梯度和无梯度优化器在过渡式液压断层扫描中的性能.
Syam Chintala1, B V N P Kambhammettu1, T S Harmya1,2
1Department of Civil Engineering, Indian Institute of Technology Hyderabad, Hyderabad, Telangana, India.
Ground water
|August 21, 2023
概括
过渡式液压断层扫描 (THT) 有效地描述了破裂的含水层. 排除低质量的数据显著提高了THT模型的性能,基于梯度的优化显示了稍微更好的验证结果.
科学领域:
- 水文地质学 水文地质学
- 地质物理学 地质物理学
- 环境科学 环境科学
背景情况:
- 由于对比的矩阵和断裂特性,破裂含水层的地下表征是复杂的.
- 过渡式液压断层扫描 (THT) 是一种可靠的技术,用于估计这种环境中的液压和储存性能.
- THT性能受到数据质量和反向使用的优化方法的影响.
研究的目的:
- 评估梯度和无梯度优化器在THT逆转中对破裂含水层的性能.
- 评估数据质量,特别是信号与噪声比 (SNR) 对THT逆转结果的影响.
- 为了比较Levenberg-Marquardt (LM) 和Nelder-Mead (NM) 的优化算法的有效性.
主要方法:
- 实验室实验是在一个具有已知的断裂模式的二维花岩块上进行的.
- 进行了穿孔试验,并监测了各个港口的 drawdown 响应.
- 使用与LM (梯度) 和NM (无梯度) 方法相结合的模拟优化模型逆转数据集,优先考虑高SNR数据 (SNR>100).
主要成果:
- 无论LM和NM算法都成功地在液压导电性 (K) 和存储 (S) 断层图像中识别了优选流路 (断层网络).
- 与Nelder-Mead (NM) 优化器相比,Levenberg-Marquardt (LM) 优化器在验证过程中显示出略高的性能.
- 排除低质量的数据集 (SNR ≤100) 显著提高了整体模型性能.
结论:
- 优化方法的选择对破裂含水层中THT模型预测的影响很小.
- 排除低质量的数据对于提高THT表征的准确性和可靠性至关重要.
- 当THT与适当的数据处理和优化相结合时,它是了解复杂的断层含水层系统的宝贵工具.
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