Factor Analysis of Well Logs for Total Organic Carbon Estimation in Unconventional Reservoirs

Norbert P. Szabó, Rafael Valadez-Vergara, Sabuhi Tapdigli, Aja Ugochukwu, István Szabó and Mihály Dobróka
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Norbert P. Szabó: Department of Geophysics, University of Miskolc, H-3515 Miskolc, Hungary
Rafael Valadez-Vergara: Department of Geophysics, University of Miskolc, H-3515 Miskolc, Hungary
Sabuhi Tapdigli: Department of Geophysics, University of Miskolc, H-3515 Miskolc, Hungary
Aja Ugochukwu: Department of Geophysics, University of Miskolc, H-3515 Miskolc, Hungary
István Szabó: MOL Plc., Group E&P Subsurface and Field Development, H-5000 Szolnok, Hungary
Mihály Dobróka: Department of Geophysics, University of Miskolc, H-3515 Miskolc, Hungary

Energies, 2021, vol. 14, issue 18, 1-17

Abstract: Several approaches have been applied for the evaluation of formation organic content. For further developments in the interpretation of organic richness, this research proposes a multivariate statistical method for exploring the interdependencies between the well logs and model parameters. A factor analysis-based approach is presented for the quantitative determination of total organic content of shale formations. Uncorrelated factors are extracted from well logging data using Jöreskog’s algorithm, and then the factor logs are correlated with estimated petrophysical properties. Whereas the first factor holds information on the amount of shaliness, the second is identified as an organic factor. The estimation method is applied both to synthetic and real datasets from different reservoir types and geologic basins, i.e., Derecske Trough in East Hungary (tight gas); Kingak formation in North Slope Alaska, United States of America (shale gas); and shale source rock formations in the Norwegian continental shelf. The estimated total organic content logs are verified by core data and/or results from other indirect estimation methods such as interval inversion, artificial neural networks and cluster analysis. The presented statistical method used for the interpretation of wireline logs offers an effective tool for the evaluation of organic matter content in unconventional reservoirs.

Keywords: total organic carbon (TOC); tight gas; shale gas; source rock; factor analysis (FA); interval inversion; artificial neural network (ANN); Hungary; Alaska; Norway (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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