Analysis of some error-causing factors in two-dimensional geoelectrical studies and providing a solution to minimize them

Document Type : Review Article

Authors

• Hosein Moghaddasi ¹
• Mohsen Moghaddasi ¹
• Ahmad Neyamadpour ²

¹ Exploration geophysicist, Jarfabkavosh Co., Tehran, Iran

² Assistant Professor, Department of Geophysics, Masjed-Soleiman Branch, Islamic Azad University, Masjed-Soleiman, Iran

10.22067/econg.2024.1123

Abstract

In recent years, two-dimensional geoelectrical surveys have become one of the common and conventional methods in mineral exploration, groundwater resources investigations, engineering geophysics, archeology, etc. However, in some cases, these studies could not reach the targeted and expected results, and sometimes the geophysical results obtained have had a significant distance from the results obtained from direct studies such as drilling, etc. In this article, authors try to comprehensively analyze some factors that cause errors in two-dimensional geoelectrical studies, and on the other hand, state solution for minimizing the amount and severity of the discussed errors. Also, it has been tried to provide practical solution and approach for minimizing the error factors by a deep understanding of the source and mechanism of error factors. Finally, a case study in which geoelectrical data has been acquired by applying that new approach has been presented.
 
Introduction
2d geoelectrical investigations are one of the most important and effective methods for the study and exploration of different minerals, groundwater, etc (Moghaddasi, et al., 2020). They are also used for geotechnical and engineering geophysics analyses. But in some projects, the final validation test results such as drilling don’t correspond so much with geoelectrical results so the output of the project didn’t satisfy the clients. In this article, we will discuss error-causing factors and will provide a solution to minimize them
 
Discussion
Pole-dipole and dipole-dipole arrays are two of the most used arrays for 2d geoelectrical studies. Figure 1 shows these arrays. The spacing between the current electrodes pair, C2-C1, is given as “a” which is the same as the distance between the potential electrodes pair P1-P2. These arrays have another factor marked as “n”. This is the ratio of the distance between the C1 and P1 electrodes to the C2-C1 (or P1-P2) dipole length “a” (Loke, 2023).
But one of the main questions is what is the maximum and reasonable “n” for each array and why data acquisition by the large amount of “n” is wrong and leads to bad data?
 First of all, we consider the sensitivity function meaning.  The sensitivity function tells us the degree to which a change in the resistivity of a section of the subsurface will influence the potential measured by the array. The higher the value of the sensitivity function, the greater the influence of the subsurface region on the measurement (Loke, 2023). Now we discuss about those arrays:
 
Pole-dipole array
The pole-dipole array also has relatively good horizontal coverage, but it has a significantly higher signal strength than the dipole-dipole array and is not as sensitive to telluric noise as the pole-pole array (Loke, 2023).
By following figures, we analyze the effect of the large “n” on the acquired data in this array:
Figure 2 sensitivity sections show that the area with the greatest sensitivity lies beneath the P1-P2 dipole pair, particularly for large “n” factors. For “n” values of 4 and higher, the high positive sensitive lobe beneath the P1-P2 dipole becomes increasingly vertical (Loke, 2023).
It can be understood based on Figure 3 what will happen when the ‘n’ factor jumps from 6 to 12 to 18. Here, the dipole length is kept constant at 1 meter. When ‘n’ is equal to 6 there are reasonably high sensitivity values to a depth of about 3 to 4 meters between the C1 current and the P1 potential electrode. When ‘n’ is increased to 12, the zone of high sensitivity values becomes increasingly more concentrated below the P1-P2 dipole in an even shallower region. This means that the array with ‘n’ equal to 12 is less sensitive to deeper structures than the array with ‘n’ equal to 6. This effect is even more pronounced when ‘n’ is increased to 18. (Loke, 2023).
Figure 4 shows the apparent resistivity anomaly due to a small near-surface high resistivity block for the pole-dipole array for ‘n’ values of up to 28. Note that the amplitude of the high resistivity anomaly due to the near-surface block increases with the ‘n’ value, i.e., the array becomes increasingly more sensitive to the near-surface block as the separation between the electrodes increases. In field surveys with the pole-dipole array where the ‘n’ factor is monotonically increased in the belief that this increases the survey depth, the pseudosection is frequently dominated by a series of parallel slanting high-amplitude anomalies due to near-surface inhomogeneities. The anomalies due to the near-surface structures frequently mask the anomalies due to deeper structures that are of interest. (Loke, 2023).
 
Dipole-dipole array
This array has been, and is still, widely used in I.P. surveys because of the low EM coupling between the current and potential circuits.
Figure 5 shows dipole-dipole sensitivity sections for n: 1, 2, 4, and 6 (Loke, 2023). Again, as can be seen for this array by increasing the “n” factor sensitivity tends to be beneath of dipole position on the surface and the sensitivity of the deeper part (which is our target zone for investigation), decreases dramatically
 Now we can understand how much lateral resistivity inhomogeneities, rough topography, presence of high contact resistance, etc., (which are all unavoidable factors in IP/Rs data acquisition), will have an adverse effect on final data when data is acquired by larger.
Also, during the inversion process, even those correct data which was acquired by smaller ‘n’ will be badly affected in the final sections.
Loke, as the creator of Res2dinv software, states that acquired data with “n” higher than 6-8 are so susceptible to noises, etc., and can cause wrong data (Loke, 2023). However, according to the authors of this article, even these values should be considered with caution and we suggest data acquisition with an even lower “n”.
In fact, in the real world, and especially in IP/Rs investigation, many factors are the source of noise and we should use lower “n” factors to get the correct and real data. 
Unfortunately, in some projects using larger “n” is routine and this is the main reason for failing the 2d geoelectrical project.
 
