Lithofacies classification

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August undefined, 2024

WebObject Moved This document may be found here Web2 mrt. 2024 · In order to clarify the characteristics of fine-grained sedimentary lithofacies and the depositional models in lacustrine environments of the Chang 7 Member of the Upper Triassic Yanchang Formation in the Ordos Basin, we focus on the lacustrine lithofacies classification and controlling factors. Based on the typical field sections of the southern …

Robust Unilateral Alignment for Subsurface Lithofacies …

Web27 aug. 2024 · Summary Classification of different lithofacies and petrotypes is one of the main objectives of modern quantitative seismic interpretation. In this study, we present preliminary results of the … Expand. 20. PDF. Save. Alert. Investigation of the random forest framework for classification of hyperspectral data. Web18 aug. 2024 · A Lithofacies Unit is classified on the basis of the lithology of the rocks and this lithology is not just a surface property but extends to depth in the same way as for any other Lithologic Unit. -- JohnLaxton - 09 Aug 2005 Lithofacies unit should probably change name to 'Surface Materials' unit. scratch社区平台

Effect of Lamination on Shale Reservoir Properties: Case

WebClassification and well-log identification of lithofacies of continental shale oil reservoirs in Chang 7-3 submember of the Triassic Yanchang Formation in the Longdong area of the Ordos Basin, China Quantifying amplitude-variation-with-offset uncertainties related to calcite-cemented beds using a Monte Carlo simulation Web16 jul. 2024 · Lithofacies are a discrete variable that describes categories of the rock quality, defined as having two or more states. Lithofacies represent small- to intermediate-scale heterogeneities in... Web14 dec. 2024 · Hence, karst geomorphology was reconstructed and classified using the topographical framework of paleokarst disconformities. This can be used to analyse the relationship between palaeogeomorphology and reservoirs, and associate specific palaeogeomorphological units with potential hydrocarbon reservoirs, thereby effectively … scratch社区推荐

The Implementation of Machine Learning in Lithofacies Classification ...

Lithofacies classification integrating conventional approaches an…

WebThe boosting machine learning ML workflow developed efficiently provides accurate lithofacies classification with reduced uncertainty in carbonate lithofacies determinations. The entire... scratch社区有哪些Web1 apr. 2024 · The lithofacies classification is the first step to figure out the heterogeneity of the reservoir properties. However, these four lithofacies are still not fully … scratch社区网址

"Web14 apr. 2005 · The electrofacies-based classification involves identifying clusters in the well-log response that reflect "similar" minerals and lithofacies within the logged interval. This statistical procedure is straightforward and inexpensive. However, identification of lithofacies and HFUs relies on core-data analysis and can be expensive and time … " - Lithofacies classification

Lithofacies classification

WebIn the classification based on the spectral facies, the trained multilayer neural network model showed high prediction accuracy for all the lithofacies. Based on these observations, it is confirmed that more precise lithofacies interpretation and classification can be conducted with the developed methods. Web7 mrt. 2024 · This paper focuses on the application of semi-supervised classification in lithofacies identification. Semi-supervised classification methods are divided into …

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Web1 apr. 2024 · Four lithofacies types were defined and discussed Lithofacies 1: organic-matter-rich mudstone Lithofacies 1 is an organic-matter-rich, rarely bioturbated, dark … Web1 apr. 2024 · Lithofacies classification is a process to identify rock lithology by indirect measurements. Usually, the classification is processed manually by an experienced geoscientist.

Web1 mrt. 2002 · The advantage of PDF over MLDA is that it will easily reveal types of lithofacies other than those in the training data and/or detect erroneous log measurements. In general, this study shows that a relatively simple statistical technique as MLDA is effective for classification of well log data into distinct lithofacies with characteristic physical … Web12 jan. 2024 · 结果表明：常规测井资料识别出的页岩岩相与ECS特殊测井资料识别结果一致，匹配程度较高。. 整体而言，当TOC质量分数≥ 2%时，涪陵气田五峰组—龙马溪组页岩硅质成分来源以生物成因为主；当TOC质量分数 < 2%时，硅质成分来源以陆源碎屑为主。. 涪陵 …

WebDr. Aqsa Anees has obtained her Ph.D. degree (2014-2024) in Petroleum Engineering from the School of Earth Resources, China University of Geosciences (CUG) (Wuhan), China. In 2024, CUG is ranked as the 7th best university globally for studying geosciences. She has recently completed postdoc at the Yunnan University, China (Dec, 2024- Dec 2024). Web4 jan. 2024 · As well as enhancing lithofacies classification more generally using well-log variables, these GR attributes can be used to forecast facies in real time based on logging-while-drilling data. The application is demonstrated with simple formula using synthetic GR logs featuring common clastic lithofacies and their transitions.

Web16 mrt. 2024 · Lithofacies is one of the most important reservoir parameters, which could provide a qualitative description for hydrocarbon and geothermal reservoirs. …

Web6 mrt. 2024 · Interpretation of the environment in which lithofacies were deposited from analysis of cored sequences involves relating the identified lithofacies to the physical and biological processes that produced them. This process-response relationship identifies the specific processes responsible for the sequence and, by inference, the depositional ... scratch社区Web22 sep. 2024 · Integrating Component Analysis & Classification Techniques for Comparative Prediction of Continuous & Discrete Lithofacies Distributions Offshore Technology Conference May 4, 2015 scratch编程下载2.0Web1 jan. 2024 · 1. Introduction. As an important reservoir parameter, lithofacies could provide a qualitative description of subsurface reservoirs, which may indicate the rock physical behaviors as well as the compartmentation degree (Bosch et al., 2002; Garland et al., 2012).Researchers have classified lithofacies based on different input data, such as in … scratch社区网站Web28 jan. 2024 · (S4): Lithofacies Classification Based on MNN. To improve the practicality of the SF interpretation results, an automated lithofacies classification model was developed based on the MNN. This MNN model can generate a nonlinear classifier to model the complicated statistical characteristics between the explanatory and response … scratch算法视频Web13 jun. 2024 · The well log interpretations that were considered for lithofacies classification and permeability modeling are neutron porosity, shale volume, and water … scratch算法题目Web3 feb. 2024 · Abstract: As a qualitative process, classification of subsurface lithofacies is very important for the characterization of hydrocarbon reservoirs. Machine learning has been a potential method to automate the prediction of this parameter based on the well-logging data. In order to incorporate the geological trend into the classification process, a … scratch算法设计Web22 okt. 2014 · Bottom: Lithofacies classification result centered at í µí±¡ = 1377ms. Blue curves are the boundary of Forestburg Limestone from structural interpretation. scratch编程入门