公开(公告)号：US20210056447A1

公开(公告)日：2021-02-25

申请号：US17000096

申请日：2020-08-21

Applicant: Landmark Graphics Corporation

Inventor： Keshava Prasad Rangarajan ,  Raja Vikram R. Pandya ,  Srinath Madasu ,  Shashi Dande

IPC: G06N5/04 ,  G06N20/00 ,  H04L9/06 ,  E21B49/00

Abstract: A system for managing well site operations, the system comprising executable partitions, predictive engines, node system stacks, and a blockchain. The predictive engines comprise an Artificial Intelligence (AI) algorithm to generate earth model variables using a physics model, well log data variables, and seismic data variables. The node system stacks are coupled to the blockchain, sensors, and machine controllers. Each node system stack comprises a Robot Operating System (ROS) based middleware controller, with each coupled to each partition, each node system stack, each predictive engine, and an AI process or processes. The blockchain comprises chained blocks of a distributed network. The distributed network comprises a genesis block and a plurality of subsequent blocks, each subsequent block comprising a well site entry and a hash value of a previous well site entry. The well site entry comprises operation control variables. The operation control variables are based on the earth model variables.

公开(公告)号：US11795804B2

公开(公告)日：2023-10-24

申请号：US16764558

申请日：2019-07-12

Applicant: Landmark Graphics Corporation

Inventor： Yashas Malur Saidutta ,  Srinath Madasu ,  Shashi Dande ,  Keshava Prasad Rangarajan ,  Raja Vikram R. Pandya ,  Jeffrey M. Yarus ,  Robello Samuel

IPC: E21B44/00 ,  E21B7/04 ,  E21B41/00 ,  G06Q10/0631

CPC classification number: E21B44/00 ,  E21B7/04 ,  E21B41/00 ,  G06Q10/06313 ,  E21B2200/22

Abstract: A drilling device may use a concurrent path planning process to create a path from a starting location to a destination location within a subterranean environment. The drilling device can receive sensor data. A probability distribution can be generated from the sensor data indicating one or more likely materials compositions that make up each portion of the subterranean environment. The probability distribution can be sampled, and for each sample, a drill path trajectory and drill parameters for the trajectory can be generated. A trained neural network may evaluate each trajectory and drill parameters to identify the most ideal trajectory based on the sensor data. The drilling device may then initiate drilling operations for a predetermined distance along the ideal trajectory.

公开(公告)号：US20220253052A1

公开(公告)日：2022-08-11

申请号：US17626368

申请日：2020-01-16

Applicant: Landmark Graphics Corporation

Inventor： Aditya Chemudupaty ,  Srinath Madasu ,  Shashi Dande ,  Keshava Prasad Rangarajan ,  Rohan Lewis

IPC: G05B23/02

Abstract: A method for detecting anomalies in a piece of wellsite equipment. The method may include measuring data related to the piece of wellsite equipment. The method may also include encoding the measured data with a first autoencoder to produce a first set of encoded data. The method may further include performing a first Gaussian process regression (“GPR”) on the first set of encoded data to produce a first set of results that identifies a first anomaly in the measured data and that provides a first confidence interval for the first anomaly.

公开(公告)号：US20220228465A1

公开(公告)日：2022-07-21

申请号：US17613761

申请日：2019-07-02

Applicant: Landmark Graphics Corporation

Inventor： Srinath Madasu ,  Shashi Dande ,  Keshava Prasad Rangarajan

IPC: E21B43/12

Abstract: A system and method for controlling a gas supply to provide gas lift for wellbore(s) using Bayesian optimization. A computing device controls a gas supply to inject gas into wellbore(s). The computing device receives first reservoir data associated with a first subterranean reservoir and simulates production using the first reservoir data, using a model for the first subterranean reservoir. The production simulation provides first production data. The computing device receives second reservoir data associated with a subterranean reservoir and simulates production using the second reservoir data, using a model for the second subterranean reservoir. The production simulation provides second production data. A Bayesian optimization of an objective function of the first and second production data subject to any gas injection constraints can be performed to produce gas-lift parameters. The gas-lift parameters can be applied to the gas supply to control injection of gas into the wellbore(s).

公开(公告)号：US20210058235A1

公开(公告)日：2021-02-25

申请号：US17000087

申请日：2020-08-21

Applicant: Landmark Graphics Corporation

Inventor： Keshava Prasad Rangarajan ,  Raja Vikram R. Pandya ,  Srinath Madasu ,  Shashi Dande

IPC: H04L9/06 ,  G06N20/00 ,  G06N7/00 ,  H04L9/00 ,  H04L9/32

Abstract: A system for managing well site operations comprising a well site operations module, a chain of blocks of a distributed network, and a sensor bank and control module. The operations module generates earth model variables using a physics model, well log variables or seismic variables, or both, and a trained AI/ML algorithmic model. The chain of blocks comprises a plurality of subsequent blocks. Each subsequent block comprises a well site entry and a hash value of a previous well site entry. A well site entry comprises transacted operation control variables. The well site operations module generates production operation control variables or development operation control variables from earth model variables. The well site entry can also include transacted earth model variables and sensor variables. The sensor bank and control module provides well log variables and the operations module couples control variables to the control module to control well site equipment.

