Abstract: A method for identifying one or more imaging properties. The method may comprise identifying one or more candidate mud constants, taking one or more measurements from a borehole with a downhole tool to form an image log, inputting into a machine learning model one or more inputs such that the machine learning model outputs one or more estimated imaging properties, and inputting into a forward model at least the one or more estimated imaging properties and the one or more candidate mud constants such that the forward model outputs one or more reconstructed tool responses. The method may further comprise computing a misfit between the one or more reconstructed tool responses and the one or more measurements, picking a mud candidate from the one or more candidate mud constants based at least in part on the misfit, and producing one or more imaging properties from the picked mud candidate.

Abstract: Aspects of the subject technology relate to systems and methods for identifying a mud angle associated with an electromagnetic imager tool based on variations in mud effect removed quantities of tool measurements made by the electromagnetic imager tool. Tool measurements made through one or more measurement units of an electromagnetic imager tool can be received. The one or more measurement units can have azimuthal sensitivity and the electromagnetic imager tool can operate to log a wellbore in a formation in making the measurements. One or more mud effect removal techniques can be applied to the tool measurements across a plurality of mud angle estimates to generate mud effect removed quantities for the one or more measurement units across the plurality of mud angle estimates.

Abstract: A method and system for resistivity imaging. A method may comprise disposing a downhole tool into a borehole, applying a voltage difference between the array of injector electrodes, constructing a first set of formation images for each of the plurality of frequencies, applying a mud effect removal algorithm to produce a second set of formation images for each of the plurality of frequencies, applying a dielectric correction algorithm to each of the plurality of frequencies to produce a third set of formation images for each of the plurality of frequencies, and combining the first set of formation images, the second set of formation images, and the third set of formation images to obtain a blended image. A system for resistivity imaging may comprise a downhole tool. The downhole tool may comprises a pad, an array of injector electrodes, and one or more return electrodes.

Abstract: 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.

Abstract: This disclosure may relate to a system and method for calculating the mud angle from a downhole device. A method for estimating a mud angle may comprise: disposing a downhole tool into a borehole; extending an arm of the downhole tool to a first location, wherein a pad is disposed on the arm; taking a first impedance measurement with at least one button electrode, wherein the button electrode is disposed in a button array, wherein the button array is disposed on the pad; extending the arm to a second location; taking a second impedance measurement with the at least one button electrode; transmitting the first measurement and the second measurement to an information handling system; and estimating the mud angle from the first impedance measurement and the second impedance measurement with an information handling system.

Abstract: A method and system for resistivity imaging. A method may comprise disposing a downhole tool into a borehole, applying a voltage difference between the array of injector electrodes, constructing a first set of formation images for each of the plurality of frequencies, applying a mud effect removal algorithm to produce a second set of formation images for each of the plurality of frequencies, applying a dielectric correction algorithm to each of the plurality of frequencies to produce a third set of formation images for each of the plurality of frequencies, and combining the first set of formation images, the second set of formation images, and the third set of formation images to obtain a blended image. A system for resistivity imaging may comprise a downhole tool. The downhole tool may comprises a pad, an array of injector electrodes, and one or more return electrodes.

Abstract: A variety of methods and systems are disclosed, including, a method for improving resistivity imaging, comprising: disposing a downhole tool into a borehole, wherein the downhole tool comprises a pad and a button array disposed on the pad; taking a measurement with the button array at a location in the borehole; selecting a projection angle; obtaining a corrected measurement from the projection angle and the measurement; and constructing an image using the corrected measurement. A system for improving resistivity imaging, comprising: a downhole tool, wherein the downhole tool comprises: an arm, and a pad; a conveyance; and an information handling system, wherein the information handling system is configured to take a measurement with the button array at a location in the borehole; select a projection angle; obtain a corrected measurement from the projection angle and the measurement; and construct an image using the corrected measurement.

