G01V2210/642

Modeling reservoir flow and transport processes in reservoir simulation

Orthogonal unstructured grids are automatically constructed for a field or reservoir model with two types of internal boundaries: complex wells and faults, or other discontinuities. The methodology is used to constructed simulation grids for reservoirs or fields which contains both complex fault planes and multi-lateral wells. A hierarchical grid point generation, prioritization, conflict point removal system is provided enabling the use of unconstrained Delaunay triangulation. High-quality orthogonal unstructured grids are produced with good convergence properties for reservoir simulation.

MODELING AND SIMULATING FAULTS IN SUBTERRANEAN FORMATIONS
20220163692 · 2022-05-26 ·

Methods for modeling and simulating fractured subterranean volumes include a method including obtaining geological data representing a subterranean volume, generating a structural model thereof in depositional space and in structural space. The method includes selecting a first cell and a second cell in the model, the first and second cells being juxtaposed in geological space and defining a fault face where the first and second cells are intersected by a fault, identifying a first point on the fault face, and calculating slip curves. Respective slip curves originate at the point and extend across the fault in geological space to a respective second point of a plurality of second points. The second points are co-located with the first point in the depositional space. The method includes calculating fault rock properties at the first point based on the slip curves and adjusting the model to include the fault rock properties.

Multi-Z horizon interpretation and editing within seismic data

Systems and methods for editing multi-Z horizons interpreted from seismic data are provided. A multi-Z horizon having a plurality of surfaces is visualized within a two-dimensional (2D) representation of seismic data displayed via a graphical user interface (GUI) of an application executable at a computing device of a user. Input is received via the GUI from the user for editing one or more of the plurality of surfaces of the multi-Z horizon within a current view of the displayed 2D representation of the seismic data. A location of the received input relative to each of the plurality of surfaces within the current view is determined. The one or more surfaces of the multi-Z horizon are modified based on the location of the received input within the current view. The visualization of the multi-Z horizon within the GUI is updated, based on the modified one or more surfaces.

System and method for subsurface structural interpretation

A method is described for assessing subsurface structure uncertainty based on at least one subsurface horizon. The method calculates seismic continuity attributes to determine a mappability of the subsurface horizon(s); determines horizontal uncertainty for each fault in vertical uncertainty for each horizon; generates probabilistic scenarios for a subsurface geometry for at least one conceptual model; and generates a map of geological model uncertainty based on the probabilistic scenarios. In some embodiments, the probabilistic scenarios are stochastic simulations. In some embodiments, generating a map of geological model uncertainty is based on information entropy. The method may be executed by a computer system.

IMPLICIT PROPERTY MODELING

A method of simulating a process of a geological structure includes obtaining a first digital model including structural data representing a geological structure. The method also includes selecting at least one marching technique based in part on a grid dimension and a grid cell shape of a grid on the first digital model. The method further includes applying the at least one marching technique to at least a portion of the structural data of the first digital model to identify at least some boundary data. The method further includes populating a second digital model based in part on the first digital model, a property, and the boundary data. The method further includes simulating a process of the geological structure using the second digital model.

Determining rupture envelopes of a fault system

Provided are a method, computer-readable medium, and a system for determining rupture envelopes for a fault system. The method includes obtaining a representation that depicts one or more faults in a region of the earth as triangulated surfaces; selecting variables from among parameters comprising stress ratio, orientation of far field stress maximum principal stress, intermediate principal stress, minimum principal stress for the far field stress, and sliding friction and cohesion of the fault system; determining a strain energy of a triangular element based on a friction coefficient, a normal stress on the triangular element, and a cohesion for the variables; summing the strain energy of each triangle in the triangulated surfaces to yield an effective shear strain energy; extracting one or more iso-surfaces of the effective shear strain energy based on the summing; and creating rupture envelopes for specific values of the effective shear strain energy.

AUTOMATED FAULT UNCERTAINTY ANALYSIS IN HYDROCARBON EXPLORATION
20220018982 · 2022-01-20 ·

A system includes a processor and a memory. The memory includes instructions that are executable by the processor to access a plurality of seismic images of a subterranean formation in a first geological area. The instructions are also executable to generate a plurality of fault estimates from each of the plurality of seismic images. Further, the instructions are executable to generate a processed seismic image of the first geological area by normalizing and merging the plurality of seismic images and the plurality of fault estimates. Additionally, the instructions are executable to generate a statistical fault uncertainty volume of the first geological area using the processed seismic image. Furthermore, the instructions are executable to control a drilling operation in the first geological area using the statistical fault uncertainty volume of the first geological area.

Geologic stratigraphy via implicit and jump functions

A method can include receiving a mesh that represents a geologic environment where the mesh includes elements; receiving location information for a discontinuity in the geologic environment; based at least in part on the location information, defining enrichment equations for a portion of the elements where the enrichment equations include a jump function that models the discontinuity; solving a system of equations for an implicit function where the system of equations includes the enrichment equations; and, based at least in part on the solving, outputting values for the implicit function with respect to at least a portion of the mesh.

Method for producing a geological vector model
11163079 · 2021-11-02 · ·

The method for producing a geological vector model (GVM) based on seismic data includes the step of forming a Model-Grid, which includes creating a network of small units, called patches, to which a relative geological age is assigned, a set of patches with the same relative geological age corresponding to a geological layer, called the geological horizon. The method includes the step of sampling the Model-Grid in two directions perpendicular to each other, enabling the Model-Grid to be sampled in a plurality of vertical planes and the step of forming two-dimensional geological vector models (2DGVM). The step of forming includes forming two-dimensional horizons (Hb) with distinct relative geological ages using the patches belonging to each sampled plane, each two-dimensional geological vector model (2DGVM) corresponding to a vertical plane originating from the sampling of the Model-Grid.

FREQUENCY-DEPENDENT MACHINE LEARNING MODEL IN SEISMIC INTERPRETATION
20230288594 · 2023-09-14 ·

Frequency-dependent machine-learning (ML) models can be used to interpret seismic data. A system can apply spectral decomposition to pre-processed training data to generate frequency-dependent training data of two or more frequencies. The system can train two or more ML models using the frequency-dependent training data. Subsequent to training the two or more ML models, the system can apply the two or more ML models to seismic data to generate two or more subterranean feature probability maps. The system can perform an analysis of aleatoric uncertainty on the two or more subterranean feature probability maps to create an uncertainty map for aleatoric uncertainty. Additionally, the system can generate a filtered subterranean feature probability map based on the uncertainty map for aleatoric uncertainty.