US 12,410,689 B2
Flow simulator for generating reservoir management workflows and forecasts based on analysis of high-dimensional parameter data space
Yevgeniy Zagayevskiy, Houston, TX (US); Shohreh Amini, Houston, TX (US); Srinath Madasu, Houston, TX (US); Zhi Chai, Houston, TX (US); and Azor Nwachukwu, Houston, TX (US)
Assigned to Landmark Graphics Corporation, Houston, TX (US)
Filed by Landmark Graphics Corporation, Houston, TX (US)
Filed on Sep. 8, 2020, as Appl. No. 17/014,331.
Claims priority of provisional application 62/929,027, filed on Oct. 31, 2019.
Prior Publication US 2021/0133375 A1, May 6, 2021
This patent is subject to a terminal disclaimer.
Int. Cl. E21B 43/00 (2006.01); E21B 21/08 (2006.01); E21B 47/003 (2012.01); G01V 20/00 (2024.01); G06F 18/20 (2023.01); G06F 30/27 (2020.01); G06F 113/08 (2020.01)
CPC E21B 43/00 (2013.01) [E21B 21/08 (2013.01); E21B 47/003 (2020.05); G01V 20/00 (2024.01); G06F 18/29 (2023.01); G06F 30/27 (2020.01); E21B 2200/20 (2020.05); G01V 2210/665 (2013.01); G06F 2113/08 (2020.01)] 18 Claims
OG exemplary drawing
 
1. An apparatus for generating forecasts from an input high-dimensional parameter data space, the apparatus comprising:
a reservoir model that includes comprising a plurality of input variables, a plurality of output variables, and at least one algorithmic model, wherein the plurality of input variables and the plurality of output variables are generated by a flow simulator module based on variables from a formation and reservoir properties database and a field database, wherein the flow simulator module is configured to generate the at least one algorithmic model and the plurality of output variables using at least one simulator selected from a full-physics flow simulator, a proxy flow simulator for assisted history matching, and a proxy flow simulator for field development optimization; and
a model order reduction module configured to generate a subset of the plurality of input variables having a reduced parameter space relative to the input high-dimensional parameter data space by identifying input variables within the plurality of input variables useful to approximate at least one output variable of the plurality of output variables, wherein the model order reduction module uses a function decomposition algorithm to identify the input variables within the plurality of input variables useful to approximate the at least one output variable so as to generate the subset of the plurality of input variables with a reduced number of input variables such that the subset of input variables of the plurality of input variables most effectively approximates the at least one output variable using the selected at least one simulator, and wherein the at least one selected simulator is further configured to generate the at least one algorithmic model using at least one of the variables used by the reservoir model, associated history matching input variables, and optimization input variables depending on the selection of the at least one simulator.