Geologic modeling methods and systems disclosed herein employ an improved simulation gridding technique. For example, an illustrative geologic modeling method may comprise: obtaining a geologic model representing a faulted subsurface region in physical space; mapping the physical space geologic model to a design space model representing an unfaulted subsurface region; gridding the design space model to obtain a design space mesh; partitioning cells in the design space mesh with faults mapped from the physical space geologic model, thereby obtaining a partitioned design space mesh; mapping the partitioned design space mesh to the physical space to obtain a physical space simulation mesh; and outputting the physical space simulation mesh.

The present invention describes a method for adaptively determining a plurality of sedimentary facies from 3D seismic data, comprising the steps of (a) generating an attribute volume comprising at least one attribute from said 3D seismic data; (b) generating at least one frequency decomposition colour blend volume from said 3D seismic data; (c) generating a data volume comprising at least one geological object utilising data from said attribute volume and said frequency decomposition colour blend volume; (d) generating a facies classification model dataset for a predetermined region of interest of said 3D seismic data applying a probabilistic algorithm and utilizing data from said geobody volume and said frequency decomposition colour blend volume; (e) selectively adjusting at least one first model parameter, so as to optimise said facies classification model dataset in accordance with a conceptual geological model; and (f) selectively providing said facies classification model dataset in a representative property model of said region of interest of said 3D seismic data.

A system can determine a location for future wells using machine-learning techniques. The system can receive seismic data about a subterranean formation and may determine a set of seismic attributes from the seismic data. The system can block the set of seismic attributes into a set of blocked seismic attributes by distributing the set of seismic attributes onto a geo-cellular grid representative of the subterranean formation. The system can apply a trained machine-learning model to the set of blocked seismic attributes to generate a composite seismic parameter. The system can distribute the composite seismic parameter in the subterranean formation to characterize formation locations based on a predicted presence of hydrocarbons.

A method for training a backpropagation-enabled regression process is used for predicting values of an attribute of subsurface data. A multi-dimensional seismic data set with an input dimension of at least two is inputted into a backpropagation-enabled process. A predicted value of the attribute has a prediction dimension of at least 1 and is at least 1 dimension less than the input dimension.

Disclosed are methods of marine 3D seismic data acquisition that do not require compensation for winds and currents.

Methods, computing systems, and computer-readable media for interpreting seismic data, of which the method includes receiving seismic data representing a subterranean volume, and determining a feature-likelihood attribute of at least a portion of a section of the seismic data. The feature-likelihood attribute comprises a value for elements of the section, the value being based on a likelihood that the element represents part of a subterranean feature. The method also includes identifying contours of the subterranean feature based in part on the feature-likelihood attribute of the section, and determining a polygonal line that approximates the subterranean feature.

Accordingly, there are disclosed herein geologic modeling methods and systems employing reference-based inversion of seismic image volumes. An illustrative method embodiment includes: (a) obtaining a measured seismic image volume; (b) determining a reference seismic image volume based on a reference model; (c) deriving a synthesized seismic image volume from a geologic model; (d) detecting at least one geologic model region where the synthesized seismic image volume and the measured seismic image volume are mismatched; (e) finding a reference model region where the reference seismic image volume best matches the measured seismic image volume; (f) replacing content of the at least one geologic model region with content of the reference model region to obtain an improved geologic model; and (g) outputting the improved geologic model.

A method for modeling a subsurface volume includes receiving a plurality of ordered seismic images including representations of objects in the subsurface volume, generating flow fields based on a difference between individual images of the plurality of ordered seismic images, and identifying the objects in the seismic images based on the flow fields and the plurality of ordered seismic images.

The present invention discloses a system and method for phased array sound wave advanced geological exploration for a shield tunneling machine. The system includes a phased array sound wave emitting and receiving apparatus, a probe automatic telescopic apparatus, an automatic protection and cleaning apparatus, and a signal processing and imaging system. Sonic probes are installed on a side wall of a main spoke, opposite to a rotation direction, of a cutterhead of the shield tunneling machine, on the basis of automatic detection of a telescopic state and a contact state, sonic array probes are enabled to make contact with a tunnel face by a hydraulic push rod, a focus sound wave is emitted by using a phased array emitting technology, and a reflected wave signal with front geological information reflected from the front of the tunnel face is received. A scanning direction of a sound wave beam is controlled and changed continuously through a host system, on the premise of obtaining a suspected abnormal body position, the suspected position is imaged in detail by using a focusing image till scanning of a whole two-dimensional section is completed, then the cutterhead is rotated to change an arrangement direction of an array to continue scanning of a next two-dimensional section, and finally three-dimensional geological exploration in front of the tunnel face is realized.

Geologic modeling methods and systems disclosed herein employ an improved simulation meshing technique. One or more illustrative geologic modeling methods may comprise: obtaining a geologic model representing a faulted subsurface region in physical space; providing a set of background cells that encompass one or more partial faults within the subsurface region; defining a pseudo-extension from each unterminated edge of said one or more partial faults to a boundary of a corresponding background cell in said set; using the pseudo-extensions and the background cell boundaries to partition the subsurface region into sub-regions; deriving a simulation mesh in each sub-region based on the horizons in each sub-region; and outputting the simulation mesh.