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Journal articles on the topic 'Rock image'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Otiede, David, and Ke Jian Wu. "The Effect of Image Resolution on the Geometry and Topological Characteristics of 3-D Reconstructed Images of Reservoir Rock Samples." International Journal of Engineering Research in Africa 6 (November 2011): 37–44. http://dx.doi.org/10.4028/www.scientific.net/jera.6.37.

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The effect of image resolution on the measured geometry and topological characteristics of network models extracted from 3-D micro-computer tomography images has been investigated. The study was conducted by extracting geologically realistic networks from images of two rock samples, imaged at different resolutions. The rock samples involved were a Castlegate Sandstone and a Carbonate-28 reservoir rock. Two-dimensional images of these rocks were obtained at a magnification of ×50. The carbonate sample was studied at two different resolutions of 0.133 microns and 1.33 microns, while the sandston

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Saxena, Nishank, Ronny Hofmann, Amie Hows, et al. "Rock compressibility from microcomputed tomography images: Controls on digital rock simulations." GEOPHYSICS 84, no. 4 (2019): WA127—WA139. http://dx.doi.org/10.1190/geo2018-0499.1.

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Rock compressibility is a major control of reservoir compaction, yet only limited core measurements are available to constrain estimates. Improved analytical and computational estimates of rock compressibility of reservoir rock can improve forecasts of reservoir production performance and the geomechanical integrity of compacting reservoirs. The fast-evolving digital rock technology can potentially overcome the need for simplification of pores (e.g., ellipsoids) to estimate rock compressibility as the computations are performed on an actual pore-scale image acquired using 3D microcomputed tomo

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Nababan, Benyamin Elilaski, Eliza Veronica Zanetta, Nahdah Novia, and Handoyo Handoyo. "ESTIMASI NILAI POROSITAS DAN PERMEABILITAS DENGAN PENDEKATAN DIGITAL ROCK PHYSICS (DRP) PADA SAMPEL BATUPASIR FORMASI NGRAYONG, CEKUNGAN JAWA TIMUR BAGIAN UTARA." Jurnal Geofisika Eksplorasi 5, no. 3 (2020): 34–44. http://dx.doi.org/10.23960/jge.v5i3.34.

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Reservoir rock permeability and porosity are physical properties of rocks that control reservoir quality. Conventionally, rock porosity and permeability values are obtained from measurements in the laboratory or through well logs. At present, calculation of porosity and permeability can be calculated using digital image processing / Digital Rock Physics (DRP). Core data samples are processed by X-ray diffraction using CT-micro-tomography scan. The result is an image model of the core sample, 2D and 3D images. The combination of theoretical processing and digital images can be obtained from the

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Tawfeeq, Yahya Jirjees, and Jalal A. Al-Sudani. "Digital Rock Samples Porosity Analysis by OTSU Thresholding Technique Using MATLAB." Iraqi Journal of Chemical and Petroleum Engineering 21, no. 3 (2020): 57–66. http://dx.doi.org/10.31699/ijcpe.2020.3.8.

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Porosity plays an essential role in petroleum engineering. It controls fluid storage in aquifers, connectivity of the pore structure control fluid flow through reservoir formations. To quantify the relationships between porosity, storage, transport and rock properties, however, the pore structure must be measured and quantitatively described. Porosity estimation of digital image utilizing image processing essential for the reservoir rock analysis since the sample 2D porosity briefly described. The regular procedure utilizes the binarization process, which uses the pixel value threshold to conv

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Li, Sijia, Zhuwen Wang, and Dan Mou. "Fractal Analysis of Volcanic Rock Image Based on Difference Box-Counting Dimension and Gray-Level Co-Occurrence Matrix: A Case Study in the Liaohe Basin, China." Fractal and Fractional 9, no. 2 (2025): 99. https://doi.org/10.3390/fractalfract9020099.

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Volcanic rocks, as a widely distributed rock type on the earth, are mostly buried deep within basins, and their internal structures possess characteristics by irregularity and self-similarity. In the study of volcanic rocks, accurately identifying the lithology of volcanic rocks is significant for reservoir description and reservoir evaluation. The accuracy of lithology identification can improve the success rate of petroleum exploration and development as well as the safety of engineering construction. In this study, we took the electron microscope images of four types of volcanic rocks in th

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Chen, Yulong, and Hongwei Zhang. "An Improved C-V Model and Application to the Coal Rock Mesocrack Images." Geofluids 2020 (July 17, 2020): 1–11. http://dx.doi.org/10.1155/2020/8852209.

