Abstract: A method for estimating a pipe property may include disposing an electromagnetic (EM) logging tool in a wellbore. The EM logging tool may comprise a transmitter disposed on the EM logging tool and a receiver disposed on the EM logging tool. The method may further include transmitting an electromagnetic field from the transmitter into a tubular string to energize the tubular string with the electromagnetic field thereby producing an eddy current that emanates from the tubular string. The method may further include measuring the eddy current in the tubular string with the receiver on at least one channel to obtain one or more measurements from the EM logging tool. The method may further include forming an EM log from the one or more measurements, forming a relationship between a set of one or more previously analyzed measurements and at least one pipe property, and estimating the at least one pipe property from the formed relationship and the one or more measurements from the EM logging tool.

Abstract: Methods and systems for inspecting the integrity of multiple nested tubulars are included herein. A method for inspecting the integrity of multiple nested tubulars can comprise conveying an electromagnetic pipe inspection tool inside the innermost tubular of the multiple nested tubulars; taking measurements of the multiple nested tubulars with the electromagnetic pipe inspection tool; arranging the measurements into a response image representative of the tool response to the tubular integrity properties of the multiple nested tubulars; and feeding the response image to a pre-trained deep neural network (DNN) to produce a processed image, wherein the DNN comprises at least one convolutional layer, and wherein the processed image comprises a representation of the tubular integrity property of each individual tubular of the multiple nested tubulars.

Abstract: A method and non-transitory storage computer-readable medium for performing a neural operator on one or more wellbore measurements. The method may comprise o obtaining one or more measurements, performing a measurement normalization on the one or more measurements to form one or more normalized measurements, forming a material function with the one or more normalized measurements, and forming a neural operator generated physical response with a neural operator and the material function. The method may further comprise forming a beamforming map with the one or more measurements, and forming a neural operator leak source location map with a neural operator and the one or more measurements.

Abstract: Described herein are systems and techniques for monitoring for monitoring and evaluating conditions associated with a wellbore and wellbore operations that use neural operators instead of computationally intensive iterative differential equations. Such systems and techniques allow for determinations to be made as operations associated with a wellbore are performed. Instead of having to wait for computationally intensive tasks to be performed or take risks of proceeding with a wellbore operation without real-time evaluations being performed, these wellbore operations may be continued while determinations are timely made, thus improving operation of computing systems that perform evaluations and that make decisions regarding safely and efficiently performing wellbore operations such as drilling a wellbore, cementing wellbore casings in place, or injecting fluids into formations of the Earth.

Abstract: A system for inspecting a tubular may comprise an electromagnetic (EM) logging tool and information handling system. The EM logging tool may further include a mandrel, one or more sensor pads attached to the mandrel by one or more extendable arms, and one or more partial saturation eddy current sensors disposed on each of the one or more sensor pads.

Abstract: A method for identifying a collar using machine learning may include acquiring one or more measurements from one or more depth points within a wellbore including a tubular string, training a machine learning model using a training dataset to create a trained machine learning model, and identifying at least one hyperparameter using the trained machine learning model. The method may further include creating a synthetic model, wherein the synthetic model is defined by one or more pipe attributes, minimizing a mismatch between the one or more measurements and the synthetic model utilizing the at least one hyperparameter, updating the synthetic model to form an updated synthetic model, and repeating the minimizing the mismatch with the updated synthetic model until a threshold is met.

Abstract: Methods and systems for inspecting the integrity of multiple nested tubulars are provided. A method for inspecting the integrity of multiple nested tubulars can comprise conveying an electromagnetic pipe inspection tool inside the innermost tubular of the multiple nested tubulars; taking measurements of the multiple nested tubulars with the electromagnetic pipe inspection tool; inverting the measurements for a tubular integrity property of each individual tubular of the multiple nested tubulars to provide inverted tubular integrity properties; arranging the inverted integrity properties into an inverted image representative of an estimated tubular integrity property of each individual tubular; and feeding the inverted image to a pre-trained deep neural network (DNN) to produce a corrected image, wherein the DNN comprises at least one convolutional layer, and wherein the corrected image comprises a representation of the tubular integrity property of each individual tubular of the multiple nested tubulars.

Abstract: Aspects of the subject technology relate to systems, methods, and computer-readable media for accounting for artifacts in pipe measurements made by an electromagnetic pipe inspection tool. Measurements gathered in a plurality of pipes across different depth points are accessed. Initial estimates of an attribute associated with the plurality of pipes are made for each pipe and a total estimate of the attribute for the plurality of pipes as a whole are made across the different depth points. Corresponding initial estimates of the attribute for each pipe are filtered to remove an artifact present in at least one of the corresponding initial estimates while the total estimate is preserved. Corresponding final estimates of the attribute for each pipe are determined based on both the measurements and corresponding filtered initial estimates of the attribute for each pipe. Integrity of each pipe can be determined based on the corresponding final estimates of the attribute.

