Halliburton Energy Services, Inc.

Richard Gibson

Mikko K Jaaskelainen

Julian Drew

Barry Fish

Benjamin Simon Schaeffer

Werner Heigl

David Diller

A method can be used to determine multi-phase measurements of fluid flowing with respect to a wellbore. Signals can be received, and the signals can be emitted by each variable frequency acoustic emitter of a set of variable frequency acoustic emitters positioned spaced apart in a sensing transducer that is in an interior of a wellbore. The received signals can be converted into a flow rate of each of a set of different fluid phases of a fluid in the wellbore. The multi-phase measurements of the fluid can be determined using the converted flow rate.

Oil and gas well multi-phase fluid flow monitoring with multiple transducers and machine learning

Aspects of the subject technology relate to systems, methods, and computer-readable media for machine learning analysis of low-frequency signal data in fracturing operations. The present technology can receive strain data associated with a monitoring well that is proximate to a treatment well. The strain data can comprise information representing a fracturing operation associated with the treatment well. Further, the present technology can convert the strain data into image data where a color scale corresponds to a degree of strain observed by a fiber optic cable deployed in the monitoring well. As follows, the present technology can provide the image data to a machine-learning model, which is configured to identify one or more features in the image data.

Machine learning analysis of low-frequency signal data in fracturing operations

Growing community of inventors

Littleton, CO, United States of America

Richard Gibson