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1.发明申请公开(公告)号：US20210148213A1
公开(公告)日：2021-05-20
申请号：US16616795
申请日：2017-11-15
Applicant: Landmark Graphics Corporation
Inventor： Srinath Madasu , Keshava Prasad Rangarajan , Nishant Raizada
Abstract: System and methods for optimizing parameters for drilling operations are provided. Real-time data including values for input variables associated with a current stage of a drilling operation along a planned well path are acquired. A neural network model is trained to produce an objective function defining a response value for at least one operating variable of the drilling operation. The response value for the operating variable is estimated based on the objective function produced by the trained neural network model. Stochastic optimization is applied to the estimated response value so as to produce an optimized response value for the operating variable. Values of controllable parameters are estimated for a subsequent stage of the drilling operation, based on the optimized response value of the operating variable. The subsequent stage of the drilling operation is performed based on the estimated values of the controllable parameters.
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Patent Agency Ranking
2.发明授权公开(公告)号：US11319793B2
公开(公告)日：2022-05-03
申请号：US16616795
申请日：2017-11-15
Applicant: Landmark Graphics Corporation
Inventor： Srinath Madasu , Keshava Prasad Rangarajan , Nishant Raizada
Abstract: System and methods for optimizing parameters for drilling operations are provided. Real-time data including values for input variables associated with a current stage of a drilling operation along a planned well path are acquired. A neural network model is trained to produce an objective function defining a response value for at least one operating variable of the drilling operation. The response value for the operating variable is estimated based on the objective function produced by the trained neural network model. Stochastic optimization is applied to the estimated response value so as to produce an optimized response value for the operating variable. Values of controllable parameters are estimated for a subsequent stage of the drilling operation, based on the optimized response value of the operating variable. The subsequent stage of the drilling operation is performed based on the estimated values of the controllable parameters.
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公开(公告)号：US20220003108A1
公开(公告)日：2022-01-06
申请号：US17256164
申请日：2020-02-03
Applicant: LANDMARK GRAPHICS CORPORATION
Inventor： Mahdi Parak , Srinath Madasu , Egidio Marotta , Dale McMullin , Nishant Raizada
Abstract: System and methods for event prediction during drilling operations are provided. Regression data associated with coefficients of a predictive model are retrieved for a downhole event during a drilling operation along a planned path of a wellbore. The regression data includes a record of changes in historical coefficient values associated with prior occurrences of the event. As the wellbore is drilled over different stages of the operation, a value of an operating variable is estimated based on values of the coefficients and real-time data acquired during each stage. A percentage change in coefficient values adjusted between successive stages of the operation is tracked. An occurrence of the downhole event is estimated, based on a correlation between the percentage change tracked for at least one coefficient and a corresponding change in the historical coefficient values. The path of the wellbore is adjusted, based on the estimated occurrence of the event.
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公开(公告)号：US11959374B2
公开(公告)日：2024-04-16
申请号：US17256164
申请日：2020-02-03
Applicant: LANDMARK GRAPHICS CORPORATION
Inventor： Mahdi Parak , Srinath Madasu , Egidio Marotta , Dale McMullin , Nishant Raizada
CPC classification number: E21B44/02 , G05B13/0265 , G05B13/042 , G05B13/048 , G06N20/00 , E21B2200/20 , E21B2200/22
Abstract: System and methods for event prediction during drilling operations are provided. Regression data associated with coefficients of a predictive model are retrieved for a downhole event during a drilling operation along a planned path of a wellbore. The regression data includes a record of changes in historical coefficient values associated with prior occurrences of the event. As the wellbore is drilled over different stages of the operation, a value of an operating variable is estimated based on values of the coefficients and real-time data acquired during each stage. A percentage change in coefficient values adjusted between successive stages of the operation is tracked. An occurrence of the downhole event is estimated, based on a correlation between the percentage change tracked for at least one coefficient and a corresponding change in the historical coefficient values. The path of the wellbore is adjusted, based on the estimated occurrence of the event.
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公开(公告)号：US11873707B2
公开(公告)日：2024-01-16
申请号：US16629231
申请日：2018-03-09
Applicant: LANDMARK GRAPHICS CORPORATION
Inventor： Srinath Madasu , Nishant Raizada , Keshava Rangarajan , Robello Samuel
Abstract: A system and method for controlling a drilling tool inside a wellbore makes use of projection of optimal rate of penetration (ROP) and optimal controllable parameters such as weight-on-bit (WOB), and rotations-per-minute (RPM) for drilling operations. Optimum controllable parameters for drilling optimization can be predicted using a data generation model to produce synthesized data based on model physics, an ROP model, and stochastic optimization. The synthetic data can be combined with real-time data to extrapolate the data across the WOB and RPM space. The values for WOB an RPM can be controlled to steer a drilling tool. Examples of models used include a non-linear model, a linear model, a recurrent generative adversarial network (RGAN) model, and a deep neural network model.
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公开(公告)号：US11492890B2
公开(公告)日：2022-11-08
申请号：US16631542
申请日：2017-08-21
Applicant: LANDMARK GRAPHICS CORPORATION
Inventor： Srinath Madasu , Keshava Prasad Rangarajan , Robello Samuel , Nishant Raizada
Abstract: A system for real-time steering of a drill bit includes a drilling arrangement and a computing device in communication with the drilling arrangement. The system iteratively, or repeatedly, receives new data associated the wellbore. At each iteration, a model, for example an engineering model, is applied to the new data to produce an objective function defining the selected drilling parameter. The objective function is modified at each iteration to provide an updated value for the selected drilling parameter and an updated value for at least one controllable parameter. In one example, the function is modified using Bayesian optimization The system iteratively steers the drill bit to obtain the updated value for the selected drilling parameter by applying the updated value for at least one controllable parameter over the period of time that the wellbore is being formed.
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