规则化集体卡尔曼反转用于强大和高效的重力数据建模以识别矿物和矿石矿床
Dharma Arung Laby1, S Sungkono2, Arkoprovo Biswas3
1Department of Geophysical Engineering, Faculty of Civil, Planning, and Geoengineering, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia. dharma.arunglaby@its.ac.id.
Scientific reports
|November 27, 2025
概括
这项研究引入了一个规范集成卡尔曼逆转 (EKI) 方法用于地球物理勘探. 这种方法可以从重力数据中改进矿物和矿石体的建模,提供稳定和高效的不确定性量化.
科学领域:
- 地质物理学 地质物理学
- 地质物理勘探地质物理勘探
- 反向问题 逆向问题
背景情况:
- 从重力异常中对矿物和矿石体进行建模是具有挑战性的,因为反向问题的性质不好,特别是有噪音或稀疏的数据.
- 现有的反转方法通常需要广泛的参数调整,并且可以产生不稳定的解决方案.
研究的目的:
- 提出一个规范的整体卡尔曼逆转 (EKI) 框架,以提高地质物理勘探中的数值稳定性和不确定性量化.
- 改进从重力异常中对矿物和矿石体的建模.
主要方法:
- 开发了一种规范化的集体卡尔曼逆转 (EKI) 框架,其中包含提霍诺夫规范化.
- 利用集体统计来有效量化不确定性.
- 执行受控的数值实验,并与元启发算法 (PSO,VFSA,BA) 进行基准测试.
主要成果:
- 规范化的EKI框架显示了数值稳定性的提高和对集体退化的敏感性降低.
- 收稳定性和模型分辨率之间的最佳平衡是通过比[公式:参见文本]大的一组大小和适度规则化实现的.
- 与已建立的元启发算法相比,更高的计算效率和稳定的融合.
- 对于合成和真实重力数据 (染色体,Pb-Zn,硫化物,Cu-Au沉积物) 获得稳定和地质一致的结果.
结论:
- 规范化的EKI框架是矿产勘探的一个强大而有效的工具.
- 这种方法有效地减轻了采矿风险,并支持了战略决策.
- 该方法提供了稳定的,在地质上一致的模型,通过先前的解释和钻探数据来验证.
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