Schlumberger

A method of synthesizing a monolithic structure is provided, which involves casting a gel of nanoparticle material using a mold body. The gel includes the nanoparticle material in reaction media. The mold body is dissolvable in media different from the reaction media at predefined process conditions. Other aspects are described and claimed.

An apparatus is provided for use in a chemical process, which includes at least one metal tube or flow channel having at least one surface with at least one organic linker attached thereto. The at least one organic linker has first and second molecular groups, wherein the first molecular group is configured to bind to the at least one surface, and wherein the second molecular group is configured to bind to at least one compound that functions as an adsorbent or catalyst in the chemical process in order to attach the at least one compound to the at least one surface. Methods of constructing an apparatus for use in a chemical process are also described and claimed.

A packed bed unit for chemical processing is described. The packed bed unit includes packing material disposed within the packed bed unit, wherein the packing material includes a plurality of different compositions distributed in the packed bed unit.

A method can include receiving a target density value for a drilling fluid exiting a sedimentation device; receiving a measured density value for the drilling fluid directed to the sedimentation device, a measured density value for the drilling fluid exiting the sedimentation device, and an incoming flow rate value for the drilling fluid directed to the sedimentation device; and generating control instructions for control of an injection pump to regulate a diluent injection pump rate to dilute the drilling fluid entering the sedimentation device to achieve the target density value.

Systems and methods for enhancing wireline conveyance modeling in wireline conveyance using a physics-informed neural network (PINN) are provided. A method includes: receiving historical job data from at least one past wireline conveyance operation, the historical job data including: static input data, and timeseries input data, processing the historical job data through a neural network (NN) configured to learn the relationships between input features and target variables including: an input layer, a plurality of hidden layers, and an output layer, integrating the neural network with a numerical physics-based wireline conveyance model to form a physics-informed neural network (PINN), training the PINN using the historical job data and estimation results of the physical model to enhance prediction accuracy, utilizing the trained PINN to predict at least one physical parameter for a current wireline conveyance operation, and outputting the predicted at least one physical parameter for use in the wireline conveyance operation.

Systems and methods presented herein provide for cutting in a borehole or casing. A cutting device can include a first arm having a cutting blade, wherein the cutting blade has side cutting teeth and an axis of rotation that is substantially at a right angle with respect to an axis of the tool body. The cutting device can also include a second arm with a bumper. The first and second arms articulate away from the elongate body in different directions to reduce vibrations while cutting. A control device can automate the cut based on hydraulic pressure measurements. Additionally, the cutting device can also be extended or rotated on a rotary index. The cutting device can rotate around a J slot, in an example.

A system and method are provided for installing a well for a borehole heat exchanger. The method includes drilling a hole formation to a predetermined depth relative to a ground surface, including operating a bottomhole assembly (BHA) including a drill bit (108) supported at a bottom end of a cable (118) positioned within a flexible tube (104). After drilling the hole formation to a predetermined depth, the BHA is retracted through the flexible tube to remove the BHA from the hole formation while the flexible tube remains in the hole formation.

A method for estimating dogleg severity includes rotating the downhole tool in a wellbore. The downhole tool includes a roll stabilized sensor housing deployed in a rotating collar. The collar includes at least first and second magnets deployed thereon. Cross-axial magnetic field measurements are made using a magnetic field sensor deployed in the sensor housing while the collar rotates. A distortion is identified in the magnetic field measurements. The dogleg severity is estimated from the distortion.

A method for surveying a wellbore includes rotating a wellbore surveying tool in a wellbore. The wellbore surveying tool includes a plurality of magnetometers, a plurality of accelerometers, and, optionally, a plurality of temperature sensors. Sensor measurements are made while the survey tool rotates in the wellbore. A failed accelerometer or a failed temperature sensor is automatically detected from the accelerometer measurements or the temperature measurements. Corrected sensor measurements are computed for the failed sensor from selected ones of the magnetometer measurements, the accelerometer measurements, and the temperature measurements and used to further compute at least one of a wellbore inclination or a wellbore azimuth.

A method for surveying a wellbore includes rotating a downhole tool having a tilted survey sensor in the wellbore. The tilted survey sensor has a sensory axis that is rotationally offset from a longitudinal axis of the downhole tool and is used to make sensor measurements while rotating the downhole tool in the wellbore. The sensor measurements are fit with a sinusoidal fitting function to obtain first and second fitting parameters. A wellbore survey parameter such as wellbore inclination or wellbore azimuth is computed from the first and second fitting parameters.