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oil shale thailand machine
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Production Capacity Prediction Method of Shale Oil Based on Machine …
1.. IntroductionThe prediction and evaluation of horizontal well production capacity is the key to the rational and effective development of shale oil reservoirs [1, 2].Shale reservoirs have poor physical properties and complex pore and throat structures, and the economic benefits of conventional straight well development are poor, and the multi-stage …
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AI & Machine Learning: The Next Transformation for Oil …
Technologies to locate and extract oil and gas reserves enabled the shale revolution, and a new revolution is around the corner for oil and gas exploration and production companies. While it might sound like something from science fiction, artificial intelligence (AI) and machine learning have the potential to reshape the oil and gas ...
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Assessment of potential unconventional lacustrine shale-oil and shale
Using a geology-based assessment methodology, the U.S. Geological Survey assessed potential technically recoverable mean resources of 53 million barrels of shale oil and 320 billion cubic feet of shale gas in the Phitsanulok Basin, onshore Thailand....
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A Multi-Scale Approach for Assessing Shale Oil Accessibility: …
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Machine Learning Assisted State-of-the-Art-of Petrographic
In the E&P industry, accurate lithology classification is an essential task for successful exploration and production. Geophysical logs provide high-resolution …
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A Multiscale Approach for Assessing Shale Oil Availability
Finally, combining the results of the above two scales, machine learning is used to predict shale oil availability across the entire core. On the core scale, the watershed and maximum ball methods are used to extract the core pore network model, and it is found that square pores occupy the highest proportion among the three pore …
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Technically Recoverable Shale Oil and Shale Gas …
When considering the market implications of abundant shale resources, it is important to distinguish between a technically recoverable resource, which is the focus of this …
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Shale oil production prediction and fracturing optimization …
In this paper, we propose a computational framework for shale oil production prediction and fracturing parameters optimization that couples machine learning and particle swarm optimization (PSO). Firstly, we construct a deep neural network (DNN) model database with 841 numerical simulation data as training set and validation set, and 87 field ...
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Characterization for Possible Utilization of Mae Sot Basin, Thailand …
Request PDF | Characterization for Possible Utilization of Mae Sot Basin, Thailand Oil Shale | This is a petrologic and stratigraphic project that analyzed and evaluated the Mae Sot Basin oil ...
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Oil Shale
Oil shale is a type of sedimentary rock that is rich in kerogen. Kerogen is a part of rock that breaks down and releases hydrocarbons when heated. Hydrocarbons are substances made entirely of hydrogen and carbon. Petroleum and natural gas are probably the most familiar . hydrocarbons.The hydrocarbons in oil shale can be used as an …
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Sustainability | Free Full-Text | An Analytic Hierarchy Process …
The great demand for oil shale resource development and the corresponding threats to the environment have resulted in the urgent need to assess the impact of oil shale in situ mining on the environment. In this paper, based on an analysis method developed by the previous literature and the Delphi technique, three secondary …
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AAPG Datapages/Archives: Oil Shale Sedimentology and …
The intermontane Mae Sot basin, Thailand, contains carbonate-rich oil shales in which oil yield, mineralogy, and major and trace element geochemistry are related to the rock type. Higher grade oil shale is significantly enriched in silicate minerals (quartz, feldspars, clays, and analcite) relative to carbonates, and in dolomite relative to ...
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Application of Machine Learning for Shale Oil and Gas …
With the continuous improvement of shale oil and gas recovery technologies and achievements, a large amount of geological information and data have been accumulated for the description of shale reservoirs, and it has become possible to use machine learning methods for "sweet spots" prediction in shale oil and gas areas. …
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Reservoir Fluid Data Acquisition Using Advanced Mud …
Oil production from shale reservoirs has increased dramatically in recent years. To identify drilling targets and optimize well completions, it is important to get …
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Oil Shale | U.S. Geological Survey
The USGS Energy Resources Program has studied oil shale resources of the United States, with a significant effort on the Eocene Green River Formation of Colorado, Utah, and Wyoming. This formation contains the largest oil shale deposits in the world. Oil shale, despite the name, does not actually contain oil, but is a precursor of oil …
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Understanding the Controlling Factors for CO2
Carbon capture and sequestration is the process of capturing carbon dioxide (CO2) from refineries, industrial facilities, and major point sources such as power plants and storing the CO2 in subsurface formations. Carbon capture and sequestration has the potential to generate an industry comparable to, if not greater than, the existing oil and …
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Productivity control on oil shale formation—Mae Sot Basin, Thailand
Semantic Scholar extracted view of "Productivity control on oil shale formation—Mae Sot Basin, Thailand" by J. Curiale et al. Skip to search form Skip to main content Skip to account menu. Semantic Scholar's Logo. Search 220,351,483 papers from all fields of …
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Ecological Restoration and Transformation of …
With the combination of field research, literature collection, and tracking survey, the oil shale open-pit exploitation and management process in Maoming, Guangdong, China, has been investigated, and its …
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A systematic review of CO2 injection for enhanced oil …
Introduction. Shale oil and gas, as a new unconventional energy that can gradually replace traditional fossil fuels, has attracted extensive attention [1].Shale reservoirs in America are mostly marine sedimentary, with 21% of the world's shale oil resources [2, 3].According to the data from the Energy Information Administration (EIA), …
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Production Optimization Using Machine Learning in Bakken Shale
Researchers from both industry and academia have studied the tight oil resources intensively in the past decade since the successfully development of Bakken Shale and Eagle Ford Shale and made tremendous progress. It has been recognized that locating the sweet spots in the regionally pervasive plays is of utter significance. …
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Application of machine learning in predicting oil rate …
In a similar study, the authors employed data-driven modeling for predicting the rate decline of Eagle Ford Shale oil wells 8. Another study proposed an ANN-based model for predicting the rate decline of Eagle ford Shale oil wells 9. The primary drawback of these studies was that their applicability was restricted only to Eagle for shale oil wells.
