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Interpretation-A Journal of Subsurface Characterization最新文献

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Evaluation Model of Shale Adsorbed Gas Considering Clay and Water Saturation 考虑粘土和含水饱和度的页岩吸附气评价模型
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-10 DOI: 10.1190/int-2022-0066.1
Kun Liu, Jing Lu, Song Hu, Z. Nan
Shale adsorption capacity is affected by many factors including temperature, pressure, geochemical characteristics of organic matter, clay, and water saturation. The traditional calculation model of adsorbed gas content only considers the influence of temperature, pressure, and organic geochemical characteristics. The influence of clay and water saturation on adsorption capacity is seldom considered. Isotherm adsorption experiments were conducted on synthetic specimens and natural specimens with varying clay types, clay contents, and water saturations. Then, the influences of clay and water saturation on the adsorption capacity were systematically studied. The experimental results found that the order of clay adsorption capacities was smectite > kaolinite > chlorite > illite. The multicomponent superposition rule was applicable in evaluating shale-adsorbed gas content. The total adsorption capacity was equal to the accumulation of the adsorption capacities of all types of clay and organic matter. Moisture will significantly reduce the adsorption capacity of shale. The adsorption capacities of synthetic specimens and natural specimens after being fully saturated with water were 9%–14% and 42%–61% of those in dry states, respectively. Then, a new shale-adsorbed gas evaluation model was established based on the Langmuir equation considering clay and water saturation. The calculation error of this new model was approximately 11%, which provides a new method for evaluating the adsorbed gas content of shale.
页岩的吸附能力受温度、压力、有机质地球化学特征、粘土和含水饱和度等因素的影响。传统的吸附气体含量计算模型只考虑温度、压力和有机地球化学特征的影响。很少考虑粘土和水饱和度对吸附容量的影响。在不同粘土类型、粘土含量和含水饱和度的合成试样和天然试样上进行了等温吸附实验。然后,系统地研究了粘土和含水饱和度对吸附容量的影响。实验结果表明,粘土吸附能力的大小顺序为蒙脱石>高岭石>绿泥石>伊利石。多组分叠加规则适用于评价页岩吸附气含量。总吸附容量等于所有类型的粘土和有机物的吸附容量的累积。湿气会显著降低页岩的吸附能力。合成试样和天然试样在完全饱和后的吸附能力分别为干燥状态下的9%–14%和42%–61%。然后,基于考虑粘土和水饱和度的Langmuir方程,建立了一个新的页岩吸附气评价模型。该模型的计算误差约为11%,为评价页岩吸附气含量提供了一种新的方法。
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引用次数: 0
A deep learning framework for seismic facies classification 地震相分类的深度学习框架
4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-06 DOI: 10.1190/int-2022-0048.1
Harpreet Kaur, Nam Pham, Sergey Fomel, Zhicheng Geng, Luke Decker, Ben Gremillion, Michael Jervis, Raymond Abma, Shuang Gao
We have proposed a deep neural network-based framework for seismic facies classification. We implement two different neural networks based on the architectures of DeepLabv3+ and generative adversarial network for segmentation and compare the mapping results from seismic reflection data to lithologic facies. DeepLabv3+ predictions have sharper boundaries between the predicted facies whereas generative adversarial network output has a better continuity of predicted facies. We incorporate uncertainty analysis into the workflow using a Bayesian framework. The proposed approach consisting of joint analysis of predicted facies from multiple networks along with uncertainty in prediction accelerates the interpretation process by reducing the need for human intervention and also lessens individual biases that an interpreter may bring. We determine the effectiveness of the proposed algorithm by testing on field data examples, and we find that the proposed workflow classifies facies accurately. This may potentially enable the development of depositional environment maps in areas of low well density.
我们提出了一种基于深度神经网络的地震相分类框架。我们基于DeepLabv3+和生成对抗网络的架构实现了两种不同的神经网络进行分割,并比较了地震反射数据与岩性相的映射结果。DeepLabv3+预测在预测相之间具有更清晰的边界,而生成对抗网络输出具有更好的预测相连续性。我们使用贝叶斯框架将不确定性分析合并到工作流中。提出的方法包括对来自多个网络的预测相进行联合分析,同时考虑预测中的不确定性,通过减少人工干预的需要,加速了解释过程,也减少了解释器可能带来的个人偏见。通过对现场数据实例的测试,我们确定了所提出算法的有效性,我们发现所提出的工作流能够准确地分类相。这可能使低井密度地区的沉积环境图的开发成为可能。
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引用次数: 2
Küresel Yapıda Grafitik Karbon Sentezi ve Karakterizasyonu
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.69035
Fadime Ateş, Elif Tahtasakal, Selin Şahin Sevgili
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引用次数: 0
Eşit oranlarda Zn, Cd ve Cu kullanılarak oluşturulan ZnCuO ve CdCuO ikili oksit komposit ince filmlerin optiksel karakterizasyonu
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.68498
Sitki Aktaş
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引用次数: 0
Yapay Sinir Ağları Yöntemleri Kullanılarak PVP İçeren Nanoliflerin Çaplarının Tahmini 利用人工神经网络方法预测含 PVP 纳米纤维的直径
4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.70520
İsmail Yıldız, SÜLEYMAN KARABULUT
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引用次数: 0
Uçucu Kül ve Borojipsin Yapı Malzemesi Olarak Değerlendirilmesi
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.67304
A. Evcin, Fazıl İlhan
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引用次数: 0
Prediction of irradiation phenomena induced by electron beams interaction with solid targets 电子束与固体靶相互作用诱导辐照现象的预测
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.71252
R. Labbani, Kerkatou Madjida
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引用次数: 0
Karıştırmalı Döküm Yöntemi ile Üretilen Atık Alüminyum Matrisli Kompozit Malzemelerde Al2O3 Nano Partikül Takviye Oranının Mekanik Özelliklere Etkisinin İncelenmesi
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.68413
Mehmet Di̇ri̇lmi̇ş, Muhammed Göksoy
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引用次数: 0
Gadolinyum Katkılı Silan Bazlı Nanolif Yüzeylerin Karakterizasyonu
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.69398
Ozan Ceylan, N.Çiçek Bezir
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引用次数: 0
Düşük derişimli öncü çözeltilerle hazırlanan CdX (X=Se, S) ince filmlerinin temel optiksel parametrelerinin belirlenmesi
IF 1.2 4区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS Pub Date : 2023-01-01 DOI: 10.29228/jchar.68499
Fati̇h Ünal
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引用次数: 0
期刊
Interpretation-A Journal of Subsurface Characterization
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