Systems and methods for automated filtering and normalization of logging data for improved drilling performance may enable smoothing and amplitude scaling of log data for meaningful comparison and analysis without scaling artefacts. The logging data may be collected from downhole sensors or may be recorded by a control system used for drilling. A computer implemented method may enable industrial scale automated filtering and normalization of logging data, including calibration to a known standard. In particular, the filtering and normalization may be used for stratigraphic analysis to correlate true vertical depth to measured depth along a wellbore.

A method may include obtaining first nuclear magnetic resonance (NMR) data for a saturated core sample regarding a geological region of interest. The method may further include determining, using the first NMR data, spatial porosity data based on the saturated core sample. The spatial porosity data may describe various porosity values as a function of a sampling position of the saturated core sample. The method may further include obtaining second NMR data for a desaturated core sample regarding the geological region of interest. The method may further include determining, using the second NMR data, spatial permeability data based on the desaturated core sample. The method may further include determining a geological model for the geological region of interest using the spatial porosity data, the spatial permeability data, and a fitting process.

An advanced geological prediction method and system based on perception while drilling, and relates to advanced geological prediction. The solution includes: acquiring drilling parameters during drilling; obtaining physical and mechanical parameters of tunnel surrounding rocks by inversion based on drilling parameters; acquiring rock slag or powder based on flushing fluid collected during drilling; acquiring geochemical characteristic parameters of rock slag or powder; and obtaining at least one adverse geology recognition result and surrounding rock classification result using a pre-trained deep learning model, and realizing advanced geological prediction. Combined with advanced geological drilling, the solution reflects geological characteristics from changes of physical and mechanical properties of tunnel surrounding rocks and changes of geochemical characteristic parameters. Advanced prediction of geology ahead of a tunnel face is realized by collection and analysis of drilling parameters and flushing fluid during advanced drilling and the fusion of big data and a deep learning algorithm.

Systems and methods for evaluating hydrocarbon properties. At least one of the systems includes: a drilling machine configured to drill a borehole; a plurality of infrared cameras configured to capture infrared image data representing a plurality of infrared images of at least one core sample extracted from the borehole; a computer-readable memory comprising computer-executable instructions; and at least one processor configured to execute the computer-executable instructions, in which when the at least one processor is executing the computer-executable instructions, the at least one processor is configured to carry out operations including: receiving the infrared image data captured by the plurality of infrared cameras; determining, based on the infrared image data, at least one hydrocarbon weight value of the at least one core sample.

A rotor catch assembly for connection in a workstring in a wellbore is provided. The rotor catch assembly is connected to a downhole motor assembly that includes a rotor that is driven by a fluid. In the normal operating state of the rotor catch assembly, fluid flows through the catch assembly and causes the rotor to rotate. In this state, the catch assembly generates pressure pulses in the fluid in the workstring to facilitate advancement of the workstring in the wellbore. In the event of a failure of a mechanical connection in the motor assembly, the rotor catch assembly shifts to a catch-activated state in which the motor assembly is disabled.

A system for determining a direction for drilling a well is disclosed. The system has a device in a portion of a conveyance mechanism comprising a cylindrical housing with at least one sensor that tracks a position of the portion during a drilling operation, the device being configured to obtain a plurality of drilling parameters, and a control system coupled to the device and configured to perform at least one reservoir simulation, and prepare a plurality of required parameters while drilling. The device uses an optimization box to simulate increasing an angle between a drilling direction and a maximum horizontal stress by calculating a minimum mud pressure required to prevent borehole collapse. The control system generates an engineering curve representative of each angle simulated and a corresponding mud weight or pressure, and the device and the control system identify an optimal direction corresponding to a minimum drilling mud pressure parameter.

A method for developing a procedure for pretreating a section of a wellbore prior to hydraulic fracturing stimulation of the section of the wellbore includes determining an optimized notch geometry and determining an optimized chemical treatment for the section of the wellbore. The optimized notch geometry is determined by modeling a notch in the section of the wellbore using a computing system, simulating a pressure increase in the section of the wellbore and on the notch from a hydraulic fracturing stimulation, identifying breakdown pressure in the section of the wellbore, and repeating the modeling, simulating, and identifying to determine the optimized notch geometry in the wellbore as the notch having a lowest breakdown pressure. The optimized chemical treatment is determined by determining a rock type in the section of the wellbore and determining a conditioning fluid that reduces the tensile strength of the rock type.

Methods of exploiting a formation containing a reservoir of hydrocarbons utilize a gas-liquid drift-flux (DF) model for a multi-segmented wellbore (MSW). The DF model is provided for use in conjunction with a reservoir simulator. The DF model is configured to account for pipe inclinations of the MSW between −90° and +90° including horizontal or near-horizontal wellbores in addition to vertical and slanted wellbores. The DF model is based on mixture velocity as opposed to superficial velocities, thereby permitting the DF model to be integrated with reservoir models that utilize mixture velocity. The DF model can also be continuous and differentiable over all primary variables.

Methods and apparatuses for controlling a trajectory of a borehole being drilled into the earth are provided. The apparatus includes a drilling system including a drill tubular, a disintegrating device, and a steering system coupled to the drill tubular configured to steer the drilling system, the drilling system configured to drill the borehole by receiving control outputs from at least one control unit for controlling parameters of the drilling system, the at least one control unit configured to provide the control outputs to the steering system, the at least one control unit being configured to provide depth-based control.

A system includes a discharge tool positioned within a wellbore and configured to generate an electrical discharge that interacts with a rock formation proximate to the discharge tool, wherein the interaction of the electrical discharge with the rock formation vaporizes a portion of the rock formation to generate a discharge plasma. The system further includes an optical emission spectroscopy (OES) sub-system configured to determine an elemental composition of the portion of the rock formation based on optical emission generated by the discharge plasma, wherein at least a portion of the OES sub-system is positioned within the wellbore.