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In order to accurately and comprehensively obtain information about coal rock mesocrack images, image processing technique based on partial differential equation (PDE) is introduced in order to expound on the active contour model without edges and overcome the deficiency of the C-V model. The improved C-V model is adopted in order to process mesoimages of coal rocks containing single and multiple cracks and obtain high-quality binary images of coal rock mesocracks and the effective characteristic parameters of coal rock mesostructures through quantitative processing, which will lay solid found

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Guo, Chenlu, and Zhiyuan Li. "Automatic Rock Classification Algorithm Based on Ensemble Residual Network and Merged Region Extraction." Advances in Multimedia 2022 (March 20, 2022): 1–11. http://dx.doi.org/10.1155/2022/3982892.

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Lithology identification of rocks is an important part in the field of oil and gas exploration, mineral exploration, and geological analysis. How to accomplish rock classification is a key issue for the further development of the geology industry. The current main method for classifying rock pictures containing background is to select sample points or disregard the disturbance of the background. For more accurate classification, the rock part extraction method for rock images containing boundaries is designed to eliminate the influence of background. First, the rock parts are extracted based o

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Guha, A., and K. Vinod Kumar. "Potential of thermal emissivity for mapping of greenstone rocks and associated granitoids of Hutti Maski Schist belt, Karnataka." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 423–30. http://dx.doi.org/10.5194/isprsarchives-xl-8-423-2014.

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In the present study, different temperature-emissivity separation algorithms were used to derive emissivity images based on processing of ASTER( Advanced spaceborne thermal emission and reflection radiometer) thermal bands. These emissivity images have been compared with each other in terms of geological information for mapping of major rock types in Hutti Maski schist Belt and its associated granitoids. Thermal emissivity images are analyzed conjugately with thermal radiance image, radiant temperature image and albedo image of ASTER bands to understand the potential of thermal emissivity in d

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Arindi, Cindi Claudia, Syahrun Syahrun, and Arie Toursino Hadi. "IDENTIFICATION OF DAMAGE TO ROCK ART AT THE SITE OF LA KOLUMBU CAVE, LIANGKABORI VILLAGE, LOHIA DISTRICT, MUNA REGENCY." SANGIA JOURNAL OF ARCHAEOLOGY RESEARCH 8, no. 2 (2025): 106–20. https://doi.org/10.33772/sangia.v8i2.2339.

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The Lakolumbu Cave site is one of the caves that has rock drawings. The site is in Liangkabori Village, Lohia District, Muna Regency, Southeast Sulawesi Province. This study aims to determine the image motifs and factors that cause damage to rock images at the Lakolumbu Cave Site. Then the methods used in this study were data collection, data recording and data processing using ImageJ software to lift images clearer and using CorelDraw X7 Software to reproduce rock images. Based on the results of the research conducted, the Lakolumbu Cave Site has 8 panels with a total of 60 rock images that h

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Schneider, Marc H., Patrick Tabeling, Fadhel Rezgui, Martin G. Lüling, and Aurelien Daynes. "Novel microscopic imager instrument for rock and fluid imaging." GEOPHYSICS 74, no. 6 (2009): E251—E262. http://dx.doi.org/10.1190/1.3261801.

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Core analysis from reservoir rock plays an important role in oil and gas exploration as it can provide a large number of rock properties. Some of these rock properties can be extracted by image analysis of microscopic rock images in the visible light range. Such properties include the size, shape, and distribution of pores and grains, or more generally the texture, mineral distribution, and so on. A novel laboratory instrument and method allows for easy and reliable core imaging. This method is applicable even when the core sample is in poor shape. The capabilities of this technique can be ver

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Yosi, Klementin Fairyo. "GAMBAR CADAS PRASEJARAH DI TELUK WONDAMA SEBARAN DAN CERITA RAKYATNYA." Jurnal Penelitian Arkeologi Papua dan Papua Barat 12, no. 2 (2021): 97–113. http://dx.doi.org/10.24832/papua.v12i2.233.

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ABSTRAKKeberadaan gambar cadas di Teluk Wondama ditulis oleh Galis tahun 1948. Balai Arkeologi Papua tahun 2016 di Pulau Roon. Hasilnya bersifat eksplorasi, belum terfokus pada tipologi gambar cadas. Tahun 2019 Balai Arkeologi Papua melakukan penelitian Tipologi gambar cadas prasejarah di kawasan Teluk Wondama. Selain mengkaji tipologi gambar cadas, juga mengungkap cerita rakyatnya. Tujuan penulisan adalah mengetahui tipologi gambar cadas, seperti apa sebarannya dan apa saja cerita rakyat terkait gambar cadas. Metode penelitian eksploratif dan deskriptif kualitatif. Tahapan penelitian adalah s

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Ma, Mingshuo, Zhiming Gui, and Zhenji Gao. "Research on a High-Performance Rock Image Classification Method." Electronics 12, no. 23 (2023): 4805. http://dx.doi.org/10.3390/electronics12234805.

