METHODS OF GENERATING A PARAMETER REALIZATION FOR A SUBSURFACE PARAMETER

    公开(公告)号:US20240210583A1

    公开(公告)日:2024-06-27

    申请号:US18507295

    申请日:2023-11-13

    CPC classification number: G01V1/282 G06F17/18 G01V2210/6242 G01V2210/667

    Abstract: Methods of generating a parameter realization, for a subsurface parameter, as a function of depth within a subsurface region are disclosed herein. The methods include dividing a subsurface parameter profile for the subsurface region into a plurality of adjacent stratigraphic units. The methods also include splitting each stratigraphic unit of the plurality of adjacent stratigraphic units into a plurality of stratigraphic unit layers. The methods further include determining a layer parameter value range for each stratigraphic unit layer of the plurality of stratigraphic unit layers and for each stratigraphic unit. The methods also include, within each stratigraphic unit layer, selecting a corresponding layer parameter value from within the layer parameter value range. The methods further include generating the parameter realization by assigning the corresponding layer parameter value to the parameter realization for a corresponding layer depth range of each stratigraphic unit layer.

    METHOD AND SYSTEM TO CALIBRATE SUBSURFACE EARTH STRESSES IN A GEOCELLULAR MODEL

    公开(公告)号:US20240272327A1

    公开(公告)日:2024-08-15

    申请号:US18411288

    申请日:2024-01-12

    CPC classification number: G01V20/00 G06F30/13

    Abstract: A methodology for estimating stresses in the subsurface for the generation of a three dimensional (3D) mechanical earth model is provided. The method is executed via a processor of a computing system. The method includes generating a synthetic principal horizontal stress profile representative of a one-dimensional mechanical earth model (1D MEM) based on simplification that all formations are elastically isotropic. The method also includes combining the isotropically generated synthetic principal horizontal stress profile with an additional data-driven functional relationship for anisotropic formations to generate a global predictive conditional relationship based on a lithology dependent cutoff. The method also further includes generating a three-dimensional volume-based mechanical earth model using the global predictive conditional relationship.

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