Borehole Electromagnetic Induction

Basic Concept

Electromagnetic Induction (EMI) borehole logging is a wireline geophysical technique used to delineate variations in bulk electrical conductivity of the earth materials adjacent to a borehole. Unlike borehole resistivity and similar direct current (DC) methods, EMI logging does not require electrical contact with formations via a conductive borehole mud or fluid. Because of the non-invasive principles of electromagnetic induction, EMI logging can be conducted in boreholes with nearly all types of construction, except those with steel casing.

Electrical conductivity (and its inverse, resistivity) is influenced by lithology, minerology, porosity, permeability, saturation, and concentration of dissolved ions within the groundwater. EMI logs measure the bulk (i.e., formation plus fluid) apparent conductivity ( σ_a ) and are used to identify relative changes in rock type or pore-fluid electrical properties. EMI logging collects depth-dependent measurements of apparent conductivity, which, by using various loops sizes within the tool, can be sampled at different distances away from the borehole.

Theory

The simplest EMI-logging tool induces electrical current within the formations and measures returning signals using multi-turn wire coil with an axis parallel to the borehole. Signals are transmitted using a power supply that delivers an alternating current (AC) to a downhole-transmitter coil. The alternating current within the transmitter coil generates a time-varying magnetic field that penetrates the borehole-adjacent materials. According to Faraday’s Law, this primary magnetic field induces an electromotive force (emf) within nearby conductors.

The emf generates electrical-eddy currents in conductive layers that produce a secondary magnetic field in the formation that varies similarly to the primary field. Using similar mechanisms, the secondary field induces the flow of alternating current within the receiver coil within the tool. The potential difference (i.e., voltage) across the receiver coil is measured and is proportional to the conductivity of the formation from which it was generated.

The single-EMI tool, which contains one transmitter- and receiver coil, collect conductivity measurements at a single distance from the borehole center (i.e., radius of investigation (ROI)). Single-EMI measurements include all material (i.e., borehole fluid and invaded formation) within the ROI and, thus, differ from the true values of bulk-formation conductivity. However, inter-coil spacing effects the vertical resolution and ROI of EMI measurements, and it can be manipulated to resolve thinner layers and focus measurements past the disturbed zone.

The normal-EMI and dual-EMI tools are focused tools that are designed to investigate the native formations with higher resolutions. The normal-EMI tool contains an additional receiver coil that is wound opposite the primary-receiver coil and positioned nearer to the transmitter coil. The normal-EMI measurement sums the signals from both receivers. Because the additional receiver is oppositely wound, the signal produced by materials within its corresponding radius of investigation is eliminated (Collier, 1993).

The dual-induction tool collects apparent electrical conductivity data at two different radii of investigation, which are commonly referred to as “medium” and “deep”. Typically, the deep induction components utilizes six coils (i.e., three transmitters and three receivers), and the medium induction component uses fewer. The dual-EMI tool is designed to maximize vertical resolution and ROI, while minimizes the effects of the disturbed borehole zone. Generally, dual-induction tools are the most commonly used EMI-logging tool

Applications

Electromagnetic fields are subject to attenuation and a subsequent decrease in radius of investigation. This skin effect (i.e., reduction in magnitude and change in phase of returning signal) is due to interference of current ground loops and distance traveled through conductors. Typically, it increases with transmitter-receiver inter-coil spacing. However, this phenomenon is predictable, only becomes significant when true formation resistivity (ρ_t ) is less than one, and can be automatically corrected during logging (Collier, 1993).

Additionally, accurate apparent conductivity measurements require a full-tool response (i.e., the tool’s measurement zone is within one formation). Thus, though thin conductive beds can be identified, their actual conductivity value may not be resolved because of the averaging of over- and/or underlying resistive layers. As such, EMI logging is well suited for determining true formation conductivity in highly conductive zones, but highly resistive formations might be better quantified with normal-borehole resistivity (Mussett and Khan, 2000).

