Determination of the statistical similarity of the physicochemical measurement data of shale formations based on the methods of cluster analysis

Abstract

Determination of the statistical similarity of the physicochemical measurement data of shale formations based on the methods of cluster analysisThe paper presents the application of the methods of statistical analysis to the determination of the similarity of measurement data, using boreholes providing access to shale formations as an example. The proposed methodology is based on two statistical techniques: the factor analysis and the cluster analysis. The first method allows the reduction of the number of measurements variables in order to eliminate the redundancy of the data. The second one allows grouping the wells on the grounds of factor variables defining the similarity features of the analysed wells. The available results of geochemical measurements for nine wells providing access to shale structures have been used as measurement data.Key words: shale formations, factor analysis, cluster analysis.Określenie podobieństwa statystycznego fizykochemicznych danych pomiarowych formacji łupkowych na podstawie metod analizy klastrowej W artykule przedstawiono zastosowanie metod analizy statystycznej dla określenia podobieństwa danych pomiarowych na przykładzie odwiertów udostępnionych w formacjach łupkowych. Proponowana metodologia zakłada zastosowanie dwóch technik statystycznych: analizy czynnikowej oraz analizy skupień. Pierwsza z metod pozwala na redukcję ilości zmiennych pomiarowych w celu wyeliminowania redundancji danych, natomiast druga umoż-liwia pogrupowanie odwiertów w oparciu o zmienne czynnikowe definiujące cechy podobieństwa analizowanych odwiertów. Jako dane pomiarowe wykorzystano dostępne wyniki pomiarów geochemicznych dla dziewięciu odwiertów udostępnionych w strukturach łupkowych.Słowa kluczowe: formacje łupkowe, analiza czynnikowa, analiza klastrowa.One of the basic elements of the identification and examination of hydrocarbon reservoir are the laboratory tests providing the necessary information on the geological structure, mechanical, physicochemical and petrophysical properties of the reservoir rock, the characteristics of reservoir fluids etc. Due to the amount and complexity of the available data, their statistical analysis constitutes a certain challenge. The problem is that the various types of measurement values (measured in various physical units) are correlated in a varying degree, which combined with the number of single calculations for each measurement value generates problems when interpreting and attempting to identify their internal structure. The use of the characteristics of descriptive statistics, i.e. the measure of placement, diversification, concentration or asymmetry seems to be insufficient, since it gives no detailed information about the variability of data following the depth, which constitutes significant information for the construction of geological and simulation models.

Improving the Efficiency of Oil Recovery in Research and Development

“…The classification of objects is based on a cluster analysis, where the focus is on the issue of generating clusters that are grouped into samples in gas, condensate and oil windows [29]. The characteristic geochemical properties of the samples classified into selected clusters are also determined [30]. Researchers successfully classified the samples into individual windows and determined their percentages in Silurian, Ordovician and Cambrian units.…”

Use of Cluster Analysis to Group Organic Shale Gas Rocks by Hydrocarbon Generation Zones

“…Cluster analysis methods have also been applied to investigate the similarity of samples described with geochemical parameters. One of the key issues presented in these works was the identification of rocks with similar total organic carbon (TOC) values [39][40][41]. The results demonstrated that it is possible to group the samples assigned to gas, condensate, and oil windows through cluster analysis.…”