Abstract: Aspects of the subject technology relate to systems, methods, and computer-readable media for controlling borehole imaging blending through machine learning. A blending parameter machine learning model can be trained through a supervised machine learning technique with a dataset of known input and known output associated with an electromagnetic imager tool. The blending parameter machine learning model is associated with an image blending technique for blending images generated through the electromagnetic imager tool at different frequencies. One or more blending parameters for the image blending technique can be identified by applying the blending parameter machine learning model to measurements of the electromagnetic imager tool operating to log a wellbore across a plurality of frequencies. One or more blended images can be generated by applying the image blending technique according to the one or more blending parameters to a plurality of images of the measurements made by the electromagnetic imager tool.

Abstract: A downhole tool may comprise a mandrel, wherein the mandrel is a structural support for the downhole tool; one or more arms, wherein the one or more arms are attached to the mandrel; and a pad, wherein the pad is connected to the one or more arms. The pad may comprise a material, where the material expands or contracts from an external electromagnetic field; an insulator, wherein the insulator is connected at a first end to the material; and an electrode, wherein the electrode is connected to the insulator. A method may comprise applying a time varying biasing voltage to a material, wherein the material exhibits mechanical strain; taking a first measurement and a second measurement with at least one operating frequency with an electrode; calculating a mud property based at least in part on the first measurement and the second measurement; and applying a mud effect removal algorithm to the mud property.

Abstract: 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.

Abstract: A method and a system for estimating a pipe property for a plurality of nested pipes. The method may comprise determining the pipe property from the plurality of measurements, wherein the pipe property identifies a feature in the wellbore, forming a pre-computed table of responses for the at least one channel comprising a plurality of points that sample the pipe property, and performing a model-based inversion to estimate the pipe property using the plurality of measurements, the nominal properties of the pipes, and a fast forward model based on the pre-computed table of responses. A system may comprise an electromagnetic logging tool and an information handling system. The electromagnetic logging tool may comprise a transmitter, wherein the transmitter is a first coil and is operable to transmit an electromagnetic field, and a receiver, wherein the receiver and is operable to measure the electromagnetic field.

Abstract: Aspects of the subject technology relate to systems and methods for identifying a mud angle associated with an electromagnetic imager tool based on tool measurements made during operation of the electromagnetic imager tool. Tool measurements made by an electromagnetic imager tool operating to log a wellbore in a formation can be gathered. The tool measurements can be decomposed into two quantities along a plurality of candidate mud angles for the electromagnetic imager tool. As follows, a mud angle associated with the electromagnetic imager tool can be identified from the plurality of candidate mud angles based on an amount of correlation between the two quantities for each of the plurality of candidate mud angles.

Abstract: Aspects of the subject technology relate to systems and methods for identifying a mud angle associated with an electromagnetic imager tool based on variations in mud effect removed quantities of tool measurements made by the electromagnetic imager tool. Tool measurements made through one or more measurement units of an electromagnetic imager tool can be received. The one or more measurement units can have azimuthal sensitivity and the electromagnetic imager tool can operate to log a wellbore in a formation in making the measurements. One or more mud effect removal techniques can be applied to the tool measurements across a plurality of mud angle estimates to generate mud effect removed quantities for the one or more measurement units across the plurality of mud angle estimates.

Abstract: A method and electromagnetic ranging system for determining the location of a target well. A method may comprise taking a first measurement with an electromagnetic ranging tool at a first position and calculating a first modeled signal. Additionally, calculating a calibration for the electromagnetic ranging tool from at least the first measurement and the first modeled signal, taking a second measurement with the electromagnetic ranging tool at a second position, and calculating a calibrated measurement. The method may comprise determining a distance, direction, and/or orientation to a target wellbore using at least the calibrated measurement. An electromagnetic ranging system may comprise an electromagnetic ranging tool and an information handling system coupled to the electromagnetic ranging tool.