Under ideal conditions, however, EMI logging can image the vertical extent of permeable beds and indicate saturation. Additionally, EMI logs can be used to monitor apparent conductivity over time for saltwater-encroachment investigations (Prinos and Valderrama, 2016) or contamination studies. However, formation boundaries are most accurately picked when combining EMI data with other logs. Williams and others (1993), for example, used EMI logging with gamma logging to distinguish between high-conductivity zones caused by lithology and those from landfill-impacted fluids.

For investigations where accurate measurements are needed, it is critical to allow the tool to achieve thermal equilibrium and to calibrate the response to a calibration ring. Regardless, EMI logging is a reliable technique that provide accurate bulk conductivity values of the formations surrounding a borehole. Because it is the only electrical-borehole tool able to collect data in nonmetallic, air-filled holes, EMI logging is the most widely used and has aided the following:

Surface resistivity surveys (i.e., comparison or inversion constraints)
Groundwater models
Delineation of aquifers/aquitards
Contamination monitoring
Conductive plume mapping
Monitoring saltwater inundation
Assessing remediation efforts
Evaluation of mud invasion
Relative differentiation of lithology
Determination of variations in saturation
Formation evaluation in hydrocarbon exploration

Examples/Case studies

Acworth, R.I. and Dasey, G.R., 2003, Mapping of the hyporheic zone around a tidal creek using a combination of borehole logging, borehole electrical tomography and cross-creek electrical imaging, New South Wales, Australia: Hydrogeology Journal, v. 11, p. 368-377, doi:10.1007/s10040-003-0258-4.

Abstract: A combination of electrical imaging carried out across a tidal creek and borehole electrical tomography between strings of electrodes installed in bores adjacent to the creek is used to establish the shape of the hyporheic zone beneath a tidal creek in a sand aquifer. The interpretations provided by the data inversions are checked against fluid electrical conductivity (EC) samples collected from bundled piezometers installed in the creek banks and from bulk EC measurements made using induction logs in bores on the creek banks. Extensive seepage into the base of the creek is identified from the electrical image and verified by independent measurements of hydraulic head and fluid EC. The Effective Medium Theory is used to derive values of fluid EC from bulk resistivity measurements obtained from the inversion process. The data show an extensive zone of mixing between seawater and rainwater recharge into the aquifer, with the shape of the hyporheic zone strongly influenced by regional groundwater discharge and the presence of a thin layer of cemented sands at a depth of 10 m. The combined interpretation demonstrates the importance of borehole control in the interpretation of electrical images measured from the surface over complex EC distributions.

Liang, L., Abubaker, A., and Habashy, T.M., 2011, Estimating petrophysical parameters and average mud-filtrate invasion rates using joint inversion of induction logging and pressure transient data: Geophysics, v. 76, no. 2, p. 1MA-Z43I, doi:10.1190/1.3541963.

Abstract: We introduce an inversion approach for determining the water-based mud-filtrate invasion profile, as well as the formation porosity and horizontal permeability, from the induction logging data. The inversion is constrained by a multiphase fluid flow simulator that simulates the mud-filtrate invasion process to obtain the spatial distributions of the water saturation and the salt concentration, which are in turn transformed into the formation resistivity using a resistivity-saturation formula. By ignoring the diffusion effect, we assume that the mud-filtrate invasion process is mainly convective so that it can be equivalently simulated by providing an average invasion rate and the duration of invasion. The average invasion rate can be directly inverted from the fluid-flow-constrained inversion of induction logging data. We also obtain the mud-filtrate invasion profile, which is consistent with the fluid flow physics. The reconstructed mud-filtrate invasion profile benefits the interpretation of the formation test. When the pressure transient data are available, this approach can be also used to jointly invert both induction logging data and pressure transient data to obtain the mud-filtrate invasion profile, as well as a parametric distribution of the TI-anisotropic formation permeability and porosity. Assuming a vertical well penetrating horizontal formations, the fluid flow problem is solved using an implicit black oil finite-difference simulator with brine tracking option based on a cylindrical, axially symmetric grid, whereas the response of the induction logging tool is simulated using a frequency-domain finite-difference solver based on a Cartesian grid. A Gauss-Newton inversion scheme using the multiplicative regularization technique is used for either the fluid-flow-constrained inversion or the joint inversion. The reliability of the inversion results depends on the accuracy of a priori knowledge of the reservoir, which needs to be confirmed via sensitivity analysis.