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Efficient and convenient rock image classification methods are important for geological research. They help in identifying and categorizing rocks based on their physical and chemical properties, which can provide insights into their geological history, origin, and potential uses in various applications. The classification and identification of rocks often rely on experienced and knowledgeable professionals and are less efficient. Fine-grained rock image classification is a challenging task because of the inherent subtle differences between highly confusing categories, which require a large num

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Rahmawati, Nengsi, Abdul Alim, and Ainussalbi Al Ikhsan. "IDENTIFICATION OF ROCK ART AT THE MAKAMPILO ROCK SHELTER IN LIANGKABORI VILLAGE, LOHIA DISTRICT, MUNA REGENCY." SANGIA JOURNAL OF ARCHAEOLOGY RESEARCH 8, no. 1 (2024): 20–33. https://doi.org/10.33772/sangia.v8i1.2355.

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The Makampilo Ceruk site is one of the niches that has rock art. The site is in Liangkabori Village, Lohia District, Muna Regency, Southeast Sulawesi Province. This site has never had any research discussing rock art. So the author is interested in taking the title on the site.This research aims to find out and identify image motifs and variations in the form of rock images at the Ceruk Makampilo Site. Then, the method used in this research is data collection, data recording and data processing using ImagJ software to make the images clearer.Based on the results of research conducted, the Ceru

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Zhang, Qiang, Jieying Gu, and Junming Liu. "Research on Coal and Rock Type Recognition Based on Mechanical Vision." Shock and Vibration 2021 (March 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/6617717.

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In order to identify different kinds of coal, rock, and gangue, the FPV integrated image transmission camera is used to collect images of 6 types of coal, 8 types of rocks, and 2 types of coal gangue, and the images are processed based on the two-dimensional discrete wavelet transform (2D-DWT) based on the steerable pyramid decomposition (SPD). The maximum likelihood estimation method is used to estimate the parameters, and, the coal and rock types are judged by comparing the similarity of each image. The results show the following: (1) in the eight kinds of rocks, the recognition accuracy of

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Wang, Cong, Zian Zhang, Yongqiang Zhang, Rui Tian, and Mingli Ding. "GMSRI: A Texture-Based Martian Surface Rock Image Dataset." Sensors 21, no. 16 (2021): 5410. http://dx.doi.org/10.3390/s21165410.

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CNN-based Martian rock image processing has attracted much attention in Mars missions lately, since it can help planetary rover autonomously recognize and collect high value science targets. However, due to the difficulty of Martian rock image acquisition, the accuracy of the processing model is affected. In this paper, we introduce a new dataset called “GMSRI” that is a mixture of real Mars images and synthetic counterparts which are generated by GAN. GMSRI aims to provide a set of Martian rock images sorted by the texture and spatial structure of rocks. This paper offers a detailed analysis

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Al Ghurabi, Aisha H., Mohamed S. Jouini, and Fawaz Hjouj. "Image Segmentation of 3D X-ray Micro-computed Tomography Images." Journal of Physics: Conference Series 3027, no. 1 (2025): 012056. https://doi.org/10.1088/1742-6596/3027/1/012056.

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Abstract The objective of this research is to explore the effectiveness of different deep learning models in accurately segmenting 3D X-ray Micro Computed Tomography images of carbonate rocks. Four models with different architectures and training parameters were evaluated, and the results suggest that models using a smaller patch size demonstrated superior segmentation performance, regardless of the architecture used. The models were trained and validated using cropped regions of interest extracted from the original dataset. This study emphasizes the importance of patch size selection in influ

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Sengupta, Mita, and Shannon L. Eichmann. "Computing elastic properties of organic-rich source rocks using digital images." Leading Edge 40, no. 9 (2021): 662–66. http://dx.doi.org/10.1190/tle40090662.1.

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Digital rocks are 3D image-based representations of pore-scale geometries that reside in virtual laboratories. High-resolution 3D images that capture microstructural details of the real rock are used to build a digital rock. The digital rock, which is a data-driven model, is used to simulate physical processes such as fluid flow, heat flow, electricity, and elastic deformation through basic laws of physics and numerical simulations. Unconventional reservoirs are chemically heterogeneous where the rock matrix is composed of inorganic minerals, and hydrocarbons are held in the pores of thermally

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Sidiq, Irsyad Nuruzzaman, and Thaqibul Fikri Niyartama. "Porosity Identification of Carbonate Core Reservoir Using Digital Rock Physics Method." Proceeding International Conference on Science and Engineering 1 (October 31, 2017): 175–81. http://dx.doi.org/10.14421/icse.v1.297.

