Technology Limitations

Parameters

All ES investigations produce data sets which are relative by definition. These relative parameters include:

  • Depth estimates are relative to the applied seismic velocity models utilized while producing an ES model.
  • Hydraulic parameters are relative to the applied calibration data used to create a model.
  • Geological parameters such as formation conductivity and chemical composition effect the ES data being interpreted.
  • Electro-seismic interpretations are relative and subject to the geological context of the site being investigated.
  • All data sets produced by the ATS GeoSuite System are inferred, relative, estimates of the hydrological, geophysical, electrical and geophysical values recorded and processed. The data sets are to be considered to be inferred, relative, estimates of the values represented and at no point are to be considered absolute or real world values.
  • Thus all the ES response data is considered to be relative to the site geological and geo-hydrological composition.

Limitations

As such, a few limitations apply when interpreting ES data sets. These include but are not limited to:

  • The site geology at each survey point is assumed to be of similar seismic velocity parameters. This is not always the case as slight variations in geological formation density, porosity, compressibility and stratification are always present. This results in slight variations in the seismic velocity profiles between each unique ES sounding location even if the geology is similar. Statistically, these variations can be up to 25% of the base velocity model for the site. As such, any interpretation of the depth estimates for ES responses must account and compensate for these potential depth estimate variations. In most cases, the unique seismic velocity profile for each survey point generally can’t be known, a general seismic velocity model is applied to all the survey points in a project. This may produce some variations in the interpreted depth of the resultant ES responses.
  • ES data sets are vertical data sets, describing the geology and geo-hydrology of the site directly under the survey point. As such, ES survey point lateral resolution plays a significant role in the size and dimensions of the near vertical geological structures and features that be delineated or interpreted by ES data sets.
  • Even though the vertical resolution of an ES sounding is relatively high, with samples being taken every 8 to 12cm vertical depth depending on the velocity model used, it is important to note that a great deal of raw resolution is lost during the processing of the data. This is due to filtering and smoothing constraints applied to the data sets. As such, it is not practically possible to accurately delineate geological features thinner than 1m in thickness.
  • ES data sets for 2D and 3D interpretations rely heavily on interpolation to describe the correlation between geological and hydrological features. As interpolation parameters are set to default values that assumes that the geological setting of any particular site is mostly stratified in a horizontal or near horizontal plain, these interpolation strategies should always be considered when interpreting complex geologies. If such, complex geology, cases arise, a far better understanding of the geological context must be applied to the interpretation of such sites, in order to produce a better ES site description.
  • The interpolation methods used in the app assume a flat horizontal geology. As such, any aggressively dipping formations may be incorrectly interpreted by the interpolation algorithms and result in incorrect visualization of the ES data. If strongly dipping geology is expected, it would be better to export the data for visualization in a 3rd party visualization tool capable of interpreting dipping geologies.
  • The ES data resolution in the lateral plane can only be improved by narrowing the distance between individual ES soundings.
  • In the case of un-calibrated hydrological data interpretations, it must be understood that all ES hydrological data is subjective and relative to the maximum recorded ES response values. These data sets must be considered with reference to the geological setup of the site. For example, a low permeability formation such as a granite generally does not host high permeability, or hydraulic conductivity, aquifers. There may be slight variations in the hydraulic conductivity or permeability in the makeup of such geologies. However, a relative ES interpretation of such a geology may be misinterpreted as a high permeability aquifer. The best way to avoid these misinterpretations is to calibrate the model to the hydrological parameters of a known well that resides within the same geology as the survey site.
  • ATS ES methods cannot predict the groundwater yield that an interpreted aquifer will produce. Any estimates of groundwater flow potential, discussed in this ES study report, is merely an indicator of where the best interpreted location is for groundwater flow.
  • ES data cannot currently determine the porosity of a formation, it can only infer formations with higher porosity values.
  • The ES processing and interpretation workflow assumes that the data collected in the field was done on surface soil and sediment conditions of similar characteristics. It assumes that the site soil conditions are uniform in moisture content, electrical conductivity and soil composition. It is also assumed that the ES electrode placement and recorder settings were conducted in exactly the same manner for each sounding and that noise sources were removed as far as possible. The seismic source energy is also assumed to be consistent in strength, for every seismic event generated to produce a recorded ES conversion.
  • It is assumed that the ES survey was done in the lowest noise location possible and that all possible extraneous sources of seismic noise were eliminated from the site before surveying commenced.
  • Any electrical noise sources, such as power line noise, is assumed to be consistent in frequency and amplitude and produces odd and even harmonics that can be predictably filtered out. Any other types of electrical noise sources such as electric fences are assumed to have been physically removed from the site.
  • Fracture indicators can be generated by interfacial responses, ferrite, quart or sulfide bearing geological features. Any interpretation of possible bedding plain fractures must be done cautiously. Any other possible geological features that may have caused such fracture indications must be considered.
  • ES data interpretations and calibrations rely heavily on the correctness and relevance of the geological and hydrological data provided for the investigation site. If incorrect data is provided, then it is then possible that incorrect results and interpretations of the ES data may result.
  • Strong geological interfacial seismic reflectors may cause echo effects in an ES survey. This is due to a strong geological reflector re-bounding the injected seismic wave which then re-passes through geological features on its way back to the surface. This causes what appears to be a mirror image of the ES data with depth. As such, known strong geological seismic reflectors should always be considered when interpreting ES data set.
  • ES methods cannot determine the depth of the static water table at a survey point. As such, any permeable formations indicated on ES data sets that reside above the static water table, must be considered as poor aquifers that do not contribute to groundwater flow or yield.
  • ES Methods cannot differentiate between fully and partially saturated aquifers. As such, ES methods cannot determine if an aquifer has been partially dewatered or if an aquifer is fully saturated. Even if an aquifer has been depleted, there is still water within the aquifer which allows an Electro-seismic conversion to take place which describes the permeability of the aquifer and the pore space fluid characteristics. However, it will not indicate whether the aquifer is productive or not. With this in mind, all aquifers delineated by ES methods are assumed to be fully saturated and capable of yielding groundwater.
  • The GeoSuite app cannot always filter out co-seismic ES effects that occur within the first 20 to 40 meters from surface level depending on the seismic velocity model used. This effectively means that sometimes the ES technologies used by the GeoSuite app can interpret false positive aquifer readings up to depths of 40m depending on the seismic velocity model used.
  • If there is a very strong acoustic reflector at the interface between to geological formations which have large differences in acoustic impedance under a survey point, then this could cause the seismic impulse wave to reflect back to the surface and produce ghost, of false, ES responses. If this occurs, then the ES data sets may contain interpret an aquifer response incorrectly. This limitation of the ES technology must be considered when interpreting ES data sets.
  • When seismic attenuation correction is applied to the data sets, the noise content will also be amplified. This may cause noise effects to affect the resultant data.
  • When the echo cancellation method provide on the app are used to remove echo effects, the system assumbs that echo effects are present in the data sets.It is upto the user to determine if these echo effects are infact present in an indevidul points data set. If echo cancellation is applied to a ES data set which does not have echo effect within it, then the echo cancellation can cause deformation of the ES data sets.

As there are a number of assumptions made using ES methods to estimate and interpret the geology and geo-hydrology of a site, the results presented as well as the interpretations made in this report cannot be guaranteed to be absolutely correct. ES data can only provide an estimated insight into the geological and geo-hydrological makeup of a study site based on the information available.

ATS ES data should always be used, when possible, in conjunction with other geophysical information sources, in order to produce a better resultant site geological and hydrologic interpretation.