Metzger, L.F. and Izbicki, J.A., 2012, Electromagnetic‐Induction Logging to Monitor Changing Chloride Concentrations: Groundwater, v. 51, no. 1, p. 108-121, doi:10.1111/j.1745-6584.2012.00944.x.

Abstract: Water from the San Joaquin Delta, having chloride concentrations up to 3590 mg/L, has intruded fresh water aquifers underlying Stockton, California. Changes in chloride concentrations at depth within these aquifers were evaluated using sequential electromagnetic (EM) induction logs collected during 2004 through 2007 at seven multiple‐well sites as deep as 268 m. Sequential EM logging is useful for identifying changes in groundwater quality through polyvinyl chloride‐cased wells in intervals not screened by wells. These unscreened intervals represent more than 90% of the aquifer at the sites studied. Sequential EM logging suggested degrading groundwater quality in numerous thin intervals, typically between 1 and 7 m in thickness, especially in the northern part of the study area. Some of these intervals were unscreened by wells, and would not have been identified by traditional groundwater sample collection. Sequential logging also identified intervals with improving water quality—possibly due to groundwater management practices that have limited pumping and promoted artificial recharge. EM resistivity was correlated with chloride concentrations in sampled wells and in water from core material. Natural gamma log data were used to account for the effect of aquifer lithology on EM resistivity. Results of this study show that a sequential EM logging is useful for identifying and monitoring the movement of high‐chloride water, having lower salinities and chloride concentrations than sea water, in aquifer intervals not screened by wells, and that increases in chloride in water from wells in the area are consistent with high‐chloride water originating from the San Joaquin Delta rather than from the underlying saline aquifer.

Prinos, S.T. and Valderrama, R., 2016, Collection, Processing, and Quality Assurance of Time-Series Electromagnetic-Induction Log Datasets, 1995–2016, South Florida: U.S. Geological Survey Open-File Report 2016-1194 (pdf, 24 p.), doi:10.3133/ofr20161194.

Abstract: Time-series electromagnetic-induction log (TSEMIL) datasets are collected from polyvinyl-chloride cased or uncased monitoring wells to evaluate changes in water conductivity over time. TSEMIL datasets consist of a series of individual electromagnetic-induction logs, generally collected at a frequency of once per month or once per year that have been compiled into a dataset by eliminating small uniform offsets in bulk conductivity between logs probably caused by minor variations in calibration. These offsets are removed by selecting a depth at which no changes are apparent from year to year, and by adjusting individual logs to the median of all logs at the selected depth. Generally, the selected depths are within the freshwater saturated part of the aquifer, well below the water table. TSEMIL datasets can be used to monitor changes in water conductivity throughout the full thickness of an aquifer, without the need for long open-interval wells which have, in some instances, allowed vertical water flow within the well bore that has biased water conductivity profiles. The TSEMIL dataset compilation process enhances the ability to identify small differences between logs that were otherwise obscured by the offsets. As a result of TSEMIL dataset compilation, the root mean squared error of the linear regression between bulk conductivity of the electromagnetic induction log measurements and the chloride concentration of water samples decreased from 17.4 to 1.7 milli siemens per meter in well G–3611 and from 3.7 to 2.2 milli siemens per meter in well G–3609. The primary use of the TSEMIL datasets in south Florida is to detect temporal changes in bulk conductivity associated with saltwater intrusion in the aquifer; however, other commonly observed changes include (1) variations in bulk conductivity near the water table where water saturation of pore spaces might vary and water temperature might be more variable, and (2) dissipation of conductive water in high-porosity rock layers, which might have entered these layers during drilling. Although TSEMIL dataset processing of even a few logs improves evaluations of the differences between the logs that are related to changes in the salinity, about 16 logs are needed to estimate the bulk conductivity within ±2 milli siemens per meter. Unlike many other types of data published by the U.S. Geological Survey, the median of TSEMIL datasets should not be considered final until 16 logs are collected and the median of the dataset is stable.

