Abstract: Techniques to match a signature in seismic data with a seismic attribute space. A method includes automatically selecting a first plurality of seismic attributes corresponding to seismic data as first selected seismic attributes, combining the first selected seismic attributes into a first realization of attributes, performing a first cluster analysis on the first realization of attributes to generate a first clustered volume, selecting a region of interest (ROI) in the seismic data, projecting the ROI onto the first clustered volume to generate a first signature, determining a first level of correlation between the ROI and the first signature, and determining whether the first level of correlation between the ROI and the first signature exceeds a predetermined threshold and outputting a first correlation volume corresponding to the first signature when the first level of correlation between the ROI and the first signature exceeds the predetermined threshold.

Abstract: A method of performing single trace inversion to characterize changes in a subsurface region includes obtaining a base seismic trace and a monitor seismic trace of the subsurface region at different respective times. The method includes generating a predicted monitor seismic trace from the base seismic trace by a process including applying a time shift to the base seismic trace, the time shift being derived from estimated velocity perturbations occurring between the base seismic trace and the monitor seismic trace, compensating for amplitude changes between the base seismic trace and the monitor seismic trace, wherein the time shift is applied to the amplitude changes, and minimizing a difference between the predicted monitor seismic trace and the monitor seismic trace by iteratively estimating the velocity perturbations to obtain final estimated velocity perturbations. Changes of at least part of the subsurface region may be characterized using the final estimated velocity perturbations.

Abstract: Techniques to match a signature in seismic data with a seismic attribute space. A method includes automatically selecting a first plurality of seismic attributes corresponding to seismic data as first selected seismic attributes, combining the first selected seismic attributes into a first realization of attributes, performing a first cluster analysis on the first realization of attributes to generate a first clustered volume, selecting a region of interest (ROI) in the seismic data, projecting the ROI onto the first clustered volume to generate a first signature, determining a first level of correlation between the ROI and the first signature, and determining whether the first level of correlation between the ROI and the first signature exceeds a predetermined threshold and outputting a first correlation volume corresponding to the first signature when the first level of correlation between the ROI and the first signature exceeds the predetermined threshold.

Abstract: A method of performing single trace inversion to characterize changes in a subsurface region includes obtaining a base seismic trace and a monitor seismic trace of the subsurface region at different respective times. The method includes generating a predicted monitor seismic trace from the base seismic trace by a process including applying a time shift to the base seismic trace, the time shift being derived from estimated velocity perturbations occurring between the base seismic trace and the monitor seismic trace, compensating for amplitude changes between the base seismic trace and the monitor seismic trace, wherein the time shift is applied to the amplitude changes, and minimizing a difference between the predicted monitor seismic trace and the monitor seismic trace by iteratively estimating the velocity perturbations to obtain final estimated velocity perturbations. Changes of at least part of the subsurface region may be characterized using the final estimated velocity perturbations.

Abstract: A method includes receiving image data that is to be recognized by the at least one neural network. The image data is representative of a fault within a subsurface volume. The image data includes three-dimensional synthetic data. The method also includes generating an output via the at least one neural network based on the received image data. The method also includes comparing the output of the at least one neural network with a desired output; and modifying the neural network so that the output of the neural network corresponds to the desired output.