MS-CGAN:融合条件生成对抗网络和多尺度时空特征进行岩性识别

IF 2.2 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Journal of Applied Geophysics Pub Date : 2024-10-04 DOI:10.1016/j.jappgeo.2024.105531
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引用次数: 0

摘要

岩性识别是地层评价和储层特征描述中的一项重要工作。然而,由于小样本测井数据分布不均造成的困难,传统岩性识别模型需要提高精度。由于测井参数与岩性之间存在着错综复杂的非线性联系,再加上油田环境的独特性,因此将领域专业知识与数据驱动模型有效结合起来预测岩性至关重要。本文提出了一种多尺度条件生成对抗网络(MS-CGAN)方法,该方法将条件生成对抗网络与多尺度时空特征相结合,解决了数据不平衡问题,提高了岩性分类的准确性。我们的方法在来自美国 Hugoton 和 Panoma 油田以及中国大庆生产井的两个小型数据集上进行了测试,与其他模型相比,我们的方法是最佳选择。综合评估结果表明,新模型在利用有限数据加强岩性识别方面具有良好的实际应用前景和潜在效益。
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MS-CGAN: Fusion of conditional generative adversarial networks and multi-scale spatio-temporal features for lithology identification
Lithology identification constitutes a crucial undertaking in formation evaluation and reservoir characterization. However, the need for improved precision arises in conventional lithology identification models due to the difficulties presented by unequal distributions of small-sample logging data. An effective combination of domain expertise and data-driven models to predict lithology is essential due to the intricate and nonlinear connection between logging parameters and lithology, combined with the distinct characteristics of the oilfield environments. In this paper, we proposed a multi-scale conditional generative adversarial network(MS-CGAN) method, which combines conditional generative adversarial networks with multi-scale spatio-temporal features to address data imbalance issues and enhance the accuracy of lithology classification. Our approach, tested on two small datasets from the Hugoton and Panoma fields, USA, and the Daqing production wells, China, stands out as the optimal choice compared to other models. Comprehensive evaluation results indicate promising practical applications and potential benefits of the new model in enhancing lithology identification using limited data.
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来源期刊
Journal of Applied Geophysics
Journal of Applied Geophysics 地学-地球科学综合
CiteScore
3.60
自引率
10.00%
发文量
274
审稿时长
4 months
期刊介绍: The Journal of Applied Geophysics with its key objective of responding to pertinent and timely needs, places particular emphasis on methodological developments and innovative applications of geophysical techniques for addressing environmental, engineering, and hydrological problems. Related topical research in exploration geophysics and in soil and rock physics is also covered by the Journal of Applied Geophysics.
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