Modeling Method, Device, Equipment and Storage Medium for Continuous Variables in Meandering Rivers

By establishing a simulation grid based on logging data and a continuous variable training image of the bend river in oil and gas exploration, the modeling problem of complex spatial structures and geometric forms is solved, and efficient multi-point geological modeling of continuous variables is achieved, improving the continuity and accuracy of modeling.

CN114722649BActive Publication Date: 2025-05-27PETROCHINA CO LTD
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Patent Information

Application Number
CN202110009594.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2021-01-05
Publication Date
2025-05-27
Estimated Expiration
2041-01-05

AI Technical Summary

Technical Problem

The prior art is difficult to effectively characterize complex spatial structures and geometric forms, and is not suitable for multi-point geological modeling of continuous variables.

Method used

By establishing a simulation grid based on logging data, and using geological understanding and sedimentary laws to establish a continuous variable training image of the Quliuhe River, setting up multiple data filters, data templates scan training images and grid nodes, obtaining training modes, and simulations are carried out under the constraints of soft data trends.

Benefits of technology

Under the guidance of geological mode, a multi-point geological statistical model of continuous variables that can characterize complex spatial structures and geometric forms is realized, and the problem of poor continuity of geological modeling without trend constraints is overcome.

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Abstract

An embodiment of the present invention provides a method, device, equipment and storage medium for continuous variable modeling of meandering rivers. The method includes: establishing a training image of continuous variables of meandering rivers according to simulation grids; scanning the training image of continuous variables of meandering rivers through a data template to obtain a plurality of training patterns; for each empty grid node in the simulation grids, scanning the grid node through the data template, and under the constraint of soft data trend, obtaining the training pattern of the grid node, determining the training pattern corresponding to the training pattern of the grid node among the plurality of training patterns of the meandering river training image, and referring the determined training pattern to the grid node to complete the simulation of the grid node. This solution can characterize complex spatial structures and geometric forms, and can better reflect the geological sedimentation law of meandering rivers; it is realized under the constraint of soft data trend, which is conducive to overcoming the disadvantage of poor channel continuity of multi-point geostatistics without trend constraint.
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