US 12,332,094 B2
Machine learning-based wellbore fluid flow rate prediction
Mikko Jaaskelainen, Houston, TX (US); Benjamin Simon Schaeffer, Denver, CO (US); and Julian Edmund Drew, Aurora, CO (US)
Assigned to Halliburton Energy Services, Inc., Houston, TX (US)
Filed by Halliburton Energy Services, Inc., Houston, TX (US)
Filed on Sep. 28, 2022, as Appl. No. 17/955,170.
Prior Publication US 2024/0102835 A1, Mar. 28, 2024
Int. Cl. G01F 1/32 (2022.01); E21B 47/10 (2012.01); G01F 1/661 (2022.01); G01V 8/16 (2006.01)
CPC G01F 1/3227 (2013.01) [E21B 47/10 (2013.01); G01F 1/661 (2013.01); G01V 8/16 (2013.01); E21B 2200/22 (2020.05)] 20 Claims
OG exemplary drawing
 
1. A method for configuring a learning machine to predict a flow rate of at least one phase of a fluid, comprising:
determining a feature set for the learning machine, the feature set including information derived from a signal generated by a flow of the fluid interacting with a fluidic oscillator in a wellbore; and
configuring the learning machine with the feature set including information derived from the signal.