公开(公告)号：US11481706B2

公开(公告)日：2022-10-25

申请号：US16649249

申请日：2018-02-22

Applicant: Landmark Graphics Corporation

Inventor： Hewei Tang ,  Shang Zhang ,  Feifei Zhang ,  Suresh Venugopal ,  Youli Mao

IPC: G06Q10/06 ,  E21B21/08 ,  E21B44/00 ,  E21B47/00 ,  G06Q50/02

Abstract: An abnormal trend detection system for detecting one or more hazards may provide for a safe and effective drilling operation as any of the one or more hazards may be avoided. Several indicators may be defined including a first, second, third and fourth indicator. The indicators are used to identify in a trend analysis abnormal trends. One or more thresholds may be defined. When a trend analysis indicates that a threshold has been reached or exceeded an alarm may be triggered, a drilling operation may be altered or a combination thereof.

公开(公告)号：US11255180B2

公开(公告)日：2022-02-22

申请号：US16640666

申请日：2017-12-22

Applicant: Landmark Graphics Corporation

Inventor： Shang Zhang ,  Hewei Tang ,  Feifei Zhang ,  Suresh Venugopal ,  Patrick McCormack

IPC: E21B21/08 ,  E21B45/00 ,  E21B47/10 ,  E21B44/06 ,  E21B47/04 ,  E21B44/00

Abstract: Embodiments of the subject technology provide for receiving real-time drilling data comprising different drilling parameters measured during a drilling operation. The subject technology calculates a kick detection parameter based at least in part on the different drilling parameters. The subject technology detects an occurrence of a kick during the drilling operation when the kick detection parameter deviates from a trend formed by previously calculated kick detection parameters. Further, the subject technology activates an alarm during the drilling operation in response to detected occurrence of the kick to facilitate preventing a blowout.

公开(公告)号：US20200302353A1

公开(公告)日：2020-09-24

申请号：US16649249

申请日：2018-02-22

Applicant: Landmark Graphics Corporation

Inventor： Hewei Tang ,  Shang Zhang ,  Feifei Zhang ,  Suresh Venugopal ,  Youli Mao

IPC: G06Q10/06 ,  E21B44/00 ,  E21B47/00 ,  E21B21/08 ,  G06Q50/02

Abstract: An abnormal trend detection system for detecting one or more hazards may provide for a safe and effective drilling operation as any of the one or more hazards may be avoided. Several indicators may be defined including a first, second, third and fourth indicator. The indicators are used to identify in a trend analysis abnormal trends. One or more thresholds may be defined. When a trend analysis indicates that a threshold has been reached or exceeded an alarm may be triggered, a drilling operation may be altered or a combination thereof.

公开(公告)号：US20200149354A1

公开(公告)日：2020-05-14

申请号：US16611817

申请日：2018-08-31

Applicant: LANDMARK GRAPHICS CORPORATION

Inventor： Ajay Pratap Singh ,  Roxana Nielsen, Jr. ,  Satyam Priyadarshy ,  Ashwani Dev ,  Geetha Gopakumar Nair ,  Suresh Venugopal

IPC: E21B12/02 ,  G06N3/08 ,  E21B10/62

Abstract: The subject disclosure provides for a mechanism implemented with neural networks through machine learning to predict wear and relative performance metrics for performing repairs on drill bits in a next repair cycle, which can improve decision making by drill bit repair model engines, drill bit design, and help reduce the cost of drill bit repairs. The machine learning mechanism includes obtaining drill bit data from different data sources and integrating the drill bit data from each of the data sources into an integrated dataset. The integrated dataset is pre-processed to filter out outliers. The filtered dataset is applied to a neural network to build a machine learning based model and extract features that indicate significant parameters affecting wear. A repair type prediction is determined with the applied machine learning based model and is provided as a signal for facilitating a drill bit operation on a cutter of the drill bit.