Schlumberger Technology Corporation

Services Petroliers Schlumberger

Crispin Chatar

Jose Celaya Galvan

Soumya Gupta

Yingwei Yu

Velizar Vesselinov

Cheolkyun Jeong

Andrey Sergeevich Konchenko

Suhas Suresha

Ivan Alaniz

Erik Burton

Sergey Mikhailovich Makarychev-Mikhailov

Fatma Mahfoudh

John Z Pang

Laetitia Shao

Yezid Arevalo Romero

Indranil Roychoudhury

Oleh Petryshak

Gregory Michael Skoff

Georgia Kouyialis

Mugdha Bhusari

A method can include receiving input for a drilling operation that utilizes a bottom hole assembly and drilling fluid; generating a set of offset drilling operations using historical feature data, where the historical feature data are processed by computing feature distances; performing an assessment of the offset drilling operations as characterized by at least feature distance-based similarity between the drilling operation and the offset drilling operations; and outputting at least one recommendation for selection of one or more of a component of the bottom hole assembly and the drilling fluid based on the assessment.

Well construction equipment framework

A method for detecting an event includes measuring a pressure of a fluid with a pressure sensor. The method also includes generating a pressure spectrogram based at least in part on the pressure. The method also includes comparing the pressure spectrogram to a plurality of historical pressure spectrograms. The historical pressure spectrograms have previously been determined to be related to one or more events. The method also includes determining that the pressure spectrogram is related to an event based at least partially upon the comparison.

Event detection from pump data

A method includes receiving training images representing a portion of a drilling rig over a first period of time, associating individual training images of the training images with times at which the individual training images were captured, determining a rig state at each of the times, classifying the individual training images based on the rig state at each of the times, training a machine learning model to identify rig state based on the classified training images, receiving additional images representing the portion of the drilling rig over a second period of time, and determining one or more rig states of the drilling rig during the second period of time using the machine learning model based on the additional images.

Rig state detection using video data

A method including generating, by a navigation service, a route for navigating from a route origin to a route destination using a private roads repository. The method includes identifying a ghost origin and a ghost destination of a ghost road along the route. The method includes sending, using an application programming interface of a base roads engine, a first request for a route from the ghost origin to the ghost destination. The method includes receiving, from the base roads engine in response to the first request, a replacement section from the ghost origin to the ghost destination. The method includes replacing, in the route, the ghost road with the replacement section to create an updated route including segments. The method includes generating an estimated travel time from the route origin to the route destination over the segments of the updated route. The method includes presenting the estimated travel time.

System for offsite navigation

A method for predicting a stick-slip event includes measuring one or more surface properties using a sensor at the surface. The method also includes measuring one or more downhole properties using a downhole tool in a wellbore. The method also includes determining that the one or more surface properties and the one or more downhole properties match a distribution. The distribution occurs before two or more previously-detected stick-slip events. The method also includes determining a likelihood that a stick-slip event will occur based at least partially upon the distribution that the one or more surface properties and the one or more downhole properties match.

System and method for predicting stick-slip

A computer-implemented method for providing a voice interface system comprising: monitoring a first voice input during a training phase; monitoring manual inputs to a system during the monitoring the first voice input; storing training information associating the first voice input with the manual inputs; receiving a second voice input during an operational or runtime phase after the associating; identifying an instruction corresponding to the second voice input based on the training information; and executing the identified instruction.

Voice aware drilling control and reporting system

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Menlo Park, CA, United States of America

Crispin Chatar