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Indonesia is an archipelago country so rich with coral reefs that are a major component of the carbonate rock constituents. Where as much as 40% of carbonate rocks in Indonesia is a hydrocarbon reservoir is still rarely done exploration. This is because conventional hydrocarbon exploration technology has not been able to provide detailed information about the physical quantities. Hydrocarbon exploration technologies currently leads on digital technology to know the physical quantities of a reservoir of more detail such as porosity. Porosity which is physical quantities related to the presence

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Zou, Yongning, Gongjie Yao, and Jue Wang. "Research on 3D crack segmentation of CT images of oil rock core." PLOS ONE 16, no. 10 (2021): e0258463. http://dx.doi.org/10.1371/journal.pone.0258463.

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In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed t

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Yao, Kouame, Biswajeet Pradhan, and Mohammed Oludare Idrees. "Identification of Rocks and Their Quartz Content in Gua Musang Goldfield Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery." Journal of Sensors 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/6794095.

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Quartz is an important mineral element and the most abundant rock-forming mineral that controls the mineralogy of a reservoir. At the surface, quartz is more stable than most other rock minerals because it is made up of interlocking silica that makes it quite resistant to mechanical weathering. Quartz abundance is an indication of mineralization in many metal deposits; therefore, identification and mapping of quartz in rocks are of great value for exploration and resource potential assessments. In this study, thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflecti

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Wang, Xiufang, Jingyuan Li, Ming Bai, and Yan Pei. "Quantitative Identification Cracks of Heritage Rock Based on Digital Image Technology." Journal of Physics: Conference Series 2148, no. 1 (2022): 012048. http://dx.doi.org/10.1088/1742-6596/2148/1/012048.

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Abstract Digital image processing technologies are used to extract and evaluate the cracks of heritage rock in this paper. Firstly, the image needs to go through a series of image preprocessing operations such as graying, enhancement, filtering and binaryzation to filter out a large part of the noise. Then, in order to achieve the requirements of accurately extracting the crack area, the image is again divided into the crack area and morphological filtering. After evaluation, the obtained fracture area can provide data support for the restoration and protection of heritage rock. In this paper,

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Marathe, Ashutosh, Priya Jain, and Vibha Vyas. "Iterative improved learning algorithm for petrographic image classification accuracy enhancement." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 289. http://dx.doi.org/10.11591/ijece.v9i1.pp289-296.

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<p>Rock image classification using image processing has been practiced to assist trained geologists in decision making. However, the study of microstructures of rocks and their use in geological investigations offer challenges in the areas of Image processing and Pattern Classification due to the stochastic nature of the mineral textures that is revealed at the microscopic level. Locally relevant Igneous Rock Microstructure images were classified from Volcanic and Plutonic Rock subtypes. The imaging method used mineral grain size as the key physical feature of classification. Three algor

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Marathe, Ashutosh, Priya Jain, and Vibha Vyas. "Iterative improved learning algorithm for petrographic image classification accuracy enhancement." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 289–96. https://doi.org/10.11591/ijece.v9i1.pp289-296.

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Rock image classification using image processing has been practiced to assist trained geologists in decision making. However, the study of microstructures of rocks and their use in geological investigations offer challenges in the areas of Image processing and Pattern Classification due to the stochastic nature of the mineral textures that is revealed at the microscopic level. Locally relevant Igneous Rock Microstructure images were classified from Volcanic and Plutonic Rock subtypes. The imaging method used mineral grain size as the key physical feature of classification. Three algorithms, na

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Miquel-González, Lisset, Gilbert Ortiz-Rabell, and Olga Castro-Castiñeira. "Tomography axial computerized technique application to improve Cuban oil fields seal and reservoir rocks characterization." Boletín de Ciencias de la Tierra, no. 41 (January 1, 2017): 73–80. http://dx.doi.org/10.15446/rbct.n41.55046.

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This investigation pretend to obtain improve on seal and reservoir rocks composition studies in oil fields, more certain in the formations characterization, and to prove the necessity of analytical nuclear techniques’ incorporation to petrophysical methods’ complex used in the Cuban oil prospection. This investigation used computer axial tomography method in consolidated cores’ rock and free software Image J as tomography interpretation support, resulting in novel improvement to the petrophysical laboratory. The following results were obtained: the computer axial tomography on cores’ rock were

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Carpenter, Chris. "Machine-Learning Techniques Characterize Source-Rock Images at the Pore Scale." Journal of Petroleum Technology 74, no. 01 (2022): 92–95. http://dx.doi.org/10.2118/0122-0092-jpt.

