Systems and methods for determining shear failure of a rock formation are disclosed. The method includes receiving, by a processor, a plurality of parameters related to physical properties of the rock formation, applying the plurality of parameters to a predetermined failure criterion, and determining shear failure of the rock formation based on the failure criterion. In some embodiments the failure criterion is a modified Hoek-Brown failure criterion that takes into consideration an intermediate principal stress, and the difference between normal stresses and an average confining stress.

A method of registering geological data at a formation core tracking system includes, at the tracking system, registering a formation core provided within a field of view of an optical imaging system of the tracking system; tracking the orientation of the formation core relative to the tracking system and the distance of the formation core relative to the tracking system; obtaining data associated with a first section of the formation core which is located at a predetermined distance from the tracking system, displaying the data together with an image of the formation core such that an augmented reality image is provided on a display device of the tracking system, changing the distance between the tracking system and the core; and updating the displayed data by obtaining data associated with a second section of the formation core which is located at said predetermined distance from the tracking system.

A method or system is configured for determining a seismic attenuation quality factor Q for intervals of subsurface formations by performing actions including receiving vertical seismic profile traces. The actions include filtering the vertical seismic profile traces with an inverse impulse response of a downhole receiver. The actions include transforming the vertical seismic profile data from the particle motion measured by the downhole receiver to the far-field particle motions represented by the source wavelet. The actions include determining a ratio of the spectral amplitudes of the direct arrival event of the transformed vertical seismic profile data and the source Klauder wavelet. A quality factor Q is generated representing an attenuation of the seismic signal between the source at ground level surface and the downhole receiver.

A method for performing wellbore correlation across multiple wellbores includes predicting a depth alignment across the wellbores based on a geological feature of the wellbores. Predicting a depth alignment includes selecting a reference wellbore, defining a control point in a reference signal of a reference well log for the reference wellbore, and generating an input tile from the reference signal, the control points, and a number of non-reference well logs corresponding to non-reference wellbores. The well logs include changes in a geological feature over a depth of a wellbore. The input tile is input into a machine-learning model to output a corresponding control point for each non-reference well log. The corresponding control point corresponds to the control point of the reference log. Based on the corresponding control points output from the machine-learning model, the non-reference well logs are aligned with the reference well log to correlate the multiple wellbores.

The present disclosure relates to systems, methods, and non-transitory computer-readable media for dynamically utilizing offset drill-well data generated within a threshold geographic area to determine formation-top trends and identify formation-top depths at a subject drill-well site. To do so, in some embodiments, the disclosed systems estimate a variogram for observed formation-top depths of a subset of offset drill-wells, and, in turn, map a predicted response from the estimated variogram. For example, using weighted combinations (e.g., with Kriging weights) of the formation-top depths of the subset of offset drill-wells, the disclosed systems can map a continuous surface of a formation and identify a top-depth thereof. Moreover, the disclosed system can do so for multiple formations at the subject drill-well site, and (in real-time in response to a user input) provide for display at a client device, the associated formation-top depths, various predicted drilling events and/or predicted drilling metrics.

A method includes receiving well log data for a plurality of wells. A flag is generated based at least partially on the well log data. The wells are sorted into groups based at least partially on the well log data, the flag, or both. A model is built for each of the wells based at least partially on the well log data, the flag, and the groups.

Implementations described and claimed herein provide systems and methods for reservoir modeling. In one implementation, an input dataset comprising seismic data is received for a particular subsurface reservoir. Based on the input dataset and utilizing a deep learning computing technique, a plurality of trained reservoir models may be generated based on training data and/or validation information to model the particular subsurface reservoir. From the plurality of trained reservoir models, an optimized reservoir model may be selected based on a comparison of each of the plurality of reservoir models to a dataset of measured subsurface characteristics.

A lithology prediction that uses a geological age model as an input to a machine learning model. The geological age model is capable of separating and recoding different seismic packages derived from the horizon interpretation. Once the machine learning model has been trained, a validation may be performed to determine the quality of the machine learning model. The quality may be improved by refining the training of the machine learning model. The lithology prediction generated by the machine learning model that utilizes the geological age model provides an improved lithology prediction that more accurately reflects the subterranean formation of an area of interest.

An acoustic logging system includes a first transducer in contact with or in close proximity to a sound barrier configured to emit a beam of acoustic energy according to a first mode of operation or a second mode of operation. The system also includes one or more second transducers in contact with or in close proximity to the sound barrier, positioned axially away from the first transducer, configured to receive acoustic energy from a wellbore environment responsive to the beam. The first mode of operation is a transmit-receive mode of operation where the beam is steerable to interact with one or more wellbore components at a first angle and the second mode of operation is a pulse echo mode of operation where the beam interacts with the one or more wellbore components at a second angle different from the first angle.

Methods, apparatuses, and computer-readable media utilize data stacking to facilitate identification and/or correction of data interpretation conducted for a subsurface formation. Related data sets, such as well logs, may be displayed along with markers representing a common entity in the related data sets, such as formation features in a surface formation, and a visualization of stacked data may be generated and centered on the markers to highlight mis-alignment of any of the markers.