Firstly, I have previously encountered a similar issue and would highly recommend exploring the utilization of ResIPy software for improved error analysis. The software can be accessed via the following link: https://github.com/hkexgroup/resipy/releases/download/v3.4.2/ResIPy-windows.exe Secondly, the absence of induced polarization (IP) anomalies while obtaining electrical resistivity tomography (ERT) measurements along the same profile could be attributed to various factors. Some of the potential explanations include: 1. Geological setting: The geologic composition of the area may not be conducive to the development of IP anomalies. For example, subsurface structures primarily composed of resistive materials such as sandstone or granite may inhibit the detection of significant IP effects. However, ERT measurements can still provide valuable information about the resistivity structure of the subsurface, regardless of IP anomaly presence. 2. Depth of investigation: The depth of investigation for IP and ERT surveys differ significantly. IP surveys are more sensitive to shallow subsurface anomalies (usually within the first few tens of meters), while ERT can detect resistivity variations at more considerable depths (sometimes up to hundreds of meters). Consequently, limited depth of investigation during IP surveys may hinder the detection of significant IP anomalies, while ERT can capture deeper subsurface structures. 3. Measurement protocols: The acquisition and processing protocols for IP and ERT surveys can differ significantly, and minor differences in measurement setup or data processing can significantly impact the results. Suboptimal parameters or data processing during IP surveys can result in a lack of significant IP anomalies, while better protocols during ERT surveys may yield useful resistivity data. 4. Instrumentation and data quality: The quality of instrumentation and data collected during surveys is also a crucial factor. Poor data quality or instrument malfunctioning can hinder the detection of IP anomalies, while useful resistivity data can still be acquired during ERT surveys with good data quality and functional instrumentation. It is important to note that these are just a few possible explanations, and the root cause could be a combination of these or other factors. A thorough analysis of survey data and site geology is necessary to provide a more definitive answer. Regarding my personal perspective, I would lean towards measurement protocol differences as the cause of the issue. To gain a better understanding of the problem, I would need to examine the IP measurements.

If you are using IP, I highly recommend using Resipy for your inversions. It has many tools for correctly filtering your data.

Also, by only removing bad data points you are damaging your input. Initial RMS of >50% is really high. It is possible that your data acquisition went wrong.

I think you have an issue during resistivity measuring, rms >50 % very hight and unconscionable.

It is important to choose suitable timing when doing IP measurements. According to the theoretical models commonly used when modelling and interpreting IP data the charge-up and decay processes have equal time characteristics. Although this may not always be the case in reality, it is recommendable to use equal duration for current-on and current-off in the measuring cycle. It is also important to use sufficient time to allow the IP phenomena to build up and decay, otherwise the measured chargeabilities can have large errors due to this. These errors cannot be removed by stacking but only by using longer times in the measuring cycle. Furthermore, the measured resistivities will be under estimated.

From the information you provided, it seems that when you reduced the RMS error of the resistivity data to