公开(公告)号：US20250034968A1

公开(公告)日：2025-01-30

申请号：US18360406

申请日：2023-07-27

Applicant: Landmark Graphics Corporation

Inventor： Bilal Hungund ,  Rahul Saraf

IPC: E21B34/10 ,  E21B34/16

Abstract: Some implementations include a method for predicting closure of a subsurface safety valve (SCSSV) configured to shut-in a well without any sensors on the SCSSV. The method may include obtaining, by a learning machine, sensor readings indicating downhole conditions in the well. The method may include predicting, by the learning machine, closure of the SCSSV based on the sensor readings indicating downhole conditions in the well. The method may include transmitting a communication predicting closure of the SCSSV.

公开(公告)号：US20240371154A1

公开(公告)日：2024-11-07

申请号：US18312084

申请日：2023-05-04

Applicant: Landmark Graphics Corporation

Inventor： Bilal Hungund ,  Gurunath Gandikota ,  Geetha Nair

IPC: G06V20/13 ,  G06Q50/26

Abstract: A method for determining an emissions associated with hydrocarbon recovery of a hydrocarbon site within a geographic region, the method comprises selecting the hydrocarbon site for which to determine the emissions. The method comprises determining current values of hydrocarbon related attributes that affect emissions at the hydrocarbon site for a current time frame. The method comprises inputting the current values of the hydrocarbon related attributes related to emissions at the hydrocarbon site into a learning machine to generate an emissions factor for each of the hydrocarbon related attributes that affect the emissions at the hydrocarbon site.

公开(公告)号：US20230392498A1

公开(公告)日：2023-12-07

申请号：US17833873

申请日：2022-06-06

Applicant: Landmark Graphics Corporation

Inventor： Shreshth Srivastav ,  Ashutosh Kaushik ,  Bilal Hungund

IPC: E21B49/08 ,  E21B47/10

CPC classification number: E21B49/0875 ,  E21B47/10 ,  E21B2200/22

Abstract: A system can collect a first set of equipment data and emissions data from a first hydrocarbon operation location. The system can train at least one machine-learning model to estimate an emission factor of at least one equipment component of the first hydrocarbon operation location using the first set of equipment data and the emissions data of the first hydrocarbon operation location. The system can then apply the at least one machine-learning model to a second set of equipment data to estimate total emissions over a predetermined amount of time at a second hydrocarbon operation location.