US-12618997-B2 - Reducing effect of motion on NMR measurements

US12618997B2US 12618997 B2US12618997 B2US 12618997B2US-12618997-B2

Abstract

Systems and methods of removing motion-induced noise from datasets from a NMR tool. The method includes steps of generating an echo train from each dataset and identifying one or more datasets that were collected while a motion of the tool was below a predetermined threshold as stationary datasets. Datasets not identified as stationary are identified as moving datasets. The method further performs steps of building a statistical model of the echo train, estimating a motion-induced noise component of the echo train using the statistical model and the stationary datasets, calculating a distortion of the echo train for each datasets using a physical model of the tool within the wellbore, estimating a true signal of each moving dataset based on the estimated motion-induced noise component and the respective calculated distortion, estimating a true signal of each stationary dataset based on the respective calculated distortion, and combining the estimated true signals of the moving datasets and the stationary datasets to produce a superset of clean NMR data.

Inventors

Jie Yang

Assignees

HALLIBURTON ENERGY SERVICES, INC.

Dates

Publication Date: 20260505
Application Date: 20230605

Claims (15)

1 . A method of removing motion-induced noise, comprising: operating a nuclear magnetic resonance (NMR) tool in a wellbore to obtain a plurality of datasets, each dataset associated with a respective depth in the wellbore; generating corresponding echo trains from each dataset; identifying one or more datasets that were collected while a motion of the tool was below a predetermined threshold as stationary datasets, wherein datasets not identified as stationary are identified as moving datasets; building a statistical model of the echo trains based on the stationary datasets and the moving datasets; estimating a motion-induced noise component of the echo trains using the statistical model and the stationary datasets; calculating a distortion of the echo trains for each dataset of the plurality of datasets using a physical model of the tool within the wellbore; estimating a true signal of each moving dataset based on the estimated motion-induced noise component and the respective calculated distortion; estimating a true signal of each stationary dataset based on the respective calculated distortion; and combining the estimated true signals of the moving datasets and the stationary datasets to produce a superset of clean NMR data.
2 . The method of claim 1 , wherein: the datasets comprises one or more of a NMR magnetic field measurement, a depth parameter, and a motion parameter; and of identifying one or more stationary datasets comprises an evaluation of one or more of the depth parameter and the motion parameter.
3 . The method of claim 1 , wherein estimating the motion-induced noise component of the echo train is based in part on a comparison of a portion of the echo trains of the moving datasets to a portion of the echo trains of the stationary datasets.
4 . The method of claim 1 , further comprising a step of analyzing a formation surrounding the wellbore based in part on the superset of clean NMR data.
5 . The method of claim 1 , wherein each signal of the true signal of each moving dataset and the true signal of each stationary dataset comprises a single T2 value derived from the respective echo train from each of the datasets.
6 . A non-transitory computer-readable storage medium comprising instructions for removing motion-induced noise that, when loaded into a processor, cause the processor to execute steps of: operating a nuclear magnetic resonance (NMR) tool in a wellbore to obtain a plurality of datasets, each dataset associated with a respective depth in a wellbore; generating corresponding echo trains from each dataset; identifying one or more datasets that were collected while a motion of the tool was below a predetermined threshold as stationary datasets, wherein datasets not identified as stationary are identified as moving datasets; building a statistical model of the echo trains based on the stationary datasets and the moving datasets; estimating a motion-induced noise component of the echo train using the statistical model and the stationary datasets; calculating a distortion of the echo trains for each dataset of the plurality of datasets using a physical model of the tool within the wellbore; estimating a true signal of each moving dataset based on the estimated motion-induced noise component and the respective calculated distortion; estimating a true signal of each stationary dataset based on the respective calculated distortion; and combining the estimated true signals of the moving datasets and the stationary datasets to produce a superset of clean NMR data.
7 . The memory of claim 6 , wherein: the dataset comprises one or more of a NMR magnetic field measurement, a depth parameter, and a motion parameter; and of identifying one or more stationary datasets comprises an evaluation of one or more of the depth parameter and the motion parameter.
8 . The memory of claim 6 , wherein estimating the motion-induced noise component of the echo train is based in part on a comparison of a portion of the echo trains of the moving datasets to a portion of the echo trains of the stationary datasets.
9 . The memory of claim 6 , further comprising a step of analyzing a formation surrounding the wellbore based in part on the superset of clean NMR data.
10 . The memory of claim 6 , wherein each signal of the true signal of each moving dataset and the true signal of each stationary dataset comprises a single T2 value derived from the respective echo train from each of the datasets.
11 . A system for removing motion-induced noise, comprising a processor and a non-transitory computer-readable storage medium coupled to the processor and comprising instructions that, when loaded into the processor, cause the processor to execute steps of: operating a nuclear magnetic resonance (NMR) tool in a wellbore to obtain a plurality of datasets, each dataset associated with a respective depth in the wellbore; generating corresponding echo trains from each dataset; identifying one or more datasets that were collected while a motion of the tool was below a predetermined threshold as stationary datasets, wherein datasets not identified as stationary are identified as moving datasets; building a statistical model of the echo trains based on the stationary datasets and the moving datasets; estimating a motion-induced noise component of the echo train using the statistical model and the stationary datasets; calculating a distortion of the echo train for each dataset of the plurality of datasets using a physical model of the tool within the wellbore; estimating a true signal of each moving dataset based on the estimated motion-induced noise component and the respective calculated distortion; estimating a true signal of each stationary dataset based on the respective calculated distortion; and combining the estimated true signals of the moving datasets and the stationary datasets to produce a superset of clean NMR data.
12 . The system of claim 11 , wherein: the dataset comprises one or more of a NMR magnetic field measurement, a depth parameter, and a motion parameter; and the instructions further cause the processor to execute identifying one or more stationary datasets comprises an evaluation of one or more of the depth parameter and the motion parameter.
13 . The system of claim 11 , wherein the instructions further cause the processor to execute estimating the motion-induced noise component of the echo train is based in part on a comparison of a portion of the echo trains of the moving datasets to a portion of the echo trains of the stationary datasets.
14 . The system of claim 11 , further comprising a step of analyzing a formation surrounding the wellbore based in part on the superset of clean NMR data.
15 . The system of claim 11 , wherein each signal of the true signal of each moving dataset and the true signal of each stationary dataset comprises a single T2 value derived from the respective echo train from each of the datasets.

