Abstract: Systems and methods for estimating a likelihood of an object element in a given position in a subsurface volume of interest are disclosed. Exemplary implementations may: obtain target subsurface data from the subsurface volume of interest; obtain an object element set corresponding to the subsurface volume of interest; generate correlation values as a function of position in the subsurface volume of interest by applying the object filters to the target subsurface data; and generate object element likelihood values by applying the object templates to positions in the subsurface volume of interest corresponding to the correlation values.

Abstract: A computer implemented method for identifying reservoir facies in a subsurface region includes obtaining a set of seismic data points of both petrophysical and geophysical parameters relating to the subsurface region, identifying one or more correlated clusters of petrophysical parameters, generating, from the one or more correlated clusters of petrophysical parameters, one or more corresponding multi-dimensional clusters of seismic data points, storing, in a facies database, a multi-dimensional cluster center point for at least one multi-dimensional clusters, and recursively splitting the multi-dimensional clusters into distinct sub-clusters of seismic data points corresponding to facies types.

Abstract: Systems and methods for estimating a likelihood of an object element in a given position in a subsurface volume of interest are disclosed. Exemplary implementations may: obtain target subsurface data from the subsurface volume of interest; obtain an object element set corresponding to the subsurface volume of interest; generate correlation values as a function of position in the subsurface volume of interest by applying the object filters to the target subsurface data; and generate object element likelihood values by applying the object templates to positions in the subsurface volume of interest corresponding to the correlation values.

Abstract: A computer implemented method for identifying reservoir facies in a subsurface region includes obtaining a set of seismic data points of both petrophysical and geophysical parameters relating to the subsurface region, identifying one or more correlated clusters of petrophysical parameters, generating, from the one or more correlated clusters of petrophysical parameters, one or more corresponding multi-dimensional clusters of seismic data points, storing, in a facies database, a multi-dimensional cluster center point for at least one multi-dimensional clusters, and recursively splitting the multi-dimensional clusters into distinct sub-clusters of seismic data points corresponding to facies types.

Abstract: Methods and systems for trend modeling of subsurface properties are disclosed. One method includes defining a stratigraphic grid of a subsurface volume, the stratigraphic grid including a plurality of columns and a plurality of layers. The method further includes determining, for each layer or column, an initial average property value based at least in part on well data in the subsurface volume and a confidence interval around that initial average property value defining a range of likely values for a target average property value. The method also includes receiving one or more user-defined edits to the initial average property value in one or more of the layers or columns, the one or more edits resulting in the modeled target average property value, and determining whether the modeled target average property value falls within the confidence interval.

Abstract: Geological systems are automatically categorized based on one or more characteristics. Datasets from one or more sources related to a space of a geological system are transformed, cropped and analyzed using lacunarity-based statistical methodologies. The one or more analyzed datasets describe characteristics of the transformed dataset within the space of the geological system. The characteristics of the distribution of the transformed dataset are compared with one or more characteristics of one or more previously categorized geological systems. The space within the geological system is categorized based upon an indication that the characteristics of the transformed data set of the space within the geological system is similar to the characteristics of one or more previously categorized geological systems.