Chevron U.s.a. Inc.

Dustin J Keele

Simon Clinch

Boqin Q Sun

Bo Gong

Emmanuel Toumelin

Byron Dean Gulick

A method is described for ways to generate a Fraction of Sand (F) estimate and net-to-gross (NTG) estimate of sand in a formation using a machine-learning algorithm such as a neural network based on borehole image logs. The method may use the Fand other information to estimate hydrocarbons in place in a subsurface formation. The method may be executed by a computer system.

System and method for quantitative analysis of borehole images

Exemplary implementations may: obtain subsurface relaxation time data specifying subsurface relaxation time values corresponding to a well in the subsurface volume of interest; generating a subsurface relaxation time distribution using the subsurface relaxation time data; generating a subsurface porosity distribution using the subsurface relaxation time distribution; generating a representation of the subsurface porosity distribution in the subsurface volume of interest using visual effects to depict at least one of the one or more subsurface relaxation time values; and display the representation.

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Houston, TX, United States of America

Dustin J Keele