Abstract: A method includes receiving a first set of measurement data from a plurality of transmitter-receiver pairs of a measurement tool coupled to a drill string of a drilling system, wherein the first set of measurement data includes a first portion of measurement data from each of the plurality of transmitter-receiver pairs. The method further includes generating a first inversion image based on the first set of measurement data, updating a geological model based on the first inversion image, and controlling one or more operational parameters of the drilling system substantially in real-time based on the geological model.

Abstract: A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.

Abstract: Techniques and systems for generating resistivity images. A system includes an electromagnetic (EM) logging tool configured to generate EM propagation measurements during a drilling operation. The system also includes a processing system configured to be coupled to the EM logging tool, wherein the processing system is configured to calculate a resistivity image for a formation utilizing at least one EM propagation measurement of the EM propagation measurements and without use of an inversion technique or lookup table; and transmit the resistivity image for display on a display.

Abstract: A method for classifying a subterranean formation includes deploying an electromagnetic logging tool in a wellbore penetrating the subterranean formation, causing the electromagnetic logging tool to make electromagnetic logging measurements in the wellbore, and evaluating the electromagnetic logging measurements with a trained machine learning primary classifier to classify the subterranean formation as either a 1D formation or a non-1D formation.

Abstract: The present disclosure provides systems and methods of selecting measurement channels. The methods include receiving a plurality of measurement channels for a logging tool. A plurality of measurement parameters is determined for each measurement channel of the plurality of measurement channels of a formation of a wellbore. A global sensitivity indices is determined, in which determining the global sensitivity indices includes identifying a sampling distribution of the plurality of measurement parameters using a measurement parameter range for each measurement parameter, receiving a noise model, and determining the global sensitivity indices using the measurement parameters, the sampling distribution, and the noise model. Each measurement channel of the plurality of measurement channel is ranked using the global sensitivity indices.

Abstract: A method includes receiving formation model data corresponding to characteristics of a formation, receiving at least one drilling parameter corresponding to an attribute related to a well in the formation, generating a synthetic response based upon the formation model data and the at least one drilling parameter, undertaking channel selection based on the synthetic response as training data, wherein the channel selection comprises a set of data channels of a logging tool of the well that prioritizes a predetermined portion of measurements to transmit from the logging tool, training a machine learning system into a trained machine learning system utilizing the training data comprising the channel selection corresponding to the synthetic response as a matched pair of inputs for the machine learning system, and generating a final model as the trained machine learning system via the training of the machine learning system.

Abstract: Techniques and systems for generating resistivity images. A system includes an electromagnetic (EM) logging tool configured to generate EM propagation measurements during a drilling operation. The system also includes a processing system configured to be coupled to the EM logging tool, wherein the processing system is configured to calculate a resistivity image for a formation utilizing at least one EM propagation measurement of the EM propagation measurements and without use of an inversion technique or lookup table; and transmit the resistivity image for display on a display.

Abstract: Techniques and systems for logging tool data channel prioritization. A system includes a logging tool configured to generate measurements in a well during a drilling operation and transmit a predetermined portion of the measurements and a processing system configured to be coupled to the logging tool, wherein the processing system is configured to calculate which data channels of the logging tool to prioritize as the predetermined portion of the measurements to transmit and transmit a control signal to configure the logging tool to transmit the predetermined portion of the measurements.

Abstract: A method for estimating EM measurement uncertainty includes evaluating EM logging measurements with a trained machine learning model to estimate the measurement uncertainties of the EM logging measurements. The trained machine learning model is trained using a training data set made up of modeled EM logging measurements and corresponding measurement uncertainties.

Abstract: A method for making electromagnetic directional resistivity measurements includes rotating an electromagnetic logging tool in a subterranean wellbore penetrating the formation. The logging tool includes a transmitting antenna and a receiving antenna spaced along a tool body with at least one of the transmitting antenna and the receiving antenna being a tiltted antenna. The electromagnectic logging tool is used to make a plurality of electromagnetic measurements at a corresponding plurality of frequencies while rotating in the wellbore. The plurality of measurements made at the corresponding plurality of frequencies is processed to compute a combined apparent resistivity of the subterranean formation. The processing includes minimizing a difference between a plurality of modeled measurements and the plurality of wellbore measurements in which the modeled measurements are computed using a model assuming a homogenous formation.

Abstract: A method can include receiving data for a geologic region; based at least in part on the data, selecting a model from a plurality of models using a trained machine learning model, and inverting the data using the selected model to determine parameters of the selected model.

Abstract: A method includes receiving information for a subsurface region; based at least in part on the information, identifying sub-regions within the subsurface region; assigning individual identified sub-regions a dimensionality of a plurality of different dimensionalities that correspond to a plurality of different models; via a model-based computational framework, generating at least one result for at least one of the individual identified sub-regions based at least in part on at least one assigned dimensionality; and consolidating the at least one result for multiple sub-regions.