Abstract: A method for identifying one or more imaging properties. The method may comprise identifying one or more candidate mud constants, taking one or more measurements from a borehole with a downhole tool to form an image log, inputting into a machine learning model one or more inputs such that the machine learning model outputs one or more estimated imaging properties, and inputting into a forward model at least the one or more estimated imaging properties and the one or more candidate mud constants such that the forward model outputs one or more reconstructed tool responses. The method may further comprise computing a misfit between the one or more reconstructed tool responses and the one or more measurements, picking a mud candidate from the one or more candidate mud constants based at least in part on the misfit, and producing one or more imaging properties from the picked mud candidate.

Abstract: Aspects of the subject technology relate to systems, methods, and computer-readable media for controlling borehole imaging blending through machine learning. A blending parameter machine learning model can be trained through a supervised machine learning technique with a dataset of known input and known output associated with an electromagnetic imager tool. The blending parameter machine learning model is associated with an image blending technique for blending images generated through the electromagnetic imager tool at different frequencies. One or more blending parameters for the image blending technique can be identified by applying the blending parameter machine learning model to measurements of the electromagnetic imager tool operating to log a wellbore across a plurality of frequencies. One or more blended images can be generated by applying the image blending technique according to the one or more blending parameters to a plurality of images of the measurements made by the electromagnetic imager tool.

Abstract: A sensor and sensing method for a downhole logging tool provide an antenna having a toroidal or spiral winding that is toroidally or helically wound around a toroid core. The toroidally-wound toroidal winding antenna forms a natural high-pass filter that is capable of suppressing low-frequency and midrange frequency noise and other interference. This allows the logging tool to sense or detect high-frequency signals, or the high-frequency component of a signal, more clearly and accurately. Multiple toroidally-wound toroidal winding antennas may be used in multiple different configurations, including a multi-axial configuration, bucking configuration, radial configuration, and the like. The sensor and sensing method are particularly useful in applications, such as dielectric logging, short hop communications, waterflood monitoring, and the like.

Abstract: A method for identifying an operating frequency may comprise performing a frequency sweep using one or more injector electrodes disposed on a downhole tool, recording one or more measurements from the frequency sweep, identifying one or more stable frequencies from the frequency sweep, and identifying one or more operating frequencies from the one or more stable frequencies. A system for electrical isolation may comprise a downhole tool, a pad, an arm, wherein the arm is attached to the mounting bracket and the mandrel, and an information handling system connected to the pad through the first set of electronics and the second set of electronics. The downhole tool may comprise a mandrel, a chassis disposed in the mandrel, and a first set of electronics disposed in the chassis.

Abstract: A method and a system for tuning a pad. The method may comprise disposing a downhole tool into a borehole, configuring the pad in a first configuration, taking a first measurement of the formation in the first configuration, configuring the pad in a second configuration, taking a second measurement of the formation in the second configuration, determining a tuning coefficient to reduce a tool body effect in the first measurement and the second measurement, computing a first weighted measurement from the tuning coefficient and the first measurement, computing a second weighted measurement from the tuning coefficient and the second measurement, and computing a tuned impedance from a ratio of the first weighted measurement and the second weighted measurement. A system for determining a formation boundary may comprise a downhole tool, an arm, and a pad. The system may further comprise a conveyance and an information handling system.

Abstract: A method for determining mud properties may comprise taking multi-frequency measurement data with a downhole tool, selecting an injector electrode from the one or more injector electrodes for the multi-frequency measurement data, selecting data from the multi-frequency measurement data with low resistivity or a large standoff, creating a forward model based at least partially on the selected data by making initial guesses of model parameters for one or more mud properties, performing a cost function minimization with the forward model, identifying from the cost function minimization if a misfit is above or below a threshold, and identifying the one or more mud properties based at least in part on the cost function minimization. A system may comprise a downhole tool including a mandrel, one or more arms, one or more pads, and one or more injector electrodes. The system may further include an information handling system.