Schlumberger Technology Corporation

Sylvain Chambon

Richard John Meehan

Yingwei Yu

Qiuhua Liu

Yuelin Shen

Velizar Vesselinov

Jean-Pierre Poyet

Minh Trang Chau

Wei Chen

Raymond Lin

Benoit Foubert

Sandra Reyes

Mohammad Khairi Hamzah

A system and method that include receiving sensor data acquired during execution of a drilling operation workflow and generating state information of a wellsite system and receiving contextual information for a role associated with a workflow that includes one or more tasks of the workflow. The system and method also include generating a natural language report based at least in part on the state information and based at least in part on the contextual information to facilitate planning and execution of the one or more tasks of the workflow. The system and method further include transmitting the natural language report via a network interface based at least in part on an identifier associated with the role and presenting a graphical user interface that renders information as to the planning and execution of the one or more tasks of the workflow to achieve a desired state of the wellsite system.

Wellsite report system

A system and method that include receiving sensor data during drilling of a portion of a borehole in a geologic environment. The system and method also include selecting a drilling mode from a plurality of drilling modes based at least on a portion of the sensor data. The system and method additionally include simulating drilling of the borehole using the selected drilling mode and generating a state of the borehole in the geologic environment based on the simulated drilling of the borehole. The system and method further include generating a reward using the state of the borehole and a planned borehole trajectory and using the reward through deep reinforcement learning to maximize future rewards for drilling actions.

Drilling control

A system and method that can include training a deep neural network using time series data that represents functions of a non-linear Kalman filter that represents a dynamic system of equipment and environment and models a pre-defined operational procedure as a temporal sequence. The system and method can also include receiving operation data from the equipment responsive to operation in the environment and outputting an actual operation as an actual sequence of operational actions by the deep neural network. The system and method can additionally include performing an operation-level comparison to evaluate the temporal sequence against the actual sequence using a distance function in a latent space of the deep neural network and outputting a score function that quantifies the distance function in the latent space. The system and method can further include controlling an electronic component to execute an electronic operation based on the score function.

Field operations system with filter

Growing community of inventors

Clamart, France

Sylvain Chambon