Local updating of 3D geocellular model

    公开(公告)号:US10529144B2

    公开(公告)日:2020-01-07

    申请号:US14891308

    申请日:2013-08-23

    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.

    GLOBAL GRID BUILDING UNFAULTING SEQUENCE FOR COMPLEX FAULT-NETWORK TOPOLOGIES
    25.
    发明申请
    GLOBAL GRID BUILDING UNFAULTING SEQUENCE FOR COMPLEX FAULT-NETWORK TOPOLOGIES 审中-公开
    全球网格构建复杂故障网络拓扑的不均匀序列

    公开(公告)号:US20160216403A1

    公开(公告)日:2016-07-28

    申请号:US14913883

    申请日:2013-11-26

    CPC classification number: G01V99/005

    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 translation: 在各种示例中,一种方法包括将一个或多个数据结构存储在存储设备上,所述一个或多个数据结构标识地理区域中的多个故障以及地理上的多个故障的任一侧上的多个故障块 形成; 对于在所述一个或多个数据结构中识别的故障的相对侧上的每对故障块,确定相对于所述多个故障的故障的相应故障块对的至少一个处理器的故障多边形; 以及基于所述故障多边形计算所述各对故障块之间的匹配因子; 根据计算的匹配因子选择一对故障块进行合并; 并且更新所述一个或多个数据结构以指示所选择的一对故障块已被合并。

    GRIDLESS VOLUMETRIC COMPUTATION
    26.
    发明公开

    公开(公告)号:US20240192400A1

    公开(公告)日:2024-06-13

    申请号:US18079655

    申请日:2022-12-12

    CPC classification number: G01V99/005 E21B49/00 E21B2200/20

    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.

    BUILDING SCALABLE GEOLOGICAL PROPERTY MODELS USING MACHINE LEARNING ALGORITHMS

    公开(公告)号:US20230367031A1

    公开(公告)日:2023-11-16

    申请号:US17585441

    申请日:2019-12-03

    CPC classification number: G01V99/005 G06N3/091

    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.

    RESERVOIR TURNING BANDS SIMULATION WITH DISTRIBUTED COMPUTING

    公开(公告)号:US20220221615A1

    公开(公告)日:2022-07-14

    申请号:US17595654

    申请日:2020-02-14

    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.

    Seamless Scaling Geomodeling
    29.
    发明申请

    公开(公告)号:US20210225071A1

    公开(公告)日:2021-07-22

    申请号:US16753945

    申请日:2018-12-20

    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.

Patent Agency Ranking