Disclosed is a system and method for calculating a formation shear-wave slowness. The system includes a borehole sonic logging tool and an information handling system. The borehole sonic logging tool may comprise a transmitter comprising one or more elements disposed at one or more radial distances from an axis of the borehole sonic logging tool and the transmitter is configured to transmit a first mode into a borehole. The sonic logging tool may further include one or more receivers disposed at a second radial distance from the axis of the borehole sonic logging tool and are configured to detect a second mode that one or more lobes than is a higher order than the first mode. A method may comprise broadcasting the first mode into the borehole, recording the second mode from the borehole with the one or more receivers, and calculating the formation shear-wave slowness from the second mode.

An integrated data recorder may be positioned within a slot in a tool. The integrated data recorder includes a sensor package that includes one or more drilling dynamics sensors, a processor in data communication with the one or more drilling dynamics sensors, a memory module in data communication with the one or more drilling dynamics sensors, a wireless communications module in data communication with the processor, and an electrical energy source in electrical communication with the memory module, the one or more drilling dynamics sensors, and the processor.

A system and method that includes querying a database to obtain offset well data collected while drilling previously drilled wells. The system and method also include determining if at least one risk is identified with respect to a planned well based on the offset well data. The system and method additionally include generating a machine learning model based on the at least one risk that is identified based on the offset well data. The system and method further include predicting at least one drilling risk based on the machine learning model, wherein a drill plan that includes drilling parameters is adjusted based on the at least one predicted drilling risk.

Using machine learning for sedimentary facies prediction by using one or more logs acquired in a borehole. This includes performing a petrophysical clustering of borehole depths wherein the depths of the borehole are gathered into clusters based on similarities in the one or more logs. Also performed is a log inclusion optimization, including a selection of one or more parameters of the petrophysical clustering, wherein the one or more parameters include a number and/or type of considered logs among the one or more logs and/or a clustering method. Also performed is a classification of the clusters into core depositional facies using one or more predetermined rules.

A system for looking ahead of a drill bit includes a plane wave generator (PWG) tool deployed downhole inside a wellbore for formation evaluation and generation of reflection data, a power source providing electric power to the PWG tool for the formation evaluation and the generation of the reflection data, a surface control system receiving the reflection data from the PWG tool and generating image data of a subsurface rock formation based on the received reflection data, and a wireline that electrically couples the PWG tool to the power source and communicatively couples the PWG tool to the surface control system. The PWG tool includes a beam forming network (BFN) architecture and a plurality of antenna elements mounted to a base of the PWG tool to transmit and receive electromagnetic signals.

An integrated data recorder may be positioned within a slot in a tool. The integrated data recorder includes a sensor package that includes one or more drilling dynamics sensors, a processor in data communication with the one or more drilling dynamics sensors, a memory module in data communication with the one or more drilling dynamics sensors, a wireless communications module in data communication with the processor, and an electrical energy source in electrical communication with the memory module, the one or more drilling dynamics sensors, and the processor.

A system can include a processor; memory operatively coupled to the processor; and processor-executable instructions stored in the memory to instruct the system to: receive a marker on a well log for a well in a geographic region; and iteratively propagate the marker automatically to a plurality of well logs for other wells in the geographic region.

A method for hydrocarbon exploration based on imaging tunnel valleys is disclosed. The method includes obtaining a 3D seismic volume data corresponding to a target formation having at least one tunnel valley, interpreting a key horizon at or above the target formation as preparation for paleo-depositional environment restoration, flattening and decimating the 3D seismic volume data using the key horizon for paleo-depositional environment restoration to obtain a conditioned 3D seismic volume data, analyzing the conditioned 3D seismic volume data for frequency content and decomposing the conditioned 3D seismic volume data into at least three attributes, blending the at least three attributes to form a single seismic volume data to illuminate key features, and displaying, on a map, a distribution of the tunnel valleys in the 3D seismic volume data of the target formation.

A system for collecting subsurface formation data in a petroleum exploration environment includes a drilling tool and a subsurface formation data hub. A drilling tool may include drill pipe, a geophone, a drilling hammer, and a drill bit. The subsurface formation data hub may comprise a seismic data processor and a user interface. The seismic data processor may be operable to drive the drilling hammer at a frequency and an energy, synchronize the geophone to sense seismic vibration at a frequency, and determine subsurface formation properties. The user interface may be operable to display subsurface formation data. A method of collecting subsurface formation data in a petroleum exploration environment may include defining a drilling hammer frequency and energy, synchronizing a geophone to sense seismic vibration at a frequency, generating an impact in the petroleum exploration environment, receiving a returning seismic vibration at the geophone, and collecting subsurface formation data.

A method for estimating a borehole condition using a Stoneley measurement is provided. The method comprises recording acoustic waveforms obtained from one or more receivers, applying a time window to the acoustic waveforms to extract Stoneley components, computing energies of the Stoneley components within a frequency band, and obtaining at least one of borehole conditions based on the energies of Stoneley components.