A method of analysing seismic data to detect possible hydrocarbons includes determining a set of data tiles from a seismic data cube of seismic data and testing each data tile in the set of data tiles to determine whether it corresponds to a possible fluid contact.

A method for training a backpropagation-enabled segmentation process is used for identifying an occurrence of a sub-surface feature. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A prediction of the occurrence of the subsurface feature has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.

A method can include accessing volumetric data from a data store, where the volumetric data correspond to a region; generating structured shape information for the region using at least a portion of the volumetric data; and, in response to a command from a client device, transmitting to the client device, via a network interface, a visualization data stream generated using at least a portion of the structured shape information.

The present invention belongs to the field of treatment for data identification and recording carriers, and specifically relates to a method and system for analyzing filling for a karst reservoir based on spectrum decomposition and machine learning, which aims to solve the problems that by adopting the existing petroleum exploration technology, the reservoir with fast lateral change cannot be predicted, and the development characteristics of a carbonate cave type reservoir in a large-scale complex basin cannot be identified. The method comprises: acquiring data of standardized logging curves; obtaining a high-precision 3D seismic amplitude data body by mixed-phase wavelet estimation and maximum posteriori deconvolution and enhancing diffusion filtering. According to the method and the system, the effect of identifying the development characteristics of the carbonate karst cave type reservoir in the large-scale complex basin can be achieved, and the characterization precision is improved.

A computer-implemented method for generating a 3D geological model of a subsurface volume of a geographic site. The method includes processing, based on a machine-learning-based model, borehole data of a plurality of boreholes at the geographic site and trusted geological data associated with the geographic site, so as to generate a plurality of geological cross-sections of the subsurface volume of the geographic site. The borehole data includes data related to subsurface soil and/or rock information along at least part of each of the plurality of boreholes. The trusted geological data includes data related to prior stratigraphic information associated with the geographic site. Each of the geological cross-sections contains respective stratigraphic information. The method also includes forming the 3D geological model based on the generated geological cross-sections for display.

Methods of providing digital images of living tissue that may include: obtaining data of a propagating wavefield through living tissue; obtaining a reference digital image of the living tissue; selecting a holographic computational method of wavefield imaging; selecting a wavefield based on one or more parameters; calculating a sampling ratio by dividing a number of data samples in the data subset by a number of image samples in the data subset; decimating the data subset; generating a new digital image based on the selected holographic computational method of imaging, the decimated data subset, and parameters corresponding to the data subset; and determining a quantitative difference measure between the reference digital image and the new digital image based on the changing of one or more parameters selected from the group consisting of field sampling, imaging sampling, and image quality.

A computer-implemented method for detecting at least one natural contour of a geologic object in 3D seismic data may comprise: (a) receiving at least one first predetermined data set from said 3D seismic data comprising a plurality of phase events; (b) selecting at least one first seed phase event having a first phase characteristic from said plurality of phase events; (c) determine a characterizing score between said selected at least one first seed phase event and each one of a predetermined number of candidate phase events of said at least one first predetermined data set; (d) assigning said characterizing score to each one of said predetermined number of candidate phase events; (e) adjusting said characterizing score of at least one of said predetermined number of candidate phase events in accordance with at least one first boundary condition; (f) determining at least one natural contour between said at least one first seed phase event and at least a second phase event, utilizing an optimization algorithm; (g) generating a visual representation of said at least one natural contour within said at least one first predetermined data set.

Systems and methods for interpreting and visualizing multi-Z horizons from seismic data are disclosed. A two-dimensional (2D) representation of seismic data is displayed via a graphical user interface (GUI). User input is received via the GUI for interpreting a multi-Z horizon within a portion of the displayed 2D representation. The user's input is tracked relative to displayed 2D representation within the GUI. Based on the tracking, each of a plurality of surfaces for the multi-Z horizon is determined. At least one intersection point between the multi-Z horizon surfaces is identified. A depth position for each surface relative to other surfaces is determined. The 2D representation of the seismic data is dynamically updated to include visual indications for the plurality of surfaces and the intersection point(s), based on the depth position of each surface, where the visual indications use different visualization styles to represent the surfaces and intersection point(s).

A fault indicator calculator, a method for determining a fault indicator, and a fault indicator calculating system are disclosed herein. One embodiment of a fault indicator calculator includes: 1) an interface configured to receive seismic data, and 2) a processor configured to scan a manifold-shaped operator through said seismic data at a range of dips and azimuths and calculate fault throws at various orientations of said dips and azimuths independent of determining other fault indicators.

The present invention relates to a method of prediction of hydrocarbon accumulation in a geological region comprising the following steps of: a. Generation of a geological basin model; b. Generation of a geomechanical model; c. Generation of an integrated model; d. Generation of a strain map based on the information obtained in steps a to c; e. Prediction of hydrocarbon accumulation from the strain maps.