Quality Checking for Geochemistry Data

The exploration phase at the beginning of a project has a vital role in describing the resource of one geothermal field area. 3G (geology, geochemistry, and geophysics) approach is still the best exploration method to recognize all geothermal system components. Exploration survey activity produces the data. Each method will have different challenges and pitfalls, especially in data/sample collection. Therefore, quality checks for the conducted data should be maintained.

In this first article, we will first delve more deeply into geochemistry data. Read on to understand the best practice of quality checks for geochemistry samples, both water, and gas, from field survey activity!

One step of ensuring quality data can be done by implementing treatments like conducting sample collection carefully, QAQC samples collection, and minimizing human error in the exploration data to avoid bias.

Additionally, we need to know the accuracy and precision of each data from the field survey.

Accuracy means how close the data is to the actual value, whereas precision is how much repeatability from the data has resulted from unchanged conditions (Streiner and Norman 2006).

Determining accuracy can be done through several methods, i.e. using standard additions to the sample and obtaining recovery percentage (%). Determining the same constituent through different methods and using standards or reference samples run with each batch of determined samples. Meanwhile, precision could be checked by duplicates sample analysis (ármannsson and ólafsson 2007). Keep in mind that all these treatments could be done in the pre-analysis step for QAQC data.

Despite obtaining the chemical constituents from a lab analysis for geochemistry data treatment, all samples may still have low accuracy. It may be caused by several factors, such as the poor resolution of the instrument of analyses and failure of sample collection, among others. Those should be considered before continuing to data interpretation.

Several methods could be done to minimize the uncertainty level of water and gas sample data.

Water sample

There are two essential methods for water sample quality checks after laboratory analysis.

Ion balance

Ion balance or charge balance is a common method used to check the accuracy of the geothermal fluid analysis. It is calculated by converting the concentration of all charged species (Na+, K+, Cl-, SO42-, HCO3-, etc) into milliequivalent (meq) units, then adding the sum of each anion and cation constituents (Nicholson 1993). The obtained sub of the anion and cation is then compared to obtain the difference in sum ion calculation.

The difference in the sum ion calculation should not be greater than 5 %; then, the sample could be adjusted for further interpretation. However, this method can only detect charged constituents and is insensitive to errors of the minor constituents. Additionally, this method also needs an understanding of the sample’s physical properties and fluid type because some water types, like sulphate water, commonly has high ion balance value.

Mass balance/TDS

TDS is the weight of total dissolved solids in the solution. The mass balance method compares the measured TDS values with the sum of the total dissolved solid species concentrations in weight unit, i.e., mg/kg (Nicholson 1993). However, this method is less reliable for some geothermal fluid types, such as a fluid with high bicarbonate content.

Measured TDS (mg/kg) / ∑ solute concentrations (mg/kg). The difference of the mass sum should not be greater than 5%.

Gas sample

O2 check

Geothermal gas chemistry analysis aims to determine subsurface conditions through subsurface gas content discharged through surface manifestation. A simple method to evaluate the quality of the gas sample can be commonly done through the presence of O2 gas content. The O2 content in an uncontaminated gas sample should be close to or under the detection limit of the sample (Nicholson 1993).

O2 is one of the main gas content on the surface environment; the sampling procedure must be done carefully to prevent surface gas contamination in sample gas collection. The following table is an example of gas sample data from surface manifestation in one geothermal field area that contained O2 (mmol% unit).

N2/Ar ratio

Besides oxygen content, the degree of atmospheric/surface contaminant can be viewed based on N2 and Ar content. The N2/Ar ratio helps show the relative contribution of magmatic or meteoric gas/air sources (Powell 2010). There are two approaches for determining the N2/Ar ratio: N2-Ar-CO2 ternary diagram and N2-Ar-He ternary diagram. Both ternary diagrams can be used to determine the source of geothermal gas and indicate if air contamination might adversely affect the interpretation of gas chemistry (Giggenbach 1992). Atmospheric contamination is commonly indicated by a value of N2/Ar ratio close to 84.

The ternary diagrams below are an example of N2/Ar ratio application to determine the geothermal gas source in a geothermal field. The ternary diagrams show that all samples are plotted close to Air Saturated Water (ASW) condition, thus indicating meteoric water affected gas sample.?

So, both methods have their advantages and disadvantages, depending on the intended aim of the fluid. A good geochemist will elaborate on all data. However, an excellent geochemist is always curious about where the data come from and respect the data’s quality.

(Written by Galih Bayu Permadi)

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References

ármannsson, Halldór, and Magnús ólafsson. 2007. “GEOTHERMAL SAMPLING AND ANALYSIS.” 8.

Geoenergis. 2021. A Geothermal Prospect Area: Final Report Peer Review, Geoscience and Well Targeting. Unpublished report.

Giggenbach, W.F. 1992, Isotopic shifts in waters from geothermal and volcanic systems along convergent plate boundaries and their origin, EPSL 113, 495-510.

Nicholson, Keith. 1993. Geothermal Fluids. Berlin, Heidelberg: Springer Berlin Heidelberg.

Powell, T., & Cumming, W. (2010, February). Spreadsheets for geothermal water and gas geochemistry. In?Proceedings?(pp. 4-6).

Streiner, David L., and Geoffrey R. Norman. 2006. Precision’ and ‘Accuracy’: Two Terms That Are Neither. Journal of Clinical Epidemiology 59(4):327–30. doi: 10.1016/j.jclinepi.2005.09.005.