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 208632, “Reconstruction and Synthesis of Source-Rock Images at the Pore Scale,” by Timothy Anderson, SPE, Stanford University. The paper has not been peer reviewed. Nanoimaging techniques for characterizing pore-scale structure of shales trade oﬀ between high-resolution/high-contrast sample-destructive imaging modalities and low-contrast/low-resolution sample-preserving modalities. Acquisition of nanoscale images also is often time-consuming and expensive. In the complete paper, the author introduc

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Kuang, Hong Hai. "Pattern Recognition of Carbonate Rocks in Rs Image." Key Engineering Materials 500 (January 2012): 37–39. http://dx.doi.org/10.4028/www.scientific.net/kem.500.37.

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Pattern recognition of carbonate rocks in RS image have been studied in the paper. Samples of carbonate rocks were scanned into rock images.By analysing these samples of carbonate rocks,a new arithmetic was chosed and a standard curve of carbonate rocks by the arithmetic can be gotten.Rs images were divided into grids.There are curves by the arithmetic in grids. The standard curve of carbonate rocks and curves in grids were compared.If both of curves look very similar,the grid is carbonate rocks area.

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Yang, Liying. "Core Image Lithology Identification." International Journal of Computer Science and Information Technology 2, no. 1 (2024): 522–33. http://dx.doi.org/10.62051/ijcsit.v2n1.55.

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Core is a part of subsurface rock formations, and rock classification can be achieved by analyzing lithological characteristics such as color, texture, or shape. This is an essential step in oil and gas exploration. In the field of geology, core image analysis is a method for studying the micro-features of rocks, utilizing color and texture characteristics from core images for lithology identification. This paper establishes three models: one utilizing color moments for neural network training, another using gray-level co-occurrence matrix for neural network training, and a third employing a f

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Yang, Liying. "Core Image Lithology Identification." International Journal of Computer Science and Information Technology 2, no. 2 (2024): 172–83. https://doi.org/10.62051/ijcsit.v2n2.20.

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Core is a part of subsurface rock formations, and rock classification can be achieved by analyzing lithological characteristics such as color, texture, or shape. This is an essential step in oil and gas exploration. In the field of geology, core image analysis is a method for studying the micro-features of rocks, utilizing color and texture characteristics from core images for lithology identification. This paper establishes three models: one utilizing color moments for neural network training, another using gray-level co-occurrence matrix for neural network training, and a third employing a f

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Wei, Xin Shan, Chun Long Rong, Jun Xiang Nan, Guo Jian Cheng, and Ye Liu. "Rock Classification Based on Image Processing and Neural Networks." Applied Mechanics and Materials 568-570 (June 2014): 685–90. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.685.

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For the identification complexity of rock microstructure, based on numerical analysis of rock section images, an automatic rock texture classification method and identification system is proposed in this paper. Digital grey image processing of rock thin section is used for features extraction, the features are then as inputs to the neural network model, the model output is the rock microstructure classification. 100 pieces of rock section images from Sulige region in Changqing Oilfield are used for the experiment; the whole dataset is randomly divided into 70 images for training datasets, 15 i

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Malik, Owais A., Idrus Puasa, and Daphne Teck Ching Lai. "Segmentation for Multi-Rock Types on Digital Outcrop Photographs Using Deep Learning Techniques." Sensors 22, no. 21 (2022): 8086. http://dx.doi.org/10.3390/s22218086.

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The basic identification and classification of sedimentary rocks into sandstone and mudstone are important in the study of sedimentology and they are executed by a sedimentologist. However, such manual activity involves countless hours of observation and data collection prior to any interpretation. When such activity is conducted in the field as part of an outcrop study, the sedimentologist is likely to be exposed to challenging conditions such as the weather and their accessibility to the outcrops. This study uses high-resolution photographs which are acquired from a sedimentological study to

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Li, Diyuan, Junjie Zhao, and Jinyin Ma. "Experimental Studies on Rock Thin-Section Image Classification by Deep Learning-Based Approaches." Mathematics 10, no. 13 (2022): 2317. http://dx.doi.org/10.3390/math10132317.

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Experimental studies were carried out to analyze the impact of optimizers and learning rate on the performance of deep learning-based algorithms for rock thin-section image classification. A total of 2634 rock thin-section images including three rock types—metamorphic, sedimentary, and volcanic rocks—were acquired from an online open-source science data bank. Four CNNs using three different optimizer algorithms (Adam, SGD, RMSprop) under two learning-rate decay schedules (lambda and cosine decay modes) were trained and validated. Then, a systematic comparison was conducted based on the perform

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Anderson, Timothy I., Kelly M. Guan, Bolivia Vega, Saman A. Aryana, and Anthony R. Kovscek. "RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models." Energies 13, no. 24 (2020): 6571. http://dx.doi.org/10.3390/en13246571.

