Abstract: A hierarchical conditioning methodology for building and conditioning a geological model is disclosed. In particular, the hierarchical conditioning may include separate levels of conditioning of template instances using larger-scale data (such as conditioning using large-scale data and conditioning using medium-scale data) and using smaller-scale data (such as fine-scale data). Further, one or more templates, to be instantiated to generate the geological bodies in the model, may be selected from currently available templates and/or machine-learned templates. For example, the templates may be generated using unsupervised or supervised learning to re-parameterize the functional form parameters, or may be generated using statistical generative modeling.

Abstract: A method for conditioning of surface-based geological models is provided. Surface-based geological models seek to represent a portion of the subsurface while honoring the available data. However, conditioning of surface-based geological models may be challenging particularly for situations where the geologic elements, such as lobes or channels, are interspersed with another geological element, such as impermeable mud. To condition the geological model, muds are specified through a mud trend or a set of specified mud layers. For example, each mud layer provides the environment of the geological element, such as the lobe to rest on or the channel to erode into. The surface-based geological model may then be built by sequential conditioning layer by layer, such as bottom upward. In this way, the mud layers provide context in which to place objects during conditioning to better generate the surface-based geological model.

Abstract: A method to select a representative subset of a plurality of horizon surfaces or surface patches from geophysical subsurface imaging data, including: defining a score function on one or more horizon surfaces or surface patches; calculating, by a computer, the score for each of the plurality of horizon surfaces or surface patches with regard to other horizon surfaces or surface patches and whether the other horizon surfaces or surface patches have been selected or not for inclusion or exclusion in the subset of the plurality of horizon surfaces; selecting, by a computer, one or more of the plurality of horizon surfaces or surface patches to be included in the subset of the plurality of horizon surfaces or surface patches or excluded from the subset of the plurality of horizon surfaces or surface patches based on their respective scores; iteratively repeating the selecting and calculating steps until a stopping condition is reached and the subset of the plurality of horizon surfaces or surface patches is determ

Abstract: A workflow is presented that facilitates defining geocontextual information as a set of rules for multiple seismic attributes. Modeling algorithms may be employed that facilitate analysis of multiple seismic attributes to find candidate regions that are most likely to satisfy the set of rules. These candidates may then be sorted based on how well they represent the geocontextual information.

Abstract: A method to select a representative subset of a plurality of horizon surfaces or surface patches from geophysical subsurface imaging data, including: defining a score function on one or more horizon surfaces or surface patches; calculating, by a computer, the score for each of the plurality of horizon surfaces or surface patches with regard to other horizon surfaces or surface patches and whether the other horizon surfaces or surface patches have been selected or not for inclusion or exclusion in the subset of the plurality of horizon surfaces; selecting, by a computer, one or more of the plurality of horizon surfaces or surface patches to be included in the subset of the plurality of horizon surfaces or surface patches or excluded from the subset of the plurality of horizon surfaces or surface patches based on their respective scores; iteratively repeating the selecting and calculating steps until a stopping condition is reached and the subset of the plurality of horizon surfaces or surface patches is determ

Abstract: The present disclosure provides a system and method for automatically identifying and classifying seismic terminations within a seismic data volume. A set of surfaces is obtained (step 303) describing the seismic data volume. A plurality of seismic terminations is identified within the set of surfaces (step 307). Based upon seismic attributes or geometric criterion, a termination direction can be determined (step 309) for at least one termination.

Abstract: Method for analyzing seismic data representing a subsurface region for presence of a hydrocarbon system or a particular play. Seismic attributes are computed, the attributes being selected to relate to the classical elements of a hydrocarbon system, namely reservoir, seal, trap, source, maturation, and migration. Preferably, the attributes are computed along structural fabrics (1) of the subsurface region, and are smoothed over at least tens or hundreds of data voxels. The resulting geologic attributes (2) are used to analyze the data for elements of the hydrocarbon system and/or recognition of specific plays, and for ranking and annotating partitioned regions (3) of the data volume based on size, quality, and confidence in the prospectivity prediction (5). A catalog (8) of hydrocarbon trap configurations may be created and used to identify potential presence of hydrocarbon traps and/or aid in scoring (4) and ranking partitioned regions as hydrocarbon prospects.

Abstract: The present disclosure provides a system and method for automatically identifying and classifying seismic terminations within a seismic data volume. A set of surfaces is obtained (step 303) describing the seismic data volume. A plurality of seismic terminations is identified within the set of surfaces (step 307). Based upon seismic attributes or geometric criterion, a termination direction can be determined (step 309) for at least one termination.

Abstract: A workflow is presented that facilitates defining geocontextual information as a set of rules for multiple seismic attributes. Modeling algorithms may be employed that facilitate analysis of multiple seismic attributes to find candidate regions that are most likely to satisfy the set of rules. These candidates may then be sorted based on how well they represent the geocontextual information.

Abstract: Method for analysis of hydrocarbon potential of subterranean regions by generating surfaces or geobodies and analyzing them for hydrocarbon indications. Reflection-based surfaces may be automatically created in a topologically consistent manner where individual surfaces do not overlap themselves and sets of multiple surfaces are consistent with stratigraphic superposition principles. Initial surfaces are picked from the seismic data (41), then broken into smaller parts (“patches”) that are predominantly topologically consistent (42), whereupon neighboring patches are merged in a topologically consistent way (43) to form a set of surfaces that are extensive and consistent (“skeleton”). Surfaces or geobodies thus extracted may be automatically analyzed and rated (214) based on a selected measure (213) such as AVO classification or one or more other direct hydrocarbon indicators (“DHI”).

Abstract: Method for analyzing seismic data representing a subsurface region for presence of a hydrocarbon system or a particular play. Seismic attributes are computed, the attributes being selected to relate to the classical elements of a hydrocarbon system, namely reservoir, seal, trap, source, maturation, and migration. Preferably, the attributes are computed along structural fabrics (1) of the subsurface region, and are smoothed over at least tens or hundreds of data voxels. The resulting geologic attributes (2) are used to analyze the data for elements of the hydrocarbon system and/or recognition of specific plays, and for ranking and annotating partitioned regions (3) of the data volume based on size, quality, and confidence in the prospectivity prediction (5). A catalogue (8) of hydrocarbon trap configurations may be created and used to identify potential presence of hydrocarbon traps and/or aid in scoring (4) and ranking partitioned regions as hydrocarbon prospects.

Abstract: Method for analysis of hydrocarbon potential of subterranean regions by generating surfaces or geobodies and analyzing them for hydrocarbon indications. Reflection-based surfaces may be automatically created in a topologically consistent manner where individual surfaces do not overlap themselves and sets of multiple surfaces are consistent with stratigraphic superposition principles. Initial surfaces are picked from the seismic data (41), then broken into smaller parts (“patches”) that are predominantly topologically consistent (42), whereupon neighboring patches are merged in a topologically consistent way (43) to form a set of surfaces that are extensive and consistent (“skeleton”). Surfaces or geobodies thus extracted may be automatically analyzed and rated (214) based on a selected measure (213) such as one or more direct hydrocarbon indications (“DHI”), e.g. AVO classification.