessing the degree of rock burst hazard according to the size of the stress concentration coefficient value.

One or more first sensors may be configured to sense seismic signals and one or more second sensors may be configured to sense electromagnetic crosstalk signals. The second sensors are not responsive to the seismic signals. The data from the first and second sensors may be recorded as first data and second data, respectively. The first data may be modified based on the second data to remove the electromagnetic crosstalk noise form the seismic data.

A method, article and system are provided for processing and interpreting acoustic data. The method and system includes providing a number of acoustic processing elements, each element being associated with an acoustic mode of a number of acoustic modes of a sonic measurement tool adapted to acquire data representing acoustic measurements in a borehole. In addition the method and system includes providing a user interface to organize a processing chain of the number of acoustic processing elements such that the acoustic processing elements process the acquired data according to a predefined workflow.

A method can include acquiring imagery of an exposed surface of the Earth; generating a multi-dimensional model based at least in part on the imagery; generating synthetic seismic data utilizing the multi-dimensional model; acquiring seismic data of a subsurface region of the Earth; performing a search that matches a portion of the acquired seismic data and a portion of the synthetic seismic data; and characterizing the subsurface region of the Earth based at least in part on the portion of the synthetic seismic data.