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Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models have shown success, existing methods for generating 3D volumes from 2D training images are restricted to binary images and grayscale volume generation requires 3D training data. Shale characterization relies on 2D imaging techniques such as scanning electron microscopy (SEM), and grayscale value

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Wadge, G., and N. Quarmby. "Geological remote sensing of rocky coasts." Geological Magazine 125, no. 5 (1988): 495–505. http://dx.doi.org/10.1017/s0016756800013236.

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AbstractFrom remotely sensed images of rock surfaces at coasts it is possible to map some characteristics of different rock types. To do this a selection must be made of those parts of the image that correspond to the rock surfaces prior to interrogation of their geological information content. A comparative study of satellite-acquired multispectral Thematic Mapper data and aircraft-acquired multispectral scanner data at four test sites on the Pembrokeshire coast was made. The spatial resolution of the Thematic Mapper data (30 m) proved to be too coarse to provide any continuity of mapping ove

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Bénard, Antoine, Sabine Palle, Luc Serge Doucet, and Dmitri A. Ionov. "Three-Dimensional Imaging of Sulfides in Silicate Rocks at Submicron Resolution with Multiphoton Microscopy." Microscopy and Microanalysis 17, no. 6 (2011): 937–43. http://dx.doi.org/10.1017/s1431927611011883.

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AbstractWe report the first application of multiphoton microscopy (MPM) to generate three-dimensional (3D) images of natural minerals (micron-sized sulfides) in thick (∼120 μm) rock sections. First, reflection mode (RM) using confocal laser scanning microscopy (CLSM), combined with differential interference contrast (DIC), was tested on polished sections. Second, two-photon fluorescence (TPF) and second harmonic signal (SHG) images were generated using a femtosecond-laser on the same rock section without impregnation by a fluorescent dye. CSLM results show that the silicate matrix is revealed

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Bahodir, B. Tuychibaev. "THE ROLE OF DIGITAL TECHNOLOGIES IN PETROGLYPH DOCUMENTATION." Look to the past 1, SI 2 (2022): 5. https://doi.org/10.5281/zenodo.7219787.

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Due to the fact that rock paintings are located in open areas, due to natural and anthropogenic factors, the problem of their preservation is considered an important and urgent task. The article examines the issues of preservation and documentation of rock paintings, especially in recording petroglyphs, using a method that does not damage their outer surface, i.e. does not affect it by hand. The most effective method of recording color images is the pigment card method, that is, the image obtained by graphic processing of the photo image is considered. The possibilities of graphic processing o

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Gonçalves, Laercio B., and Fabiana R. Leta. "Macroscopic Rock Texture Image Classification Using a Hierarchical Neuro-Fuzzy Class Method." Mathematical Problems in Engineering 2010 (2010): 1–23. http://dx.doi.org/10.1155/2010/163635.

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We used a Hierarchical Neuro-Fuzzy Class Method based on binary space partitioning (NFHB-Class Method) for macroscopic rock texture classification. The relevance of this study is in helping Geologists in the diagnosis and planning of oil reservoir exploration. The proposed method is capable of generating its own decision structure, with automatic extraction of fuzzy rules. These rules are linguistically interpretable, thus explaining the obtained data structure. The presented image classification for macroscopic rocks is based on texture descriptors, such as spatial variation coefficient, Hurs

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Zhang, Yong Jun, Li Qian An, and Nian Jie Ma. "Study on Infrared Characteristics in the Progressive Failure of Bolted Rocks under Uniaxial Compression." Advanced Materials Research 332-334 (September 2011): 1227–31. http://dx.doi.org/10.4028/www.scientific.net/amr.332-334.1227.

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For the demands of thermal infrared (TIR) radiation change regularity for TIR radiation detection experiments of interaction between bolt and rock, TIR image information extracting and quantitative analysis of bolts action zones were carried out. The IR isothermal fringes of the bolted bocks were obtained through thermal infrared image subtraction of bolted bocks and data fitting. The interaction ranges between bolts and rock were obtained and the bolted ranges of lateral directions were determined. The quantitative treatment methods were applied to analyze infrared images of bolted roadway al

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Gonzalez, Andres, Zoya Heidari, and Oliver Lopez. "Data-Driven Algorithms for Image-Based Rock Classification and Formation Evaluation in Formations With Rapid Spatial Variation in Rock Fabric." Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description 64, no. 2 (2023): 154–73. http://dx.doi.org/10.30632/pjv64n2-2023a2.

