A method of optimizing a design of a wellbore drilling operation based on at least one set of offset well data. A drilling path record for each offset well comprises a set of drilling parameters separated into depth segments. An optimization process determines a drilling dysfunction for each set of drilling parameter by comparing the drilling parameter to a maximum value. The optimization process determines the maximum rate of penetration for each depth segment by comparing the sets of drilling parameters without a drilling dysfunction. The optimization process generates an optimum drilling roadmap in response to determining the drilling parameters for the maxim um rate of penetration for each depth segment. A drilling operation can drill a wellbore via the optimum drilling roadmap.

Systems and methods include a method for providing an integrated advanced visualization tool for geosteering underbalanced coiled tubing drilling (UBCTD) operations. Drilling operation data is received from different sources in real time during a drilling operation. The drilling operation data includes geological formation information recorded during the drilling operation, micropalaeontological test results of the drilling operation, drilling parameters being used during the drilling operation, cumulative productivity index calculations, and reservoir pressure information of reservoirs encountered during the drilling operation. The drilling operation data is analyzed to correlate elements of the drilling operation data by time and cumulative depth. A graph is generated in real time that includes multiple plots correlated as a function of cumulative depth over time.

Systems and methods include a method for providing an integrated advanced visualization tool for geosteering underbalanced coiled tubing drilling (UBCTD) operations. Drilling operation data is received from different sources in real time during a drilling operation. The drilling operation data includes geological formation information recorded during the drilling operation, micropalaeontological test results of the drilling operation, drilling parameters being used during the drilling operation, cumulative productivity index calculations, and reservoir pressure information of reservoirs encountered during the drilling operation. The drilling operation data is analyzed to correlate elements of the drilling operation data by time and cumulative depth. A graph is generated in real time that includes multiple plots correlated as a function of cumulative depth over time.

An automated slide drilling system (ASDS) may be used with a drilling rig system to control slide drilling. The ASDS may autonomously control slide drilling without user input during the slide drilling. The ASDS may further support a transition from rotary drilling to slide drilling to rotary drilling without user input during the transitions. The ASDS may also support user input and user notifications for various steps to enable manual or semi-manual control of slide drilling by a driller or an operator.

An advanced real-time drilling control system can comprise circuitry configured to continuously monitor, in real time, drilling performance of an electric drilling machine as the electric drilling machine drills a blasthole using a rotary tricone drill bit. The continuous monitoring can include continuously collecting, according to a predetermined sampling rate, drill performance data from one or more sensors of the electric drilling machine in real time. The circuitry can also be configured to adjust, in real time, pulldown pressure/rate and rotary speed of the rotary tricone drill bit of the electric drilling machine to optimize penetration rate of the rotary tricone drill bit based on the drill performance data and output of one or more machine learning operations applied to the drill performance data.

An advanced real-time drilling control system can comprise circuitry configured to continuously monitor, in real time, drilling performance of an electric drilling machine as the electric drilling machine drills a blasthole using a rotary tricone drill bit. The continuous monitoring can include continuously collecting, according to a predetermined sampling rate, drill performance data from one or more sensors of the electric drilling machine in real time. The circuitry can also be configured to adjust, in real time, pulldown pressure/rate and rotary speed of the rotary tricone drill bit of the electric drilling machine to optimize penetration rate of the rotary tricone drill bit based on the drill performance data and output of one or more machine learning operations applied to the drill performance data.

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.

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.

Aspects and features of a system for real-time drilling using automated data quality control can include a computing device, a drilling tool, sensors, and a message bus. The message bus can receive current data from a wellbore. The computing device can generate and use a feature-extraction model to provide revised data values that include those for missing data, statistical outliers, or both. The model can be used to produce controllable drilling parameters using highly accurate data to provide optimal control of the drilling tool. The real-time message bus can be used to apply the controllable drilling parameters to the drilling tool.

Aspects and features of a system for real-time drilling using automated data quality control can include a computing device, a drilling tool, sensors, and a message bus. The message bus can receive current data from a wellbore. The computing device can generate and use a feature-extraction model to provide revised data values that include those for missing data, statistical outliers, or both. The model can be used to produce controllable drilling parameters using highly accurate data to provide optimal control of the drilling tool. The real-time message bus can be used to apply the controllable drilling parameters to the drilling tool.