RockDNet: Deep Learning Approach for Lithology Classification

MAM Abdullah, AA Mohammed, SR Awad - Applied Sciences, 2024 - mdpi.com
Analyzing rock and underground layers is known as drill core lithology. The extracted core
sample helps not only in exploring the core properties but also reveals the lithology of the …

DRAG: A novel method for automatic geological boundary recognition in shale strata using multi-well log curves

T Zhou, Q Zhu, H Zhu, Q Zhao, Z Shi, S Zhao, C Zhang… - Processes, 2023 - mdpi.com
Ascertaining the positions of geological boundaries serves as a cornerstone in the
characterization of shale reservoirs. Existing methods heavily rely on labor-intensive manual …

Lithology classification of whole core CT scans using convolutional neural networks

K Chawshin, CF Berg, D Varagnolo, O Lopez - SN Applied Sciences, 2021 - Springer
X-ray computerized tomography (CT) images as digital representations of whole cores can
provide valuable information on the composition and internal structure of cores extracted …

Automated Rock Classification Using High-Resolution CT-Scan Images and Core Photos in a Siliciclastic Formation Used for CO2 Storage

A Gonzalez, Z Heidari, O Lopez - SPE Annual Technical Conference …, 2022 - onepetro.org
Carbon capture and storage (CCS) is an attractive alternative to reduce the concentration of
greenhouse gases in the atmosphere with the objective of preventing further increases in …

Machine learning for multiple petrophysical properties regression based on core images and well logs in a heterogenous reservoir

T Lin, M Mezghani, C Xu, W Li - SPE Annual Technical Conference …, 2021 - onepetro.org
Reservoir characterization requires accurate prediction of multiple petrophysical properties
such as bulk density (or acoustic impedance), porosity, and permeability. However, it …

Data-Driven Algorithms for Image-Based Rock Classification and Formation Evaluation in Formations With Rapid Spatial Variation in Rock Fabric

A Gonzalez, Z Heidari, O Lopez - Petrophysics, 2023 - onepetro.org
Supervised learning algorithms can be employed for the automation of time-intensive tasks,
such as image-based rock classification. However, labeled data are not always available …

Semi-Automated Rock Classification for Permeability Estimation Using High-Resolution Computed Tomography Scan Images, Core Photos, and Well Logs

A Gonzalez, P Sahu, Z Heidari, O Lopez - SPE Journal, 2024 - onepetro.org
Reliable estimation of petrophysical properties can be challenging, especially in geological
formations with rapid variation in the spatial distribution of rock components. The spatial …

High resolution petrophysics and geomechanics workflow—one key to optimal development of unconventional reservoirs

P Gaillot - … Resources Technology Conference, 20–22 July 2020, 2020 - library.seg.org
This paper presents a log-based workflow that provides the cm-scale vertical resolution well
framework capable of capturing the level of heterogeneity often present in mudstones. The …

A contrario dip picking for borehole imaging

J Costes, G Facciolo, R Grompone von Gioi… - Geophysics, 2021 - library.seg.org
We have described an algorithm to perform automatic dip picking on borehole images. One
key element of our method is a statistical validation, based on the a contrario theory, which is …

Electrical, Diffusional, Hydraulic, and Geometrical Tortuosity Anisotropy Quantification Using 3D Computed Tomography Scan Image Data

A Gonzalez, Z Heidari, O Lopez - SPE Reservoir Evaluation & …, 2023 - onepetro.org
Sedimentary rocks display complex spatial distribution of both pore space and solid
components, impacting the directional dependence of physical phenomena such as …