Towed transient electromagnetic survey for groundwater investigation - challenges and solutions.

Allen, David A.

doi:10.1071/aseg2012ab043

Cited by 1 publication

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TEM has a preponderance in groundwater investigation and geophysical mapping (Sapia et al., 2014). Allen and Anonymous (2012) introduced a towed TEM system and showed its application and future in groundwater exploration, while Auken et al. (2018) demonstrated the TEM application in large‐scale groundwater investigation using Pulled Array TEM and the High Moment TEM systems.…”

Section: Introductionmentioning

confidence: 99%

Bayesian inversion and uncertainty analysis of transient electromagnetic data

Zhang,

Sun,

Liu

et al. 2024

Near Surface Geophysics

View full text Add to dashboard Cite

Quantification of non‐uniqueness and uncertainty is important for transient electromagnetism (TEM). To address this issue, we develop a trans‐dimensional Bayesian inversion schema for TEM data interpretation. The trans‐dimensional posterior probability density (PPD) offers a solution to model selection and quantifies parameter uncertainty resulting from the model selection from all possible models rather than determining a single model. We use the reversible‐jump Markov chain Monte Carlo sampler to draw ensembles of models to approximate PPD. In addition to providing reasonable model selection, we address the reliability of the inversion results for uncertainty analysis. This strategy offers reasonable guidance when interpreting the inversion results. We make the following improvements in this paper. First, in terms of algorithmic acceleration, we use the nonlinear optimization inversion results as the initial model and implement the multi‐chain parallel method. Second, we develop double factors to control the sampling step size of the proposed distribution, so that the sampling models cover the high‐probability region of the parameter space as much as possible. Finally, we provide the potential scale reduction factor‐η convergence criteria to assess the convergence of the samples and ensure the rationality of the output models. The proposed methodology is first tested on synthetic data and subsequently applied to a field dataset. The TEM inversion results show that probability inversion can provide reliable references for data interpretation through uncertainty analysis.

show abstract

Section: Introductionmentioning

confidence: 99%