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ECI Group Pyrolysis Systems
The machine is used to reconstitute large volumes of used engine oils for resale to customers from the transport industry. ECI Thailand commenced commercial operation of its first release "next generation" state-of-the-art …
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Shale oil production prediction and fracturing optimization …
DOI: 10.1016/j.petrol.2022.110900 Corpus ID: 251236565; Shale oil production prediction and fracturing optimization based on machine learning @article{Lu2022ShaleOP, title={Shale oil production prediction and fracturing optimization based on machine learning}, author={Chunhua Lu and Hanqiao Jiang and Jinlong Yang and Zhiqiang …
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Thailand Oil and Gas Research
Thailand Oil and Gas Research. 17 comprehensive market analysis studies and industry reports on the Oil and Gas sector, offering an industry overview with historical data …
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Oil Shale Deposits | Maps, Geology & Resources
Oil shale is a rock that contains significant amounts of organic material in the form of kerogen. Up to 1/3 of the rock can be solid organic material. Liquid and gaseous hydrocarbons can be extracted from the oil shale, but the rock must be heated and/or treated with solvents.
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The oil shale deposits of Thailand
The oil shale deposits of Thailand A. K. Chakrabarti. A. K. Chakrabarti Search for other works by this author on: GSW. Google Scholar. Author and Article Information A. K. Chakrabarti Publisher: Society of Economic Geologists First Online: 02 Mar 2017. Online ISSN: 1554-0774. Print ISSN: 0361-0128 ...
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X-ray tomography imaging of shale microstructures: A …
On a regional basis, shale oil and gas reserves in the United Arab Emirates are estimated at 22.6 billion barrels of oil and 5.8 trillion m 3 of gas (EIA, 2013). From, ... Artificial neural networks and support vector machines can be used efficiently for this method. Pattern recognition algorithms can be used as well.
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Machine learning-based fracturing parameter optimization …
Machine learning-based fracturing parameter optimization ...
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Machine learning-based estimated ultimate recovery …
Lacustrine shale is characterized by rapid lithofacies transformation and compositional heterogeneity, which present challenges in shale oil sweet spot evaluation and distribution prediction and ...
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PETROLEUM POTENTIAL, THERMAL MATURITY AND THE OIL WINDOW OF OIL …
Oil shales and coals occur in Cenozoic rift basins in central and northern Thailand. Thermally immature outcrops of these rocks may constitute analogues for source rocks which have generated oil in several of these rift basins. A total of 56 oil shale and coal samples were collected from eight different basins and analysed in detail in this study.
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A New Approach for Multi-Fractured Horizontal Wells
Abstract. The continental shale oil reservoirs usually have strong heterogeneity, which make the law of fracture propagation extremely complex, and the quantitative characterization of fracture network swept volume brings great challenges. In this paper, firstly, the grey correlation analysis method is used to calculate the …
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Chemofacies characterization of lacustrine shale based on machine …
1. Introduction. With its burgeoning global prominence, shale oil has established itself as a pivotal unconventional energy reservoir, a status well recognized within the Chinese energy paradigm due to its substantial domestic reserves (Zou et al., 2013).The strategic and economic implications of exploring and harnessing shale oil within China are profound …
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Three Ways Greater Digitalization in Shale Oil Plays
As shale-oil operators adopt manufacturing models and mindsets to lower the costs of completions and production, they are deploying more and more digital technologies in diverse applications, many of which Siemens pioneered years ago. This paper offers a wide range of examples of how digitalization can drive more efficiency, visibili ty, and
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Oil shale | Definition, Composition, Extraction, …
The various oil shale deposits that have been mined around the world since the early 20th century have ranged from shale to marlstone to carbonate mudstone.All are relatively fine-grained sedimentary rocks, as …
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Shale oil production prediction and fracturing optimization …
In this paper, we propose a computational framework for shale oil production prediction and fracturing parameters optimization that couples machine learning and particle swarm optimization (PSO). Firstly, we construct a deep neural network (DNN) model database with 841 numerical simulation data as training set and validation set, …
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Application of machine learning in predicting oil rate …
The study's novelty comes from developing an innovative machine learning (ML) (random forest (RF)) based model for fast rate-decline and EUR prediction in Bakken Shale oil wells.
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