Halliburton Energy Services, Inc.

Radompon Sungkorn

Jonas Toelke

Yaoming Mu

Naum Derzhi

Abraham S Grader

Carl Sisk

Ahmed Elsayed Fouda

William Brian Atkins

Avrami Grader

Gustavo Carpio

Sadeed Sayed

Anyela Morcote

Gabriela Alexandra Davalos

Sneha Bhakta

Michael Stephen Pierce

A method comprising identifying a cutter on a drill bit based on a drill bit image, assigning a grading value of the cutter based on a classification model of a machine learning system, wherein the classification model is generated based on a set of training cutter images associated with drill bit characteristics indicators, determining a surface parameter based on a surface of the cutter, generating a comparison value based on the surface parameter, and mapping a set of cutter information to the cutter on the drill bit, wherein the set of cutter information comprises the grading value and the comparison value.

Cutter analysis and mapping

A method and system may include disposing an electromagnetic (EM) logging tool in a wellbore. The EM logging tool may include a transmitter disposed on the EM logging tool and a receiver disposed on the EM logging tool. The method may further include transmitting an electromagnetic field from the transmitter into one or more, measuring the eddy current in the one or more tubulars with the receiver, and forming an EM log from the plurality of measurements. Additionally, the method may include identifying a representative signature of a collar from the EM log, locating a plurality of signatures that are similar to the representative signature, iteratively locating a collar signature based at least in part on the representative signature, the plurality of signatures that are similar to the representative signature, and a joint length; and displaying a depth for each of the one or more collars.

Locating collars on well casings

Systems and methods for determining properties of subterranean formations surrounding a wellbore are provided. An example method can include receiving an image of a formation sample; partitioning the image into a plurality of patches; detecting, via a semantic extraction processor, textures captured in the plurality of patches; associating the textures to a location of the image of the formation sample; reducing a dimension of representation of the textures to obtain one or more vectors, the one or more vectors being based on the textures; and providing a plurality of curves based on the one or more vectors.

Method and system to analyze geologic formation properties

An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes iteratively analyzing property measurements collected throughout the digital images using different subsample sizes to identify a property distribution convergence as a function of subsample size. The method also includes selecting a smallest subsample size associated with the property distribution convergence as a representative elementary area or volume for the rock sample.

Representative elementary volume determination via clustering-based statistics

An example method includes acquiring two-dimensional (2D) or three-dimensional (3D) digital images of a rock sample. The method also includes selecting a subsample within the digital images. The method also includes deriving a trend or petrophysical property for the subsample. The method also includes applying the trend or petrophysical property to a larger-scale portion of the digital images.

Digital rock physics-based trend determination and usage for upscaling

A method for determining fabric and upscaled properties of a geological sample, such as a rock sample. A system for the method also is provided.

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Houston, TX, United States of America

Radompon Sungkorn