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公开(公告)号：US20210404315A1
公开(公告)日：2021-12-30
申请号：US16652336
申请日：2019-05-16
Applicant: Landmark Graphics Corporation
Inventor： Mahdi PARAK , Srinath MADASU , Egidio MAROTTA
IPC: E21B44/02
Abstract: Systems and methods can automatically and dynamically determine an optimum frequency for data being input into a drilling optimization tool in order to provide predictive modeling for well drilling operations. The methods and systems selectively input sets of data having different frequencies into the drilling optimization tool to build different predictive models at different frequencies. An optimization algorithm such as Bayesian optimization is then applied to the models to identify in real time an optimum frequency for the data sets being input into the drilling optimization tool based on current operational and environmental parameters.
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2.发明公开公开(公告)号：US20240093605A1
公开(公告)日：2024-03-21
申请号：US17766775
申请日：2019-11-07
Applicant: LANDMARK GRAPHICS CORPORATION
Inventor： Travis St. George RAMSAY , Egidio MAROTTA , Srinath MADASU
CPC classification number: E21B49/0875 , E21B43/162 , E21B2200/22
Abstract: The present disclosure is related to improvements in methods for evaluating and predicting responses of virtual sensors to determine formation and fluid properties as well as classifying the predicted as plausible or outlier responses that can indicate the need for maintenance of downhole physical sensors. In one aspect, a method includes detecting a change to a system of operating a wellbore to yield a determination, the system including a virtual sensor, the virtual sensor including a physical sensor placed in the wellbore for collecting one or more physical properties inside the wellbore; and based on the determination, performing one of retraining a machine learning model for predicting an output of the virtual sensor or predicting an output of the virtual sensor using the machine learning mode, the predicted output being indicative of at least one of sub-surface formation or fluid properties inside the wellbore.
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公开(公告)号：US20220298917A1
公开(公告)日：2022-09-22
申请号：US17612363
申请日：2019-07-18
Applicant: LANDMARK GRAPHICS CORPORATION
Inventor： Travis St. George RAMSAY , Egidio MAROTTA , Srinath MADASU
Abstract: The present disclosure is related to improvements in methods for evaluating formation fluid properties of interest in an in-production wellbore as well as evaluating health and functionalities of physical sensors present in and collecting data within the well. In one aspect, a method includes receiving data from one or more physical sensors within a wellbore; determining at least one formation property of the wellbore using one or more machine learning models receiving the data as input and generating reservoir simulation models using the at least one formation property.
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公开(公告)号：US20210332696A1
公开(公告)日：2021-10-28
申请号：US16473134
申请日：2018-12-07
Applicant: Landmark Graphics Corporation
Inventor： Matthew Edwin WISE , Egidio MAROTTA , Keshava Prasad RANGARAJAN
Abstract: Certain aspects and features relate to a system that efficiently determines optimal actuator set points to satisfy an objective in controlling equipment such as systems for drilling, production, completion or other operations associated with oil or gas production from a wellbore. A platform can receive data and also make use of and communicate with multiple algorithms asynchronously and efficiently to project automatic optimum set points for controllable parameters. Services can provide data over a real-time messaging bus and the data can be captured by an orchestrator that aggregates all data and calls a solver orchestrator to determine optimized parameters for a current state in time to send to control systems or display in a dashboard.
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