首页> 外国专利> MACHINE LEARNING APPROACH FOR IDENTIFYING MUD AND FORMATION PARAMETERS BASED ON MEASUREMENTS MADE BY AN ELECTROMAGNETIC IMAGER TOOL

MACHINE LEARNING APPROACH FOR IDENTIFYING MUD AND FORMATION PARAMETERS BASED ON MEASUREMENTS MADE BY AN ELECTROMAGNETIC IMAGER TOOL

机译:基于电磁成像器工具进行测量的机器学习方法

摘要

Aspects of the subject technology relate to systems and methods for identifying values of mud and formation parameters based on measurements gathered by an electromagnetic imager tool through machine learning. One or more regression functions that model mud and formation parameters capable of being identified through an electromagnetic imager tool as a function of possible tool measurements of the electromagnetic imager tool can be generated using a known dataset associated with the electromagnetic imager tool. One or more tool measurements obtained by the electromagnetic imager tool operating to log a wellbore can be gathered. As follows, one or more values of the mud and formation parameters can be identified by applying the one or more regression functions to the one or more tool measurements.
机译:主题技术的方面涉及基于通过机器学习通过电磁成像器工具收集的测量来识别泥浆和形成参数值的系统和方法。可以使用与电磁成像器工具的可能刀具测量的功能识别的模型泥浆和形成参数的一个或多个回归函数可以使用与电磁成像器工具相关联的已知数据集来产生作为电磁成像器工具的可能刀具测量的函数。可以收集通过用于记录井筒的电磁成像器工具获得的一个或多个刀具测量。如下,可以通过将一个或多个回归函数应用于一个或多个刀具测量来识别泥浆和形成参数的一个或多个值。

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