Improved recognition of rock formation on the basis of well logging and laboratory experiments results using factor analysis

• Autorzy: Puskarczyk Edyta , Jarzyna Jadwiga A. , Wawrzyniak-Guz Kamila , Krakowska Paulina I. , Zych Marcin

Identyfikatory

DOI

10.1007/s11600-019-00337-8

• Języki publikacji: EN

Abstrakty

EN

Several data sets from the Silurian and Ordovician formations from three wells on the shore of Baltic Basin in Northern Poland prepared on the basis of well logging data and results of their comprehensive interpretation were used in factor analysis. The goal of statistical analysis was structure recognition of data and proper selection of parameters to limit the number of variables in study. The top priority of research was recognition of specific features of claystone/mudstone formations predisposing them to be potential shale gas deposits. The identified data scheme based on data from one well, was then applied to: 1) well 2 and well 3 separately, 2) combined data from three wells, 3) depth intervals treated as sweet spots, i.e., formations of high hydrocarbon potential. Numbers of samples from well logging were proportional to number of laboratory data from individual formations. The extended data set comprising all available log samples in explored formations was also prepared. Outcomes from standard (Triple Combo—natural gamma log, resistivity log, neutron log and bulk density log and Quad Combo—with addition of sonic log and spectral gamma log) and sophisticated (GEM^™—Elemental Analysis Tool, Wave Sonic and Nuclear Magnetic Resonance—NMR) logs were the basis for data sets. Finally, laboratory data set of huge amount of variables from elemental, mineralogical, geochemical and petrophysical laboratory experiments was built and verified in FA to select the most informative components. Conclusions on the data set size, number of factors and type of variables were drawn.

Słowa kluczowe

EN

rock formation; petrophysical characteristics; well logging; laboratory experiments; Factor Analysis

PL

formacje skalne; cechy petrofizyczne; geofizyka otworowa; eksperymenty laboratoryjne; analiza czynników

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2019
• Tom: Vol. 67, no. 6
• Strony: 1809--1822
• Opis fizyczny: Bibliogr. 14 poz.

Twórcy

autor

Puskarczyk Edyta

• AGH University of Science and Technology, al. A. Mickiewicza 30, 30‑059 Kraków, Poland

autor

Jarzyna Jadwiga A.

• AGH University of Science and Technology, al. A. Mickiewicza 30, 30‑059 Kraków, Poland

autor

Wawrzyniak-Guz Kamila

• AGH University of Science and Technology, al. A. Mickiewicza 30, 30‑059 Kraków, Poland

autor

Krakowska Paulina I.

• AGH University of Science and Technology, al. A. Mickiewicza 30, 30‑059 Kraków, Poland

autor

Zych Marcin

• AGH University of Science and Technology, al. A. Mickiewicza 30, 30‑059 Kraków, Poland

Bibliografia

• 1. Asfahani J, Aissa M, Al-Hent R (2005) Statistical factor analysis of aerial spectrometric data, Al-Awabed area, Syria: a useful guide for phosphate and uranium exploration. Appl Radiat Isotopes 62:649–661. https://doi.org/10.1016/j.apradiso.2004.08.050
• 2. Bała M, Cichy A (2007) Comparison of P- and S-waves velocities estimated from Biot Gassmann and Kuster-Toksöz models with results obtained from acoustic wavetrains interpretation. Acta Geophys 55(2):222–230. https://doi.org/10.2478/s11600-007-0006-6
• 3. Costello AB, Osborne J (2005) Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Practical Assessment Research & Evaluation, 10 (7). Available online: http://pareonline.net/getvn.asp?v=10&n=7, pp 9
• 4. Hair JF Jr, Black WC, Babin BJ, Anderson RE, Tatham RL (2006) Multivariate data analysis. Pearson Prentice Hall, New Jersey
• 5. Jarzyna J, Wawrzyniak-Guz K (eds) (2017) Adaptation to the Polish conditions of the methodologies of the sweet spots determination on the basis of correlation of well logging with drilled core samples: methodology to determine sweet spots based on geochemical, petrophysical and geomechanical properties in connection with correlation of laboratory test with well logs and generation model 3D. Monography, 500 pp., GOLDRUK Wojciech Golachowski Printing House (in Polish)
• 6. Jarzyna JA, Bała M, Krakowska PI, Puskarczyk E, Strzępowicz A, Wawrzyniak-Guz K, Więcław D, Ziętek J (2017) Shale gas in Poland. In: Natural Gas. INTECH. ISBN: 978-953-51-4657-5, https://doi.org/10.5772/67301, distributed by Internet
• 7. Kaiser HF (1958) The varimax criterion for analytical rotation in factor analysis. Psychometrika 23(3):187–200. https://doi.org/10.1007/BF02289233
• 8. Kaźmierczuk M, Jarzyna J (2006) Improvement of lithology and saturation determined from well logging using statistical method. Acta Geophys 54:378–398. https://doi.org/10.2478/s11600-006-0030-y
• 9. Puskarczyk E (2018) Applying of the Artificial Neural Networks (ANN) to identify and characterize in shale gas. E3S Web of Conferences; ISSN 2267-1242.—2018 vol 35 art. no. 03008, s. 1–7.—https://www.e3s-conferences.org/articles/e3sconf/pdf/2018/10/e3sconf_polviet2018_03008.pdf
• 10. Statistica 13.3 Help, 2019, electronic version
• 11. Szabó NP (2011) Shale volume estimation based on the factor analysis of well-logging data. Acta Geophys 59:935. https://doi.org/10.2478/s11600-011-0034-0
• 12. Thommes M, Kaneko K, Neimark AV, Olivier JP, Rodriguez–Reinoso F, Rouquerol J, Sing KSW (2015) Physisorption of gases. with special reference to the evaluation of surface area and pore size distribution (IUPAC Technical Report). Pure and Applied Chemistry, 87, 9–10, 1052–1069
• 13. Topór T, Derkowski A, Kuila U, Fischer TB, McCarty DK (2016) Dual liquid porosimetry: a porosity measurement technique for oil-and gas-bearing shales. Fuel 183:537–549. https://doi.org/10.1016/j.fuel.2016.06.102
• 14. Wawrzyniak-Guz K, Jarzyna JA, Zych M, Bała M, Krakowska PI, Puskarczyk E (2016) Analysis of the Heterogeneity of the Polish Shale Gas Formations by Factor Analysis on the Basis of Well Logs. In: Proceedings of the 78th EAGE conference & exhibition, 2016, Vienna, Austria, 30 May—2 June 2016, Tu SBT3 07

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).