Abstract:
Target objects are simulated using different triangle mesh sizes to improve processing performance. To perform the simulation, a seed point for the target object within a constraint volume is determined, the seed point representing a vertex of a first triangle forming part of the target object. One or more hexagonal orbits of triangles adjacent the first triangle are propagated, whereby the hexagonal orbits of triangles form the target object. The size of each triangle is determined based upon dimensions of the target object, and the target object is generated.
Abstract:
The disclosed embodiments include a method, apparatus, and computer program product for modifying a three-dimensional geocellular model. For example, one disclosed embodiment includes a system that includes at least one processor and at least one memory coupled to the at least one processor. The memory stores instructions that when executed by the at least one processor performs operations that includes loading into memory a three-dimensional geocellular model that corresponds to a two-dimensional geological model. The operations include determining a portion of the three-dimensional geocellular model affected by a change to the two-dimensional geological model and performing a local update to the portion of the three-dimensional geocellular model affected by the change.
Abstract:
A computing device facilitates the organization of a plurality of three-dimensional geological data realizations into respective one-dimensional arrays of geological property values, with each geological property value corresponding to a three-dimensional grid location of a respective three-dimensional geological data realization. The computing device then facilitates the grouping of the one-dimensional arrays into two or more array clusters based on a comparison of geometric locations of the geological property values within the respective arrays, and selects at least one of the plurality of three-dimensional geological data realizations for each of the two or more array clusters. The selected data realizations are then provided at a user interface.
Abstract:
A method to generate a global grid may include storing at least one data structure representing a plurality of fault blocks associated with one or more faults in a geographic formation; selecting two fault blocks associated with a fault of the one or more faults; changing the position of a first of the two fault blocks in the at least one data structure representative of a shift of the first fault block towards the other fault block of the two fault blocks to position the center of gravity of a fault boundary of the first fault block with the center of gravity of a fault boundary of the other fault block; aligning the first fault block with the other fault block according to a permitted level of conflict between fault blocks; and updating the at least one data structure to indicate a merging of the two selected fault blocks.
Abstract:
In various examples, a method includes storing one or more data structures on a storage device, the one or more data structures identifying a plurality of faults in a geographical formation and a plurality of fault blocks on either side of the plurality of faults in the geographic formation; for each pair of faults blocks on opposite sides of a fault identified in the one or more data structures: determining, using at least one processor, a fault polygon of a respective pair of fault blocks with respect to a fault of the plurality of faults; and calculating a matching factor between the respective pair of fault blocks based on the fault polygon; selecting a pair of fault blocks to merge based on the calculated matching factor; and updating the one or more data structures to indicate the selected pair of fault blocks has been merged.
Abstract:
In some embodiments, a method for computing, by a volume data processor, volumetrics of a subsurface region without gridlines associated with the subsurface region comprises creating, in the volume data processor, a geometry representing the subsurface region and first bounding box about the geometry, computing a first probability that a group of sampled points inside the first bounding box are inside the geometry, and computing a gross rock volume (GRV) of the geometry by multiplying the first probability by a volume of the first bounding box.
Abstract:
A method of predicting rock properties at a selectable scale is provided, including receiving coordinates of locations of respective sample points, receiving measurement data associated with measurements or measurement interpretations for each sample point, receiving for each sample point a scale that indicates the scale used to obtain the measurements and/or measurement interpretations, wherein different scales are received for different sample points. A deep neural network (DNN) is trained by applying the received coordinates, measurement data, and scale associated with each sample point and associating the sample point with a rock property as a function of the coordinates, measurement data, and scale applied for the sample point. The DNN is configured to generate rock property data for a received request point having coordinates and a selectable scale, wherein the rock property data is determined for the request point as a function of the coordinates and the selectable scale.
Abstract:
A reservoir model for values of a formation property is simulated using a turning bands method with distributed computing. A distributed computing system simulates the reservoir on separate machines in parallel in several stages. First, line distributions are simulated independently on turning bands. The reservoir model is partitioned into tiles and unconditional simulations are run on each tile in parallel using the corresponding simulated turning bands. The unconditional simulations within each tile are conditioned on known formation values to generate conditional simulations. Conditional simulations are aggregated across tiles to create the simulated reservoir model.
Abstract:
A method for creating a seamless scalable geological model may comprise identifying one or more geological scales, establishing a geological tied system, identifying one or more graphical resolution levels for each of the one or more geological scales, constructing the seamless scalable geological model, and producing a post-process model. A system for creating a seamless scalable geological model may comprise an information handling system, which may comprise a random access memory, a graphics module, a main memory, a secondary memory, and one or more processors configured to run a seamless scalable geological model software.
Abstract:
Fracture networks are simulated using a large triangle mesh size for large fractures and a smaller triangle mesh size for small fractures. Input data defining parameters of one or more fractures are input, the fractures being comprised of a triangle mesh. A first triangle mesh size for the fractures is determined based upon the input data. A second smaller triangle mesh size is then determined based upon the input data. The fracture network is then simulated using the large and small triangle mesh sizes.