Geochemical data quality control as a tool for improving the interpretation of formation water chemistry: a case study of the achimov formation, northern West Siberia

Abstract

The article addresses a pressing issue in modern hydrogeochemical research — the low reliability of results in determining the chemical composition and salinity of formation waters, which often arises due to technical or methodological errors. These inaccuracies subsequently lead to highly uncertain saturation forecasts when poor-quality data are used for geophysical log interpretation. In this work, a new step-by-step geochemical control algorithm (GCA) is proposed for filtering datasets of formation waters composition from the Achimov Formation in the northern part of Western Siberia. The proposed algorithm consists of several consecutive stages — verification of electroneutrality, determination of water type according to Sulin’s classification, and control of hydrochemical parameters. As a result of passing these stages, a filtered and conditionally valid dataset is obtained. Based on the GCA of the analyzed formation-water chemistry data, it was found that only 8.1 % of 242 samples can be considered reliable and suitable for further interpretation. These samples most closely reflect the true composition of the Achimov Formation waters and can be used as reference data. The application of GCA has proven effective in screening out invalid analyses and obtaining accurate values for formation water composition and salinity, which in turn increases the reliability of geophysical forecasts. Possible solutions to improve data quality are also proposed, including methodological adjustments and modernization of laboratory analytical equipment.