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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. Alternatively, unsupervised learning algorithms, which do not require labeled data, can be employed. Using either of these methods depends on the evaluated formations and the available training/input data sets. Therefore, further investigation is needed to compare the performance of both approaches. The objectives of this paper are (a) to train two supervised learning models for image-based rock classification employ

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Mohamed, Mohamed Taha AlMakki, Latifa Shaheen Al-Naimi, Tochukwu Innocent Mgbeojedo, and Chidiebere Charles Agoha. "Geological mapping and mineral prospectivity using remote sensing and GIS in parts of Hamissana, Northeast Sudan." Journal of Petroleum Exploration and Production Technology 11, no. 3 (2021): 1123–38. http://dx.doi.org/10.1007/s13202-021-01115-3.

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AbstractIn recent years, various geological activities and different mineral prospecting and exploration programs have been intensified along the Red Sea hills in order to elucidate the geological maps and to evaluate the mineral potentials. This study is therefore aimed at testing the viability of using remote sensing and geographic information system (GIS) techniques for geological mapping and prospecting for gold mineralization in the area. The study area is located in northeast Sudan and covers an area of about 1379 km2. Different digital image processing techniques were applied to Landsat

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Handoyo, Handoyo, Fatkhan Fatkhan, Fourier D. E. Latief, and Harnanti Y. Putri. "Estimation of Rock Physical Parameters Based on Digital Rock Physics Image, Case Study: Blok Cepu Oil Field, Central Java, Indonesia." Jurnal Geofisika 16, no. 1 (2018): 21. http://dx.doi.org/10.36435/jgf.v16i1.53.

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Modern technique to estimate of the physical properties of rocks can be done by means of digital imagingand numerical simulation, an approach known as digital rock physics (DRP: Digital Rock Physics). Digital rockphysics modeling is useful to understand microstructural parameters of rocks (pores and rock matrks), quite quickly and in detail. In this paper a study was conducted on sandstone reservoir samples in a rock formation. The core of sandstone samples were calculated porosity, permeability, and elasticity parameters in the laboratory. Then performed digital image processing using CT-Scan

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Tan, Yunliang, Dongmei Huang, and Ze Zhang. "Rock Mechanical Property Influenced by Inhomogeneity." Advances in Materials Science and Engineering 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/418729.

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In order to identify the microstructure inhomogeneity influence on rock mechanical property, SEM scanning test and fractal dimension estimation were adopted. The investigations showed that the self-similarity of rock microstructure markedly changes with the scanned microscale. Different rocks behave in different fractal dimension variation patterns with the scanned magnification, so it is conditional to adopt fractal dimension to describe rock material. Grey diabase and black diabase have high suitability; red sandstone has low suitability. The suitability of fractal-dimension-describing metho

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Peng, Rui Dong, Yan Cong Yang, Peng Wang, and Yu Jun Zhang. "Developments in Detection of Rock Damage." Applied Mechanics and Materials 152-154 (January 2012): 1018–23. http://dx.doi.org/10.4028/www.scientific.net/amm.152-154.1018.

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How to quantificationally detect the damage of rocks is a key problem in damage mechanics for rocks, and it determined whether the damage theory of rocks could be brought into action in rock engineering. Detection techniques of rock damage were summarized and grouped into structural analysis approaches and feature measurement approaches, which include SEM analysis, CT detection, stress-strain measurement, wave detection, acoustic emission monitoring, infrared radiation detection, etc. Image processing and fractal theory were introduced to calculate damage variable directly based on images. All

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Popescu, Sorin, and Ovidiu-Bogdan Tomuş. "Determination of the rock mass resistance index (GSI) based on image processing." MATEC Web of Conferences 342 (2021): 02012. http://dx.doi.org/10.1051/matecconf/202134202012.

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More and more often, and on an increasingly large scale, the geological resistance index (GSI) system is used for the design and practice of the mining process. The GSI, is a unique system for classifying the mass of rocks, linked to the parameters of rock strength and mass distortion, based on the generalized criteria of Hoek-Brown and MohrCoulomb. The GSI can be estimated using standard and in situ tables by direct surface observations in underground or surface mining. The GSI value provides a numerical representation of the overall Geotechnical quality of the rock mass. The method for deter

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Puskareva, D. A. "The effectiveness of granulometric composition image analysis in rock thin sections for the study of terrigenous reservoir rocks." Actual Problems of Oil and Gas 15, no. 1 (2024): 21–36. http://dx.doi.org/10.29222/ipng.2078-5712.2024-15-1.art2.

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Background. Image analysis of the granulometric composition in rock thin sections is an effective method that complements petrographic and sedimentation analyzes of reservoir rocks. However, due to imperfect research results and the specifics of rock structure, the application method has a number of limitations. Objective. The article shows the effectiveness of using image analysis for several groups of terrigenous rocks that differ in structural and mineral parameters. Materials and methods. The study was carried out using an optical microscope with the KERN S7 petrographic research analyzer.

