- journal_title：Geophysics
- Contributor：Haoping Huang
- Publisher：Society of Exploration Geophysicists
- Date：2005-
- Format：text/html
- Language：en
- Identifier：10.1190/1.2122412
- journal_abbrev：Geophysics
- issn：0016-8033
- volume：70
- issue：6
- firstpage：G135
- section：ELECTRICAL AND ELECTROMAGNETIC METHODS
The depth of investigation in electromagnetic (EM) soundings is a maximum depth at which a given target in a given host can be detected by a given sensor. It is of primary interest in EM exploration, particularly for small EM sensors having negligible separation between the transmitter and receiver coils. The depth of investigation is related to many factors, such as sensor sensitivity, precision, operating frequencies, ambient noise level, target and host properties, and the techniques used in data processing and interpretation. Quantitative understanding of the relationships between the depth of investigation and these factors will help users meet their geologic objectives, avoid unnecessary survey expenses, and display meaningful geologic features.
Simple equations to estimate the depth of investigation for handheld EM sensors have been derived from analyzing the EM response based on layered half-space models. The results show that the depth of investigation is approximately proportional to the square root of the skin depth in the host for a given detection threshold and conductivity contrast between the target and host. For a given skin depth, the depth of investigation increases with the target conductivity and conductivity contrast and decreases with the detection threshold. Choosing a threshold mainly depends on the S/N ratio of the EM data if the sensor setup, data acquisition methods, and processing techniques are well established. A high threshold such as 20% or 30% is recommended for resistive targets or in areas where environmental noise is high or where terrain conductivity is low (<50 mS/m). In contrast, a threshold as low as 5% or 10% can be used for conductive targets in quiet areas. Field examples are presented to illustrate how to use the depth of investigation in data interpretation and presentation.