Suggested and optimal method
According to the mentioned sensitivity sections, it can be seen that the best scenario for geoelectrical surveys is when the surveys are done by n=1, and for increasing the exploration depth, the electrode distance (a) is gradually increased instead of increasing the “n” factor. The most favorable state of the sensitivity cross-section, the highest amount of signal to noise, and the least impact of noises and surface inhomogeneities occur in n=1. Nowadays with the introduction of newer technologies such as automatic electrode switching geoelectric equipment and also switch boxes, the suggested optimal method can be implemented more easily.
 Geoelectrical surveys with this method (n=1 and intermittent increase of the electrode distance) may reduce the speed of the operation and be less economical for contractors, but the results of the geoelectrical studies conducted with this method are much more reliable
Figure 6. shows one of the case studies in which authors used above suggested method and the results were excellent and RMS was very low.
 
Conclusion
In this article, it was tried to present a kind of pathology regarding the reasons of the failure of some two-dimensional geoelectrical studies with an analytical view and by the results obtained from the modeling and also the field analysis of the authors. It was clarified how much measurements with high “n” values can cause errors.
Finally, it was stated that the maximum reasonable and reliable number for n is 6-8 and it was stated that due to the presence of noise sources, also these numbers should be considered with caution.
Finally, the optimal method from which the best results are obtained was proposed.

Keywords

• dipole-dipole
• pole-dipole
• geoelectric
• electrical resistivity
• chargeability
• RES2DINV

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References

Dentith, M. and Mudge, S., 2014. Geophysics for the Mineral Exploration Geoscientist. Cambridge University Press, New York, 454 pp.

Ghanbari, H., Arab Amiri, A., Ebrahimi, S. and Mehri, M., 2020. Modeling and Interpretation of the Induced Polarization and Resistivity Data in Sharifabad Exploration Area, Northwest of Bardeskan. Journal of Research on Applied Geophysics, Volume 6(1): 12–23. (in Persian with English abstract) https://doi.org/10.22044/jrag.2018.5782.1123

Kalagari, A.A., 1992. Principles of Geophysical Exploration. Tabriz University Press, Tabriz, 558 pp. (in Persian)

Loke, M.‌H., 2023. Tutorial: 2-D and 3-D electrical imaging surveys, s.l.: Geotomo Software, Res2dinv Software. Retrieved September 16, 2023, from

 http://www.researchgate.net/publication/264739285_Tutorial_2D_and_3D_Electrical_Imaging_Surveys

Meju, M., 1986. Geophysical data analysis: Understanding inverse problem theory and practice, SEG Press, Houston, 130 pp.

Milsom, J. and Eriksen, A., 2011. Field geophysics. Wiley Press, New Jersey, 304 pp.

Moghaddasi, M. and Moghaddasi, H., 2023. A new method for IP/Rs data acquisition in the frequency domain on a network. 15th Symposium of Iranian Society of Economic Geology, University of Damghan, Damghan, Iran. (in Persian with English abstract) Retrieved September 1, 2023, from

 https://www.researchgate.net/publication/373916659_abda_rwsh_nwyn_brdasht_IPRs_bh_swrt_shbkh_ay_A_new_method_for_IPRs_data_acquisition_on_a_network

Moghaddasi, H., Moghaddasi, M. and Abbasinia, M., 2020. The role of correct delineation of bedrock topography in successful groundwater exploration using Electrical resistivity tomography. 19th Iranian Geophysics Conference, University of Tehran (Institute of geophysics), Tehran, Iran. Retrieved November 1, 2020 from

 https://www.researchgate.net/publication/345490809_The_role_of_correct_delineation_of_bedrock_topography_in_successful_groundwater_exploration_using_Electrical_resistivity_tomography

Moghaddasi, H., Moghaddasi, M. and Masnabadi, M., 2024. Integrated use of analytical signal and upward continuation for exploration of porphyry deposits and also separation and delineation of alterations related to these deposits (case study from the south of Kerman province). 16th Symposium of Iranian Society of Economic Geology. university of Tabriz, Tabriz, Iran. (in Persian with English abstract) Retrieved September 1, 2024, from

 https://www.researchgate.net/publication/382889454_bh_kargyry_tlfyqy_mlgrhay_sygnal_thlyly_w_adamh_frasw_dr_aktshaf_kansarhay_pwrfyry_w_tfkyk_dgrsany_hay_mrtbt_ba_anha_mthal_mwrdy_az_jnwb_krman_Integrated_use_of_analytical_signal_and_upward_continuati

Moshtaghian, K., Abtahi, M., Esadi, H., Haj Heydari, M. and Jangarban, G., 2022. Inversion modeling of magnetic and IP/RS data with the aim of exploration of the northern porphyry copper-gold deposit of Dali. Scientific Quarterly Journal of Geosciences, 33(3): 79–92. https://doi.org/10.22071/gsj.2021.272272.1886

Neyamadpour, A., Wan Abdullah, W., Taib, S. and Neyamadpour, B., 2010. Comparison of Wenner and dipole–dipole arrays in the study of an underground three-dimensional cavity. Journal of Geophysics and Engineering, 7(1): 30–40. http://dx.doi.org/10.1088/1742-2132/7/1/003

Samadi, L., 2012. Basic Applied Geophysics. Jahad Daneshgahi Kharazmi University Press, Tehran, 620 pp.

Telford, W.M., Geldart, L.P. and Sheriff, R.E., 1990. Applied geophysics. Cambridge University Press, New York, 751 pp.

White, R., Collins, S. and Loke, P., 2003. Resistivity and IP arrays, optimised for data collection and inversion. Exploration Geophysics, 34(4): 229–232. http://dx.doi.org/10.1071/EG03229