Arrangement for detecting water in a material flow during drilling, wherein the arrangement includes a control unit, a data acquisition unit and a sensor, wherein the sensor includes at least two probes, wherein the at least two probes are to be arranged in contact with the material flow and are connected to a programmable voltage source and a programmable voltage receiver. The arrangement is configured tomeasure a ratio between a received voltage waveform and an applied voltage waveform for a set of pre-determined frequencies; determine a complex impedance between the at least two probes for each of the pre-determined frequencies, based on the measured ratio; and determine a set of time mean values of the determined complex impedance for each of the pre-determined frequencies, using a time window.

Systems and methods for instructing a device within a wellbore of a subterranean well includes a drill string with an actuator assembly extending into the subterranean. The actuator assembly has a first pipe member with a segment formed of a first material. A second pipe member is coaxially aligned with the first pipe member. A plurality of bearings are positioned between the first pipe member and the second pipe member. Each of the plurality of bearings includes a second material. The first material is reactive to the second material. Certain of the plurality of bearings are changeable bearings that include a dissolvable material. The actuator assembly is operable to instruct an operation of the device by generating an instruction signal by rotating the first pipe member relative to the second pipe member and interpreting a pattern of a reaction of the segment as a bearing rotates past the segment.

Exemplary embodiments are directed to a system and method for continuous downlinking communication from a surface location to a bottom hole assembly during drilling operations. The system transmits harmonic pressure wave fluctuations generated by a modulator, which is disposed outside of a surface-located fluid line with a flap rotatably disposed entirely inside of the fluid line encoding data by harmonics. One letter of the combinatorial frequencies signal alphabet can have more than 200 different orthogonal frequencies components; each component represents a unique combination of downlinking command purpose and value. For deepest portion of a long trajectory well, the system uses a narrow frequency range (2-3 Hz) with two letters resulting in more than 250 combinations. The system provides continuous automatic downhole control of the signal-to-noise ratio to achieve robust decoding of downlinking signals with a transmission data rate ten times faster as compared to 1-2 bits per minute in the industry.

Drilling parameters for a wellbore operation can be determined based on resonance speeds. For example, a system can receive real-time data for a drilling operation that is concurrently occurring with receiving the real-time data. The system can determine, for a drilling depth, a rotations-per-minute (RPM) value corresponding to a resonance speed based on a weight-on-bit (WOB) value and the real-time data. The system can generate a plot of the WOB value and the RPM value corresponding to the resonance speed. The system can determine drilling parameters for the drilling operation based on the plot. The drilling parameters can exclude, for the WOB value, the RPM value corresponding to the resonance speed.

Systems and methods for machine learning (ML) assisted parameter matching are disclosed. Wellsite data is acquired for one or more existing production wells in a hydrocarbon producing field. The wellsite data is transformed into one or more model data sets for predictive modeling. A first ML model is trained to predict well logs for the existing production well(s), based on the model data set(s). A first well model is generated to estimate production of the existing production well(s) based on the predicted well logs. Parameters of the first well model are tuned based on a comparison between the estimated and an actual production of the existing production well(s). A second ML model is trained to predict parameters of a second well model for a new production well, based on the tuned parameters of the first well model. The new well’s production is forecasted using the second ML model.

Embodiments of the invention provide an untethered apparatus for measuring properties along a subterranean well. According to at least one embodiment, the untethered apparatus includes a housing, and one or more sensors configured to measure data along the subterranean well. The data includes one or more physical, chemical, geological or structural properties in the subterranean well. The untethered apparatus further includes a processor configured to control the one or more sensors measuring the data and to store the measured data, and a transmitter configured to transmit the measured data to a receiver arranged external to the subterranean well. Further, the untethered appratus includes a controller configured to control the buoyancy or the drag of the untethered apparatus to control a position of the untethered apparatus in the subterranean well. The processor includes instructions definining measurement parameters for the one or more sensors of the untethered apparatus within the subterranean well.

A downhole sub has a body defined by a wall extending in an axial direction from a first end to a second end. An inner surface of the wall defines a flow path through the downhole sub and an outer surface of the wall defines an outer diameter of the downhole sub. A compartment extends from the outer surface into the wall to having a depth less than a thickness of the wall. A housing may be removably fixed in the compartment. One or more mobile devices may be disposed in the housing. Each of the one or more mobile devices includes a sensor encapsulated in a protective material. A control element may block an opening of the housing, the control element is made of a dissolvable material configured to dissolve at a predetermined depth in a wellbore and release the one or more mobile devices into the wellbore.

A system includes a sliding sleeve, a ball landing seat, microchips, a ball catcher, and a charging ring. The sliding sleeve is installed within a tubular body. The tubular body has an exit groove. The ball landing seat is formed by the sliding sleeve and is configured to receive a ball. The plurality of microchips are housed in a microchip ring installed within the sliding sleeve. The plurality of microchips are configured to be released into the well to gather data upon reception of the ball in the ball landing seat. The ball catcher is configured to receive and hold the ball after the plurality of microchips are released into the well. The charging ring is electronically connected to the microchip ring and has a circuit, a power source, and a charging coil. The circuit has a voltage regulation chip, a microprocessor, and a circuit motion sensor.

A computer-implemented method, medium, and system for geological core property prediction using machine learning modeling are disclosed. In one computer-implemented method, multiple imagery data of a core sample of a wellbore are received. The multiple imagery data are partitioned into multiple image patches. Multiple first vectors of encoded features in a latent space are generated based on the multiple image patches. Multiple image features of the core sample of the wellbore are generated based on the multiple imagery data. Multiple second vectors of encoded features in the latent space are generated based on the multiple image features. Multiple rock properties associated with the core sample of the wellbore are predicted by running a regressor in the DFCN based on the multiple first vectors and the multiple second vectors. The multiple rock properties are provided for determining multiple properties of a subsurface reservoir that includes the wellbore.

A method for determining conditions in a wellbore extending through a subterranean formation includes: (a) deploying a plurality of sensor pods in the wellbore, wherein each sensor pod includes a housing and a plurality of sensors disposed in the housing; (b) measuring and recording a plurality of pressures and a plurality of temperatures with plurality of sensors of each sensor pod; (c) dissolving the housings of the pods to release the plurality of sensors from the pods after (b); and (d) lifting the sensors to the surface after (c).