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.

公开(公告)号：US20200256164A1

公开(公告)日：2020-08-13

申请号：US16753146

申请日：2017-11-13

Applicant: LANDMARK GRAPHICS CORPORATION

Inventor： Mahdi PARAK ,  Joseph Chukwuma NWACHUKWU

IPC: E21B43/00 ,  E21B49/00 ,  G06F30/28

Abstract: Fluid production can be simulated using a reservoir model and a tubing model. For example, pressure data and saturation data can be received from a reservoir model simulating a hydrocarbon reservoir in a subterranean formation. A tubing model can be generated by performing nodal analysis using the pressure data and the saturation data. A well-test result can be received that indicates an amount of fluid produced by the wellbore at a particular time. A tuned tubing model can be generated by adjusting the tubing model such that a tubing-model estimate of the amount of fluid produced by the wellbore at the particular time matches the well-test result. An estimated amount of fluid produced by the well-bore can then be determined using the tuned tubing model. The estimated amount of fluid produced by the wellbore may be used for production allocation or controlling a well tool.