Tobola, D.P. and Holditch, S.A., 1991, Determination of Reservoir Permeability From Repeated Induction Logging: Society of Petroleum Engineers Formation Evaluation, v. 6, no. 1, p. 20-26, doi:10.2118/19606-PA.

Abstract: When fresh-water mud filtrate invades a gas reservoir containing a saline connate water, a low-resistivity annulus will form and propagate into the formation. Analysis of how readings from an induction log change with time can yield reasonable estimates of formation permeability. This paper describes a method and presents field data that can be used to estimate permeability from time-lapse logging data.

Wang, H., Barber, T., Rosthal, R., Tabanou, J., Anderson, B., and Habashy, T., 2003, Fast and rigorous inversion of triaxial induction logging data to determine formation resistivity anisotropy, bed boundary position, relative dip and azimuth angles: Society of Exploration Geophysicists Technical Program Expanded Abstracts, p. 514-517, doi:10.1190/1.1817974.

Abstract: In this paper, we present a fast and rigorous inversion method to determine formation resistivity anisotropy, formation bed boundary location and relative dip and azimuth angles from a recently developed triaxial induction tool. This tool is fully triaxial and has sets of three orthogonal coils which are located at the same point. The sensitivity matrix with respect to horizontal conductivity, vertical conductivity, formation bed boundary locations is computed rapidly with the help of its analytical expression in a 1D TI anisotropic medium. The relative dip azimuth is solved first by rotating the full tensor measurement. The rest of the parameters are solved simultaneously by using Gauss-Newton minimization. The inversion results on synthetic data and field data show the accuracy and efficiency of the inversion algorithm.

Zhang, J., Hu, Q., Oyang, J., and Lin, C., 1998, A method to evaluate reservoirs and estimate saturation by dynamic responses of dual-induction logging tools: Journal of Petroleum Science and Engineering, v. 19, no. 3-4, p. 233-240, doi:10.1016/S0920-4105(97)00046-6.

Abstract: The invasion of drilling mud–filtrate into a reservoir is a dynamic process. Formation-resistivity profiles are therefore invasion-time dependent. The dynamic response model for resistivity logs is established and solved by numerical methods. The present model gives more physical understanding to the invasion process than the conventional step model does. The dynamic resistivity responses are sensitive to the variations of formation–water saturation, hence an effective method to evaluate reservoirs is suggested by history matching the dynamic dual-induction logging readings. Field examples are illustrated that distinguish oil reservoirs, water zones, and oil/water zones, as well as define the oil–water interface by the responses of induction logs at different logging times after drilling.

References

Collier, H.A., 1993, Focused Electrode and Induction Tools, in Borehole Geophysical Techniques for Determining Water Quality and Reservoir Parameters of Fresh and Saline Water Aquifers in Texas: Austin, Texas, Texas Water Development Board, v. 1, p. 201-236.

Metzger, L.F. and Izbicki, J.A., 2012, Electromagnetic‐Induction Logging to Monitor Changing Chloride Concentrations: Groundwater, v. 51, no. 1, p. 108-121, doi:10.1111/j.1745-6584.2012.00944.x.

Mussett, A.E. and Khan, M.A., 2000, Well Logging and Other Subsurface Geophysics, in Looking into The Earth: An Introduction to Geological Geophysics: New York, Cambridge University Press, p 285-305.

Prinos, S.T. and Valderrama, R., 2016, Collection, Processing, and Quality Assurance of Time Series Electromagnetic-Induction Log Datasets, 1995–2016, South Florida: U.S. Geological Survey Open-File Report 2016-1194 (pdf, 24 p.), doi:10.3133/ofr20161194.

Williams, J.H., Lapham, W.W., and Barringer, T.H., 1993, Application of electromagnetic logging to contamination investigations in glacial sand and gravel aquifers: Ground Water Monitoring and Remediation Review, v. 13, no. 3, p. 129-138, doi:10.1111/j.1745-6592.1993.tb00082.x.