公开(公告)号：US20230116456A1

公开(公告)日：2023-04-13

申请号：US17047109

申请日：2020-06-05

Applicant: Landmark Graphics Corporation

Inventor： Yashas Malur Saidutta ,  Raja Vikram R Pandya ,  Srinath Madasu ,  Shashi Dande ,  Keshava Rangarajan

IPC: E21B44/00 ,  G06N3/092

Abstract: Systems and methods for automated drilling control and optimization are disclosed. Training data, including values of drilling parameters, for a current stage of a drilling operation are acquired. A reinforcement learning model is trained to estimate values of the drilling parameters for a subsequent stage of the drilling operation to be performed, based on the acquired training data and a reward policy mapping inputs and outputs of the model. The subsequent stage of the drilling operation is performed based on the values of the drilling parameters estimated using the trained model. A difference between the estimated and actual values of the drilling parameters is calculated, based on real-time data acquired during the subsequent stage of the drilling operation. The reinforcement learning model is retrained to refine the reward policy, based on the calculated difference. At least one additional stage of the drilling operation is performed using the retrained model.

公开(公告)号：US20210404313A1

公开(公告)日：2021-12-30

申请号：US16764558

申请日：2019-07-12

Applicant: Landmark Graphics Corporation

Inventor： Yashas Malur Saidutta ,  Srinath Madasu ,  Shashi Dande ,  Keshava Prasad Rangarajan ,  Raja Vikram R. Pandya ,  Jeffrey M. Yarus ,  Robello Samuel

IPC: E21B44/00 ,  E21B7/04 ,  E21B41/00

Abstract: A drilling device may use a concurrent path planning process to create a path from a starting location to a destination location within a subterranean environment. The drilling device can receive sensor data. A probability distribution can be generated from the sensor data indicating one or more likely materials compositions that make up each portion of the subterranean environment. The probability distribution can be sampled, and for each sample, a drill path trajectory and drill parameters for the trajectory can be generated. A trained neural network may evaluate each trajectory and drill parameters to identify the most ideal trajectory based on the sensor data. The drilling device may then initiate drilling operations for a predetermined distance along the ideal trajectory.

公开(公告)号：US12104489B2

公开(公告)日：2024-10-01

申请号：US17619784

申请日：2020-02-10

Applicant: Landmark Graphics Corporation

Inventor： Raja Vikram Raj Pandya ,  Srinath Madasu ,  Keshava Prasad Rangarajan ,  Shashi Dande ,  Yashas Malur Saidutta

IPC: E21B7/04 ,  E21B44/02

CPC classification number: E21B7/04 ,  E21B44/02

Abstract: Geosteering can be used in a drilling operation to create a wellbore that is used to extract hydrocarbons from a defined zone within the subterranean formation. According to some aspects, generating paths for the wellbore may include using path-planning protocols and pure-pursuit protocols. The pure-pursuit protocol may be executed to output a plurality of candidate drilling paths. The output may also include control parameters for controlling the drill bit. A trajectory optimizer may determine a result of multi-objective functions for each candidate path. A cost function may represent a cost or loss associated with a candidate path. Additionally, the trajectory optimizer may perform an optimization protocol, such as Bayesian optimization, on the cost functions to determine which candidate path to select. The selected candidate path may correspond to new control parameters for controlling the drill bit to reach the target location.

公开(公告)号：US20220316278A1

公开(公告)日：2022-10-06

申请号：US17619784

申请日：2020-02-10

Applicant: Landmark Graphics Corporation

Inventor： Raja Vikram Raj Pandya ,  Srinath Madasu ,  Keshava Prasad Rangarajan ,  Shashi Dande ,  Yashas Malur Saidutta

IPC: E21B7/04

Abstract: Geosteering can be used in a drilling operation to create a wellbore that is used to extract hydrocarbons from a defined zone within the subterranean formation. According to some aspects, generating paths for the wellbore may include using path-planning protocols and pure-pursuit protocols. The pure-pursuit protocol may be executed to output a plurality of candidate drilling paths. The output may also include control parameters for controlling the drill bit. A trajectory optimizer may determine a result of multi-objective functions for each candidate path. A cost function may represent a cost or loss associated with a candidate path. Additionally, the trajectory optimizer may perform an optimization protocol, such as Bayesian optimization, on the cost functions to determine which candidate path to select. The selected candidate path may correspond to new control parameters for controlling the drill bit to reach the target location.

公开(公告)号：US20220298907A1

公开(公告)日：2022-09-22

申请号：US17619304

申请日：2019-12-31

Applicant: Landmark Graphics Corporation

Inventor： Venugopal Devarapalli ,  Srinath Madasu ,  Shashi Dande ,  Keshava Prasad Rangarajan

IPC: E21B44/00 ,  G06N3/08 ,  G06N3/04 ,  E21B7/04

Abstract: Certain aspects and features relate to a system for trajectory planning and control for new wellbores. Data can be received for multiple existing wells associated with a subterranean reservoir and used to train a deep neural network model to make accurate well property projections at any other location in the reservoir. A model of features for specific well locations based on seismic attributes of the well location can be automatically generated, and the model can be used in drilling trajectory optimization. In some examples, the system builds a deep neural network (DNN) model based on the statistical features, and trains the DNN model using Bayesian optimization to produce an optimized DNN model. The optimized model can be used to provide drilling parameters to produce an optimized trajectory for a new well.