Systems and methods for identifying potential hydrocarbon traps in a subterranean region can include: receiving seismic data of the subterranean region, the seismic data acquired by at least one seismic sensor, the seismic data indicating positions of physical barriers to hydrocarbon flow in the subterranean region and using anisotropic lateral and upward erosion to identify possible locations of hydrocarbons.

Geologic modeling methods and systems disclosed herein employ an improved simulation gridding technique that optimizes simulation efficiency by balancing the computational burdens associated with remeshing against the performance benefits of doing so. One method embodiment includes: (a) obtaining a geologic model representing a subsurface region as a mesh of cells, at least some of the cells in the mesh having one or more interfaces representing boundaries of subsurface structures including at least one fracture; (b) determining a fracture extension to the at least one fracture; (c) evaluating whether the fracture extension is collocated with, or is proximate to, an existing cell interface, and using the existing cell interface if appropriate or creating a new cell interface if not; and (d) outputting the updated version of the geologic model.

There is disclosed a system and method for analyzing geological features of a reservoir, such as a subterranean hydrocarbon reservoir undergoing changes during different stages of its production, by utilizing an artificial neural network to learn from hydrocarbon reservoir production project. In an aspect, there is provide a system and method for utilizing data collected from 4D seismic studies in order to train an artificial neural network to recognize how physical properties of a hydrocarbon reservoir change over time, as the hydrocarbon reservoir is produced. In an embodiment, the system and method are adapted to generate and obtain a plurality of image slices or image planes derived from a 3D seismic baseline and at least one monitor acquired over the course production of the hydrocarbon reservoir. Corresponding 2D image slices derived from the 3D seismic baseline and a subsequent monitor are correlated and matched and are then used to train an artificial neural network to create a predictive model of how the reservoir may change over time.

Computer-implemented stratigraphic play quality generation is disclosed. Stratigraphic data can be processed from each of a plurality of respective data sources to generate conditioned stratigraphic data. From at least some of the conditioned stratigraphic data, attributes of at least one seismic sequence can be extracted, and at least one seismic surface and at least one structural element associated with at least some of the conditioned stratigraphic data can be determined. At least some of the conditioned stratigraphic data representing sedimentary layers can be correlated with seismic reflection data to ascertain a subsurface of the geologic area at a respective depth. Reservoir properties associated with the geologic area are linked to elastic properties, and a 2D model built. Moreover, 3D map can be generated that is usable for a prospective drilling plan.

The invention concerns a method for evaluating a geophysical survey acquisition geometry over a region of interest. The method comprises determining a location of a plurality of base camps in respect of a determined minimal surface density of base camps, determining a first set of locations of a plurality of receivers in respect of a determined minimal surface density of receivers, generating a first synthetic geophysical dataset based on the first geophysical survey acquisition geometry, processing the first synthetic geophysical dataset for obtaining a first simulated image of the subsurface of the region of interest using a geophysical processing algorithm and an a priori subsurface model, and calculating a first objective function dependent of at least a first quality index of the first simulated image of the subsurface of the region of interest.

A method is described for generating a reservoir property model based on the quality of a seismic inversion product. The method may include receiving a seismic inversion product volume, a seismic attribute volume, and well data from wells drilled in a subsurface volume of interest; identifying collocated cells in the seismic volumes which correspond to the well data; creating attribute vectors from the seismic volumes in each of the collocated cells and a range of neighboring cells; calculating a seismic inversion error magnitude property at the collocated cells; training a data analytics method to predict the observed seismic inversion error magnitude property; verifying that the data analytics method accurately predicts the seismic inversion error magnitude using cross-validation; generating an inversion quality volume; and generating the reservoir property model based on the inversion quality volume. The method may be executed by a computer system.

A process for seismic imaging of a subterranean geological formation includes generating a source wavefield from seismic data representing a subterranean formation. The process includes generating a receiver wavefield from the seismic data representing the subterranean formation. The process includes decomposing the source wavefield to extract a source depth component and decomposing the receiver wavefield to extract a receiver depth component. The process includes applying a transform to each of the source depth component and the receiver depth component. The process includes combining the source depth component and the receiver depth component to generate an imaging condition. The process includes extracting a low-frequency term from the imaging condition to generate a wave-path tracking data, generating a wave path from the wave-path tracking data, and rendering a seismic image of at least a portion of the subterranean geological formation from the generated wave path.

A method is described for generating a reservoir property model based on the quality of a seismic inversion product. The method may include receiving a seismic inversion product volume, a seismic attribute volume, and well data from wells drilled in a subsurface volume of interest; identifying collocated cells in the seismic volumes which correspond to the well data; creating attribute vectors from the seismic volumes in each of the collocated cells and a range of neighboring cells; calculating a seismic inversion error magnitude property at the collocated cells; training a data analytics method to predict the observed seismic inversion error magnitude property; verifying that the data analytics method accurately predicts the seismic inversion error magnitude using cross-validation; generating an inversion quality volume; and generating the reservoir property model based on the inversion quality volume. The method may be executed by a computer system.

A method and system are described for creating a subsurface model. In this method, a watertight framework may be adjusted to lessen the ill-formed mesh elements. The method collapses mesh elements and/or eliminates nodes enhance the watertight framework and subsequent subsurface model. The resulting subsurface model may be used in reservoir simulations and hydrocarbon operations.

An illustrative geologic modeling method may comprise: obtaining a geologic model representing a subsurface region in physical space, the subsurface region being divided into multiple zones; sequentially generating a physical space simulation mesh for each of said multiple zones by: (a) mapping a current zone of the physical space geologic model to a current zone of a design space model representing a current zone of an unfaulted subsurface region; (b) gridding the design space model to obtain a design space mesh; (c) partitioning cells in the current zone of the design space mesh with faults mapped from the current zone of the physical space geologic model, thereby obtaining a partitioned design space mesh for the current zone; and (d) reverse mapping the partitioned design space mesh for the current zone to the physical space for the current zone.