Unconventional rocks elastic properties profile and geomechanical characterization

Hussain, Maaruf; Amao, Abduljamiu O.; Muqtadir, Arqam; Al‐Ramadan, Khalid; Babalola, Lamidi

doi:10.1016/j.marpetgeo.2020.104670

Cited by 4 publications

(2 citation statements)

References 33 publications

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“…The geomechanical properties obtained with an impulse hammer provide the elastic relaxation of the material and the reduced Young's modulus (E*). The latter has been proven to be a reliable proxy to unconstrained and tri-axial derived elastic properties (REPs) 4,8 For the qualitative and quantitative analysis of the data, we leveraged several machine learning and visualization techniques, including high-dimensional interactive plots (HiPlot), K-Means, t-distributed stochastic neighbor embedding (tSNE), support vector machines (SVM), XGBoost, and deep neural networks (DNN). The choice of algorithm depends on the target variable.…”

Section: Methodsmentioning

confidence: 99%

AI inference of multiphysics properties using hyperspectral data

San Roman Alerigi,

Li,

Sepulveda

et al. 2023

Optical Technology and Measurement for Industrial Applications Conference

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We investigate using machine learning techniques to infer various physical properties of rocks from hyperspectral imaging data. In particular, we demonstrate that deep neural networks (DNN) can infer mechanical and geochemical properties based on high-resolution Fourier transform spectrograms. Our goal is to enable real-time petrophysical analysis of subsurface rocks and fluids. The ongoing work encompasses the development of sensors and algorithms that facilitate nondestructive, fast, and high-resolution mapping of petrophysical properties. We acquired high-resolution mappings of mechanical, chemical, and electromagnetic properties at sub-millimeter scale (> 100 um) using a scanning system fitted with multiphysics probes, including impulse hammer geomechanical probe designed to measure the rebound hardness and the reduced Young modulus; Fourier transform spectrometer (FTIR) to acquire the diffuse reflectance; acoustic transducers to measure unconstrained sonic velocities; and near-surface gas permeability. We have characterized over two hundred thousand samples across various lithologies, including limestone, sandstones, and shales from outcrops and cores from unidentified wells. We present the results of machine-learning models and algorithms that predict, based on the IR reflectance data, the rock types, and the unconstrained geomechanical properties. The method could be extended to characterize other solids from subsurface, terrestrial, or non-terrestrial environments. The combination of photonic measurements and machine learning provides the means to find non-causal relations between materials' electromagnetic/photonic response and their other physical properties under various stress states and environmental configurations. This work presents the foundational blocks to achieve this objective and develop optical sensors for sustainable energy extraction.

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Section: Methodsmentioning

confidence: 99%

AI inference of multiphysics properties using hyperspectral data

San Roman Alerigi,

Li,

Sepulveda

et al. 2023

Optical Technology and Measurement for Industrial Applications Conference

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“…Makoond (2020) proporciono una expresión empírica para estimar el módulo de elasticidad estático de los componentes de la mampostería de ladrillo a partir de su contraparte dinámica (Makoond et al, 2020) . estudiaron las relaciones entre Young módulo (estático (Es) y dinámico (Ed)) generado a partir de la prueba triaxial y su forma reducida (E *) derivada de la medición del martillo de impulso (Hussain et al, 2020). En este trabajo de investigación, se estudiaron canteras de roca de la región Morelia, Michoacán, México (Figura 1).…”

Section: Introductionunclassified

Memorias del X Congreso Nacional de Alconpat México 2022

Borges¹,

Guzmán²,

López³

2023

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Alconpat México fue creada en abril del año 2002. Fue la primera delegación de Alconpat Internacional. Desde aquella época, y en cada año par, se ha llevado a cabo el Congreso Nacional de Alconpat México, que de cariño es llamado el Pre-Conpat. Desde aquel entonces, numerosas delegaciones nacionales se han creado año con año. En esta ocasión el comité organizador quizo hacer una celebración académica por los primeros 20 años. Esto implicó darle al congreso una imagen mística que incluye la presentación de una obra alusiva del famoso pintor Guido Farina y que engalana este libro de memorias. La obra consiste en una mano que evoca el mando de las diferentes directivas bajo la tutela del consejo fundador ilustrado con los nombres de las personas de éste en la forma de un halo. La mano sostiene una brújula que indica el camino de nuestra asociación, donde se encuentra el logo de Alconpat México y un Katun maya que representa el número 20, alusivo al 20 aniversario. Estamos muy contentos de compartir contigo ésta celebración académica.

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