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Tian, Pengzhi, and Meibao Yao. "RSU-Net: An Attention U-Net for Martian Rock Segmentation." Journal of Physics: Conference Series 2762, no. 1 (2024): 012001. http://dx.doi.org/10.1088/1742-6596/2762/1/012001.

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Abstract Since rocks may collide with the rover or wear tires during the exploration mission of the Mars probe, and may contain rich geological information, identifying rocks in the scene is crucial for the navigation and obstacle avoidance of the Mars probe. Additionally, since the communication between the Mars rover and the earth is often intermittent and delayed during missions, it needs a certain degree of autonomy. Deep learning technologies such as semantic segmentation and target detection can meet this requirement to a certain extent, which facilitates the enhancement of safety and ef

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Callender, C. A., Wm C. Dawson, and J. J. Funk. "Correlation of Pore Structure and Permeability by SEM-Image Analysis." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 1 (1990): 428–29. http://dx.doi.org/10.1017/s0424820100180896.

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The geometric structure of pore space in some carbonate rocks can be correlated with petrophysical measurements by quantitatively analyzing binaries generated from SEM images. Reservoirs with similar porosities can have markedly different permeabilities. Image analysis identifies which characteristics of a rock are responsible for the permeability differences. Imaging data can explain unusual fluid flow patterns which, in turn, can improve production simulation models.Analytical SchemeOur sample suite consists of 30 Middle East carbonates having porosities ranging from 21 to 28% and permeabili

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Wei, Xin Shan, Xiao Hua Qin, Chun Long Rong, Jun Xiang Nan, and Guo Jian Cheng. "Image Classification Recognition for Rock Micro-Thin Section Based on Probabilistic Neural Networks." Applied Mechanics and Materials 602-605 (August 2014): 2147–52. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2147.

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In order to implement the recognition automation of rock section pore images, a method combined K-means clustering with probabilistic neural network is proposed and applied to rock thin section images. Firstly, K-means clustering is used as segmentation algorithm, the rock images are divided into two types and extracted enough features and it is shown good classification recognition effect on testing dataset. Secondly, 100 pieces of rock image section are used as validation dataset, including 20 groups, each group has 5 images and 200 data samplings. Experiments show that the probabilistic neu

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Abdullah, Rafea A., Maysaa A. Abdulhameed, Maher J. Ismail, and Ahmed Saadoon. "Integrated the Core Analysis Data, Image logs, and Conventional Logs to Understand the Reservoir Rock Type of the Mauddud Formation." Journal of Petroleum Research and Studies 13, no. 4 (2023): 1–15. http://dx.doi.org/10.52716/jprs.v13i4.756.

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Inner ramp carbonates with dolomitic limestone make up the Late Albian Mauddud reservoir in Arabian plate. The age of the Mauddud Formation is Albian–Early Cenomanian, and it overlies the Nahr-Umr Formation and the Ahmadi Formation. The depositional environments range from subtidal to lagoon and shoal environments. The main goal of this study is to integrate all the available information to recognize different rock types within Mauddud reservoir. Due to the limited core available in Mauddud reservoir, the rock types have been identified mainly based on the Full-bore formation micro imager tool

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Junning, Xie, Liu Bolong, and Zeng Nianchang. "Study on the breaking process of jointed rock mass by disc cutters based on digital image correlation and infrared thermography." E3S Web of Conferences 233 (2021): 03006. http://dx.doi.org/10.1051/e3sconf/202123303006.

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Jointed rock masses are frequently encountered during the TBM excavation. To investigate the rock breakage mechanism of jointed rock mass by disc cutter and precursory information before rock failure, a series of indentation tests were performed on shear rheological test system. During the test, breaking process of specimens were recorded by digital image correlation system and thermal infrared imager simultaneously. Therefore, the strain fields and thermal infrared images of jointed rock mass by disc cutters were obtain. The experimental results show that the failure process of jointed rock m

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Liu, Jinzi, Wenying Du, Chong Zhou, and Zhiqing Qin. "Rock Image Intelligent Classification and Recognition Based on Resnet-50 Model." Journal of Physics: Conference Series 2076, no. 1 (2021): 012011. http://dx.doi.org/10.1088/1742-6596/2076/1/012011.

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Abstract Machine learning algorithms becomes popular for intelligent classification of rock images. In this paper, it selects Resnet 50 neural network model to divide the data sets based on the rock pictures taken under the white light lamp. By continuously adjusting the parameters of each layer, the intelligent classification of rocks is carries out. The training final validates accuracy reached 94.12%.

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