Description

TECHNICAL FIELD The present technology pertains to downhole sensing systems and, more particularly, to nuclear magnetic resonance (NMR) tools that emit and detect acoustic signals so as to characterize the substrate surrounding a wellbore. BACKGROUND Logging while drilling (LWD) is a technique of conveying well logging tools into the well borehole downhole as part of the bottom hole assembly (BHA). LWD refers to measurements concerning the geological formation made while drilling. Data and measurements can be transmitted to the surface, e.g., via a mud pulser, while the LWD tool is still in the borehole, referred to as “real-time data,” or downloaded from the LWD tool after it is pulled out of hole, referred to as “memory data.” NMR technology has become a powerful tool for obtaining well-logging data. The method mainly relies on the Carr-Purcell-Meiboom-Gill (CPMG) sequence to measure the T2 decay signal and, by inverting the time-domain signal, to estimate porosity, permeability, pore size distribution, and movable fluid saturation of a formation at various depths. Sensor data usually includes noise induced by motion of the tool while making measurements. Typically, a simple physical model is used to compensate for the motion effect. When the sensor signal is on the same order of magnitude as the motion-induced noise, as is common in NMR tools, a simple physical model does not accurately handle the actual motion dynamics. BRIEF DESCRIPTION OF THE DRAWINGS In order to describe the manner in which the features and advantages of this disclosure can be obtained, a more particular description is provided with reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only exemplary embodiments of the disclosure and are not therefore to be considered to be limiting of its scope, the principles herein are described and explained with additional specificity and detail through the use of the accompanying drawings in which: FIG. 1 illustrates an example of a well system, in accordance with various aspects of the subject technology; and FIG. 2 illustrates an example of movement of a tool down a borehole, in accordance with various aspects of the subject technology. FIG. 3 is a plot of an example NMR echo train, in accordance with various aspects of the subject technology. FIG. 4 is a plot of an example echo train received from an NMR tool, in accordance with various aspects of the subject technology. FIG. 5 is a plot of an example of spectra from stationary data and corrected moving data compared to the true underlying signal, in accordance with various aspects of the subject technology. FIG. 6 is a flowchart of a method of removing noise from wellbore datasets, in accordance with various aspects of the subject technology. DETAILED DESCRIPTION Various embodiments of the disclosure are discussed in detail below. While specific implementations are discussed, it should be understood that this is done for illustration purposes only. A person skilled in the relevant art will recognize that other components and configurations may be used without parting from the spirit and scope of the disclosure. Additional features and advantages of the disclosure will be set forth in the description which follows, and in part will be obvious from the description, or can be learned by practice of the principles disclosed herein. The features and advantages of the disclosure can be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. These and other features of the disclosure will become more fully apparent from the following description and appended claims or can be learned by the practice of the principles set forth herein. It will be appreciated that for simplicity and clarity of illustration, where appropriate, reference numerals have been repeated among the different figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in order to provide a thorough understanding of the embodiments described herein. However, it will be understood by those of ordinary skill in the art that the embodiments described herein can be practiced without these specific details. In other instances, methods, procedures, and components have not been described in detail so as not to obscure the related relevant feature being described. The drawings are not necessarily to scale and the proportions of certain parts may be exaggerated to better illustrate details and features. The description is not to be considered as limiting the scope of the embodiments described herein. One method used to analyze the structure and composition of the subterranean substrate in which a wellbore has been drilled is to lower an NMR tool into the wellbore while drilling. The NMR data usually includes noise on the same order of magnitude as the signal, wherein the noise can be decomposed into mot