Circuits that employ selective solid-state isolation of circuit elements can include solid-state switches, such as back-to-back Field Effect Transistor (FET) pairs, and isolated gate drive electronics adapted to operate the solid-state switches in order to selectively decouple certain circuit elements. The isolated solid-state switches can be placed in series to achieve higher standoff voltages, and can be configured for low on resistance and short switching times. The gate drive electronics can include electrical isolation components adapted to enhance standoff voltages and reduce electrical noise at the selectively isolated circuit elements.

System and methods for geosteering inversion are provided. Downhole tool responses are predicted for different points along a planned path of a wellbore during a downhole operation, based on each of a plurality of inversion models. Measurements of the downhole tool's actual responses are obtained as the wellbore is drilled over the different points during a current stage of the operation. The inversion models are clustered based on a comparison between the actual and predicted tool responses and a randomly selected centroid for each cluster. The inversion models are re-clustered using an average inversion model determined for each cluster as the centroid for that cluster. At least one of the re-m clustered inversion models is used to perform inversion for one or more subsequent stages of the downhole operation along the planned wellbore path. The planned wellbore path is adjusted for the subsequent stage(s) of the downhole operation.

A method includes providing a Bottom Hole Assembly (BHA) in a wellbore. The BHA includes a rotary steerable system and a downhole attitude correction and control system. The downhole correction and control system includes a first sensor set, the sensors of the first sensor set positioned near ferromagnetic components of a drill string and a second sensor set, the sensors of the second sensor set positioned further from the ferromagnetic components of the drill string than the sensors of the first sensor set. Corrupted data from the first sensor set and reference data from the second sensor set is obtained, the corrupted data including cross-axis magnetometer and accelerometer measurements. The method additionally includes correcting the corrupted sensor data to form corrected sensor measurements and calculating an estimated azimuth from the corrected sensor measurements. The method further includes steering the rotary steerable system based on the estimated azimuth.

A method includes providing a Bottom Hole Assembly (BHA) in a wellbore. The BHA includes a rotary steerable system and a downhole attitude correction and control system. The downhole correction and control system includes a first sensor set, the sensors of the first sensor set positioned near ferromagnetic components of a drill string and a second sensor set, the sensors of the second sensor set positioned further from the ferromagnetic components of the drill string than the sensors of the first sensor set. Corrupted data from the first sensor set and reference data from the second sensor set is obtained, the corrupted data including cross-axis magnetometer and accelerometer measurements. The method additionally includes correcting the corrupted sensor data to form corrected sensor measurements and calculating an estimated azimuth from the corrected sensor measurements. The method further includes steering the rotary steerable system based on the estimated azimuth.

Systems and methods for generating a curtain plot that includes two inverted parameters based on the formation boundaries and the formation resistivity, the uncertainties of the formation boundaries, and the uncertainties of the drilled well-path, generating an updated curtain plot that includes two projected inverted parameters based on updated formation boundaries and updated formation resistivity, the projected uncertainties of the updated formation boundaries, and the projected uncertainties of the planned well-path, and avoiding, by the drilling operations, the uncertainties of the formation boundaries of the curtain plot and the updated curtain plot based on the two inverted parameters and the two projected inverted parameters to maintain or adjust the planned well-path within the projected uncertainties of the planned well-path.

Systems and methods for generating a curtain plot that includes two inverted parameters based on the formation boundaries and the formation resistivity, the uncertainties of the formation boundaries, and the uncertainties of the drilled well-path, generating an updated curtain plot that includes two projected inverted parameters based on updated formation boundaries and updated formation resistivity, the projected uncertainties of the updated formation boundaries, and the projected uncertainties of the planned well-path, and avoiding, by the drilling operations, the uncertainties of the formation boundaries of the curtain plot and the updated curtain plot based on the two inverted parameters and the two projected inverted parameters to maintain or adjust the planned well-path within the projected uncertainties of the planned well-path.

A sequence time window amplitude-phase-frequency characteristics analysis method and system for underwater vehicle power frequency electromagnetic field disturbance are provided. The method includes: establishing a power grid dipole group model, emulating and calculating to obtain background field intensity data of a test location, and constructing an emulated background field database; acquiring measured background field data, comparing the emulated data with the measured data, and providing a relative error; calculating a background field intensity and underwater vehicle target disturbance under the action of the above dipole group, and establishing a measured target signal database; and performing actual measurement according to an underwater vehicle motion and detection topology, performing a Fourier transform and Fourier sliding window decomposition after acquiring original data, and acquiring an amplitude spectrum and a spectrogram of an underwater vehicle target disturbance signal.

A sequence time window amplitude-phase-frequency characteristics analysis method and system for underwater vehicle power frequency electromagnetic field disturbance are provided. The method includes: establishing a power grid dipole group model, emulating and calculating to obtain background field intensity data of a test location, and constructing an emulated background field database; acquiring measured background field data, comparing the emulated data with the measured data, and providing a relative error; calculating a background field intensity and underwater vehicle target disturbance under the action of the above dipole group, and establishing a measured target signal database; and performing actual measurement according to an underwater vehicle motion and detection topology, performing a Fourier transform and Fourier sliding window decomposition after acquiring original data, and acquiring an amplitude spectrum and a spectrogram of an underwater vehicle target disturbance signal.

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.

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.