SweetSpot – a computer system for storing and sharing data on the rock properties of shale formations

Budak, P.; Łętkowski, Piotr; Szpunar, T.; Nowak, Robert; Radzikowski, Kacper; Arabas, Jarosław

doi:10.18668/ng2015.12.02

Cited by 2 publications

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“…We now want to divide the dataset into a predetermined number of groups (clusters) which will be as different as possible. The action of the algorithm begins by picking two random k clusters, followed by moving the grouped objects between these clusters in order to (1) minimise the variability inside the clusters and (2) maximise the variability between the clusters. In other words, our goal is to obtain the maximum similarity in the group, accompanied by a maximum diversification between the groups.…”

Section: Grouping Using the K-means Methodsmentioning

confidence: 99%

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

Łętkowski

Gołąbek

Budak³

et al. 2016

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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.

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Section: Grouping Using the K-means Methodsmentioning

confidence: 99%

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

Łętkowski

Gołąbek

Budak³

et al. 2016

Self Cite

View full text Add to dashboard Cite

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“…Another example of the use of statistical methods for the categorisation of measurement data is [3]. A direct inspiration to conduct the following analysis was the desire to construct a method of the identification of similar wells in order to implement it in a computer system for collecting and exchanging data for shale rocks [1]. The analysis presented in the paper constitutes a first stage of such a method of identification.…”

mentioning

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Factor analysis of measurement data using the example of physicochemical well data for shale formations

Łętkowski

Gołąbek

Budak

et al. 2016

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The paper presents the use of statistical factor analysis for the reduction of the number of physicochemical measurement variables, based on the example of well data from shale formations. The main objective of the conducted analyses was the reduction of the number of measurement variables in a manner which would enable the preservation of the possibly high amount of information about the variability of the original data. The presented procedure consists of two main stages: 1) the elimination of correlated variables, 2) the actual factor analysis. The method turned out to be effective and it can constitute a basis for further analyses, e.g. an agglomeration analysis.Key words: shale formations, physicochemical measurements, factor analysis.Analiza czynnikowa danych pomiarowych na przykładzie danych fizykochemicznych odwiertów formacji łupkowych W artykule przedstawiono zastosowanie statystycznej analizy czynnikowej do redukcji liczby fizykochemicznych zmiennych pomiarowych na przykładzie danych z odwiertów w formacjach łupkowych. Celem przeprowadzonych analiz była redukcja liczby zmiennych pomiarowych w sposób umożliwiający zachowanie możliwie dużej ilości informacji na temat zmienności pierwotnych danych. Przedstawiona procedura składa się z dwóch podstawowych etapów: 1) eliminacja zmiennych skorelowanych, 2) właściwa analiza czynnikowa. Metoda okazała się być efektywna i może stanowić podstawę dla dalszych analiz, np. analizy aglomeracyjnej.Słowa kluczowe: formacje łupkowe, pomiary fizykochemiczne, analiza czynnikowa.Depending on the degree of the identification of a reservoir we may deal with several to over a dozen measurement values (measurement variables) characterising the petrophysical, geochemical, lithological or mechanical properties in each well in the reservoir. As the measurements progress, for each well we get a set of measurement variables of various types (measured in different units), which are not only correlated with each other to a varying extent, but also contain a very high number of cases, meaning the individual measurements taken along the depth of the well. The high number of variables and the amount of individual measurements are the cause of redundancy, resulting in difficulties associated with their interpretation, and make the detection of the internal structure of the data more difficult.Limiting the number of measurement variables would allow their more effective analysis and the determination of the characteristic values for each well. These values would constitute a basis for the assessment of the similarity of data originating from various wells. To this end, the use of basic statistical values such as the mean value or variance is

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SweetSpot – a computer system for storing and sharing data on the rock properties of shale formations

Cited by 2 publications

References 1 publication

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

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

Factor analysis of measurement data using the example of physicochemical well data for shale formations

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