公开(公告)号：US11269100B2

公开(公告)日：2022-03-08

申请号：US16610031

申请日：2017-12-21

Applicant: Landmark Graphics Corporation

Inventor： Youli Mao ,  Raja Vikram Pandya ,  Bhaskar Mandapaka ,  Keshava Prasad Rangarajan ,  Srinath Madasu ,  Satyam Priyadarshy ,  Ashwani Dev

IPC: G01V1/30 ,  G01V1/50 ,  G06K9/62 ,  G06N7/00 ,  G06N20/00

Abstract: A method includes receiving a training selection of a first set of faults located in a first subset of a seismic dataset for a subsurface geologic formation, detecting a second set of faults in the seismic dataset based on fault interpretation operations using a first set of interpretation parameters, and determining a difference between the first set of faults and the second set of faults. The method also includes generating a second set of interpretation parameters for the fault interpretation operations based on the difference between the first set of faults and the second set of faults, and determining a feature of the subsurface geologic formation based on fault interpretation operations using the second set of interpretation parameters.

公开(公告)号：US20220034220A1

公开(公告)日：2022-02-03

申请号：US17276985

申请日：2018-11-30

Applicant: Landmark Graphics Corporation

Inventor： Srinath Madasu ,  Ashwani Dev ,  Keshava Prasad Rangarajan ,  Satyam Priyadarshy

IPC: E21B47/12 ,  E21B47/07 ,  E21B47/10 ,  E21B43/12

Abstract: A system for determining real time cluster efficiency for a pumping operation in a wellbore includes a pump, a surface sensor, a downhole sensor system, and a computing device. The pump can pump slurry or diverter material in the wellbore. The surface sensor can be positioned at a surface of the wellbore to detect surface data about the pump. The downhole sensor system can be positioned in the wellbore to detect downhole data about an environment of the wellbore. The computing device can receive the surface data from the surface sensor, receive the downhole data from the downhole sensor system, apply the surface data and the downhole data to a long short-term memory (LSTM) neural network to produce a predicted cluster efficiency associated with operational settings of the pump, and control the pump using the operational settings to achieve the predicted cluster efficiency.