Abstract: Identifying the dielectric constant and/or the electrical resistivity of part of a geological formation may reveal useful characteristics of the geological formation. This disclosure provides methods, systems, and machine-readable media to determine dielectric constant or electrical resistivity, or both, using contraction mapping. Specifically, contraction mapping may be used with a function of wavenumber k to iteratively solve for values of dielectric constant and electrical resistivity until convergence is achieved. This may allow for convergence to a solution without computing partial derivatives and/or with fewer iterations than previous techniques.

Abstract: A method includes receiving information for a subsurface region; based at least in part on the information, identifying sub-regions within the subsurface region; assigning individual identified sub-regions a dimensionality of a plurality of different dimensionalities that correspond to a plurality of different models; via a model-based computational framework, generating at least one result for at least one of the individual identified sub-regions based at least in part on at least one assigned dimensionality; and consolidating the at least one result for multiple sub-regions.

Abstract: Techniques for log squaring using both directional and non-directional electromagnetic measurements are disclosed. The techniques described herein can be used for determining bed boundary locations and assigning resistivity values to each layer in a layered earth model, regardless of well deviation. Potential bed boundary locations can be derived from both directional and non-directional electromagnetic measurement data. The bed boundary locations from the directional and non-directional measurements can then be consolidated using a weighted averaging scheme, where weight can be dependent based on apparent formation dip. By combining the results from both directional and non-directional measurements, the log squaring techniques described herein can be used in most wells regardless of the well angle (the angle can be arbitrary). Once bed boundaries are selected, formation properties, such as horizontal resistivity (Rh) and vertical resistivity (Rv) can be assigned to the model layers.

Abstract: Methods, computer-readable media, and systems are disclosed for applying 1D processing in a non-1D formation. In some embodiments, a 3D model or curtain section of a subsurface earth formation may be obtained. A processing window within the 3D model or curtain that is suitable for 1D inversion processing is determined, and a local 1D model for the processing window is built. A 1D inversion is performed on the local 1D model, and inverted formation parameters are used to update the 3D model or curtain section.

Abstract: A system and method discloses performing a fracture operation at a wellsite about a subterranean formation. The method involves, obtaining wellsite measurements by placing a downhole tool in a wellbore and using the downhole tool to acquire measurements of the subterranean formation, simulating the obtained wellsite measurements to determine formation parameters comprising conductivity tensors based on a formation model of the measured subterranean formation, validating the formation model by comparing the obtained wellsite measurements with the simulated wellsite measurements, generating fracture parameters and triaxiality indicators based on the validated formation model, and fracturing the subterranean formation based on the generated fracture parameters and triaxiality indicators.

Abstract: Embodiments set forth in this disclosure providing techniques for determining formation parameters, such as horizontal resistivity (Rh), vertical resistivity (Rv), and dip, in high angle and horizontal wells using non-directional resistivity measurements. For example, a method is provided that may include using an electromagnetic logging tool to acquire non-directional resistivity measurements in a wellbore of a high angle or horizontal well. The method may also include defining a processing window that corresponds to a measurement point of the electromagnetic logging tool along a well trajectory that intersects a at least one bed boundary between two layers of a subsurface formation. The method may also include defining a formation structure and defining an initial set of formation parameters for each layer in the formation structure. Furthermore, the method may include inverting the formation parameters for each layer.

Abstract: Embodiments set forth in this disclosure providing techniques for determining formation parameters, such as horizontal resistivity (Rh), vertical resistivity (Rv), and dip, in high angle and horizontal wells using non-directional resistivity measurements. For example, a method is provided that may include using an electromagnetic logging tool to acquire non-directional resistivity measurements in a wellbore of a high angle or horizontal well. The method may also include defining a processing window that corresponds to a measurement point of the electromagnetic logging tool along a well trajectory that intersects a at least one bed boundary between two layers of a subsurface formation. The method may also include defining a formation structure and defining an initial set of formation parameters for each layer in the formation structure. Furthermore, the method may include inverting the formation parameters for each layer.

Abstract: Techniques for log squaring using both directional and non-directional electromagnetic measurements are disclosed. The techniques described herein can be used for determining bed boundary locations and assigning resistivity values to each layer in a layered earth model, regardless of well deviation. Potential bed boundary locations can be derived from both directional and non-directional electromagnetic measurement data. The bed boundary locations from the directional and non-directional measurements can then be consolidated using a weighted averaging scheme, where weight can be dependent based on apparent formation dip. By combining the results from both directional and non-directional measurements, the log squaring techniques described herein can be used in most wells regardless of the well angle (the angle can be arbitrary). Once bed boundaries are selected, formation properties, such as horizontal resistivity (Rh) and vertical resistivity (Rv) can be assigned to the model layers.