Schlumberger Technology Corporation

Services Petroliers Schlumberger

Geoquest Systems B.v.

Nadege Bize-Forest

Robert L Kleinberg

Josselin Kherroubi

Austin Boyd

Isabelle Le Nir

Robert Laronga

Andre Bertolini

Flavio Da Costa Ferreira

Stacy L Reeder

Peter Schlicht

Rodolfo Oliveira

Victoria Baines

Emmanuel Bize

Lucas Lima De Carvalho

Laura Lima Angelo Dos Santos

Robert J Laronga

Generating a virtual core includes obtaining acquired data for a region of interest, determining a rock type of the region of interest, obtaining a selection of modules based on the rock type, and generating, using the acquired data and an interpolator from the modules, a wellbore image of the region of interest. The interpolator generates interpolated data between data points among the acquired data in the wellbore image. Further, using a quantifier from the plurality of modules, a core characterization of the region of interest is determined. The core characterization describes an integration of wellbore data types. Using the core characterization and the wellbore image, a digital core construction of the region of interest is generated. The digital core construction describes subterranean formation properties of the region of interest.

Method and system for generating a virtual core

Using machine learning for sedimentary facies prediction by using one or more logs acquired in a borehole. This includes performing a petrophysical clustering of borehole depths wherein the depths of the borehole are gathered into clusters based on similarities in the one or more logs. Also performed is a log inclusion optimization, including a selection of one or more parameters of the petrophysical clustering, wherein the one or more parameters include a number and/or type of considered logs among the one or more logs and/or a clustering method. Also performed is a classification of the clusters into core depositional facies using one or more predetermined rules.

Machine-learning for sedimentary facies prediction

Irreducible water saturation of fluid-storing porous reservoir rock is determined using methods that include obtaining a reservoir rock sample from the underground fluid reservoir; performing mercury saturation measurements on the reservoir rock sample for different mercury injection pressure values to obtain mercury saturation values for the different mercury injection pressure values; and estimating the irreducible water saturation (Sw) from the mercury saturation values and the mercury injection pressure values by correcting for surface films of fluid retained on pore walls of the reservoir rock.

Method for estimating irreducible water saturation from mercury injection capillary pressure

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Rio de Janeiro, Brazil

Nadege Bize-Forest