Abstract: A system for inspecting a tubular may comprise an electromagnetic (EM) logging tool and information handling system. The EM logging tool may further include a mandrel, one or more sensor pads attached to the mandrel by one or more extendable arms, and one or more partial saturation eddy current sensors disposed on each of the one or more sensor pads.

Abstract: Electromagnetic logging tools to inspect nested pipes using hybrid frequency- and time-domain logging techniques are disclosed. The disclosed logging system and processing workflows combine frequency-domain and time-domain techniques to overcome the disadvantages of using frequency-domain or time domain tools in isolation.

Abstract: A method for estimating a thickness for each of a plurality of nested tubulars may comprise disposing an electromagnetic (EM) logging tool in a wellbore. The method may further comprise transmitting an electromagnetic field from the transmitter into one or more tubulars to energize the one or more tubulars with the electromagnetic field thereby producing an eddy, forming a measurement log from the plurality of measurements, and solving a first inverse problem with uniform priors to obtain a first set of estimated tubular parameters. The method may further comprise designing a data-driven prior based on the first set of estimated tubular parameters, solving a second inverse problem with the data-driven prior to obtain a second set of estimated tubular parameters, and using the second set of estimated tubular parameters to make informed decisions on the integrity of the well casings.

Abstract: A method for estimating a pipe property for a plurality of nested tubulars. The method may comprise disposing an electromagnetic (EM) logging tool in a wellbore. The electromagnetic logging tool may comprise a transmitter disposed on the electromagnetic logging tool and a receiver disposed on the electromagnetic logging tool. The method may further comprise transmitting an electromagnetic field from the transmitter into one or more tubulars, measuring the eddy current in the pipe string with the receiver on at least one channel to obtain a plurality of measurements, forming an EM log from the plurality of measurements, extracting data and distinct features from the EM log, forming a relationship between the EM log data and a database, wherein the database is formed from one or more high-resolution measurements, and producing a mapping function between the EM log and the database.

Abstract: A method for identifying a collar using machine learning may include acquiring one or more measurements from one or more depth points within a wellbore including a tubular string, training a machine learning model using a training dataset to create a trained machine learning model, and identifying at least one hyperparameter using the trained machine learning model. The method may further include creating a synthetic model, wherein the synthetic model is defined by one or more pipe attributes, minimizing a mismatch between the one or more measurements and the synthetic model utilizing the at least one hyperparameter, updating the synthetic model to form an updated synthetic model, and repeating the minimizing the mismatch with the updated synthetic model until a threshold is met.

Abstract: A system may include an electromagnetic (EM) logging tool for inspecting downhole tubulars. The EM logging tool may include a mandrel, at least one low-frequency transmitter coil disposed on the mandrel, at least one-low frequency receiver coil disposed on the mandrel, and at least one-high frequency sensor configured to measure one or more electromagnetic properties of a tubular.

Abstract: Reconfigurable electromagnetic pipe inspection tools are designed and assembled using optimized parameters determined using modeling. The reconfigurable tools include multiple modules connected to one another in a stackable fashion guided by optimized tool parameters customized based on well diagrams.

Abstract: Electromagnetic logging tools are optimized using synthetic logs for the purpose of pre-job planning and accuracy/resolution estimation. One, two and three-dimensional forward modeling are used to generate accurate inspection tool responses. A radial one-dimensional (R1D) electromagnetic forward model is also used to compute an approximate log. By constructing non-linear mapping functions between the R1D model-based log and the 2D model-based log, and mapping the R1D synthetic log using the non-linear mapping functions, a quasi 2D log is computed. The quasi 2D log is processed using model-based inversion, thereby providing estimates of pipe parameters. By analyzing the estimates of pipe parameters, tool performance metrics are obtained and analyze to determine the performance of the tool. The tool parameters are adjusted in order to optimize the performance metrics.

Abstract: Electromagnetic logging tools to inspect nested pipes using hybrid frequency- and time-domain logging techniques are disclosed. The disclosed logging system and processing workflows combine frequency-domain and time-domain techniques to overcome the disadvantages of using frequency-domain or time domain tools in isolation.

Abstract: A method for enhancing a formation property image may include taking at least one set of formation property measurements with a borehole imaging device, arranging the at least one set of formation property measurements into a two-dimensional image with a buffer, feeding the two-dimensional image into a deep-learning neural network (DNN), and forming a corrected formation property image from the two-dimensional image. The method may further include inverting the at least one set of formation property measurements to form at least one set of inverted formation property measurements and arranging the at least one set of inverted formation property measurements into a two-dimensional image with a buffer.

Abstract: A system for inspecting a tubular may comprise an electromagnetic (EM) logging tool and information handling system. The EM logging tool may further include a mandrel, one or more sensor pads attached to the mandrel by one or more extendable arms, and one or more partial saturation eddy current sensors disposed on each of the one or more sensor pads.

Abstract: A system may include an electromagnetic (EM) logging tool for inspecting downhole tubulars. The EM logging tool may include a mandrel, at least one low-frequency transmitter coil disposed on the mandrel, at least one-low frequency receiver coil disposed on the mandrel, and at least one-high frequency sensor configured to measure one or more electromagnetic properties of a tubular.