IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v392y2013i20p5132-5137.html
   My bibliography  Save this article

Non-Gaussianity effects in petrophysical quantities

Author

Listed:
  • Koohi Lai, Z.
  • Jafari, G.R.

Abstract

It has been proved that there are many indicators (petrophysical quantities) for the estimation of petroleum reservoirs. The value of information contained in each indicator is yet to be addressed. In this work, the most famous and applicable petrophysical quantities for a reservoir, which are the gamma emission (GR), sonic transient time (DT), neutron porosity (NPHI), bulk density (RHOB), and deep induced resistivity (ILD), have been analyzed in order to characterize a reservoir. The implemented technique is the well-logging method. Based on the log-normal model defined in random multiplicative processes, the probability distribution function (PDF) for the data sets is described. The shape of the PDF depends on the parameter λ2 which determines the efficiency of non-Gaussianity. When non-Gaussianity appears, it is a sign of uncertainty and phase transition in the critical regime. The large value and scale-invariant behavior of the non-Gaussian parameter λ2 is an indication of a new phase which proves adequate for the existence of petroleum reservoirs. Our results show that one of the indicators (GR) is more non-Gaussian than the other indicators, scale wise. This means that GR is a continuously critical indicator. But by moving windows with various scales, the estimated λ2 shows that the most appropriate indicator for distinguishing the critical regime is ILD, which shows an increase at the end of the measured region of the well.

Suggested Citation

  • Koohi Lai, Z. & Jafari, G.R., 2013. "Non-Gaussianity effects in petrophysical quantities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5132-5137.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:20:p:5132-5137
    DOI: 10.1016/j.physa.2013.06.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437113005293
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2013.06.031?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bacry, E. & Delour, J. & Muzy, J.F., 2001. "Modelling financial time series using multifractal random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 84-92.
    2. King, Peter R. & Jr., José S.Andrade & Buldyrev, Sergey V. & Dokholyan, Nikolay & Lee, Youngki & Havlin, Shlomo & Stanley, H.Eugene, 1999. "Predicting oil recovery using percolation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 266(1), pages 107-114.
    3. Ferreira, R.B. & Vieira, V.M. & Gleria, Iram & Lyra, M.L., 2009. "Correlation and complexity analysis of well logs via Lyapunov, Hurst, Lempel–Ziv and neural network algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 747-754.
    4. G. R. Jafari & M. Sadegh Movahed & P. Noroozzadeh & A. Bahraminasab & Muhammad Sahimi & F. Ghasemi & M. Reza Rahimi Tabar, 2007. "Uncertainty in the Fluctuations of the Price of Stocks," Papers 0706.1460, arXiv.org.
    5. Corso, G. & Kuhn, P.S. & Lucena, L.S. & Thomé, Z.D., 2003. "Seismic ground roll time–frequency filtering using the gaussian wavelet transform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 318(3), pages 551-561.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Reza Hosseini & Samin Tajik & Zahra Koohi Lai & Tayeb Jamali & Emmanuel Haven & G. Reza Jafari, 2022. "Quantum Bohmian Inspired Potential to Model Non-Gaussian Events and the Application in Financial Markets," Papers 2204.11203, arXiv.org.
    2. Ganjeh-Ghazvini, Mostafa & Masihi, Mohsen & Ghaedi, Mojtaba, 2014. "Random walk–percolation-based modeling of two-phase flow in porous media: Breakthrough time and net to gross ratio estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 214-221.
    3. Marinho, E.B.S. & Sousa, A.M.Y.R. & Andrade, R.F.S., 2013. "Using Detrended Cross-Correlation Analysis in geophysical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2195-2201.
    4. Christian M. Hafner, 2012. "Cross-correlating wavelet coefficients with applications to high-frequency financial time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1363-1379, December.
    5. Sadeghnejad, S. & Masihi, M. & King, P.R., 2013. "Dependency of percolation critical exponents on the exponent of power law size distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6189-6197.
    6. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
    7. Chen, Wang & Wei, Yu & Lang, Qiaoqi & Lin, Yu & Liu, Maojuan, 2014. "Financial market volatility and contagion effect: A copula–multifractal volatility approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 398(C), pages 289-300.
    8. Lee, Chung Kung & Chin Yu, Chung & Cai Wang, Cheng & Der Hwang, Ruey & Kuen Yu, Guey, 2006. "Scaling characteristics in aftershock sequence of earthquake," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 692-702.
    9. Leonid A Safonov & Yoshikazu Isomura & Siu Kang & Zbigniew R Struzik & Tomoki Fukai & Hideyuki Câteau, 2010. "Near Scale-Free Dynamics in Neural Population Activity of Waking/Sleeping Rats Revealed by Multiscale Analysis," PLOS ONE, Public Library of Science, vol. 5(9), pages 1-11, September.
    10. Wei, Kun & Zhang, Youxin & Luo, Yi, 2018. "Variance-mediated multifractal analysis of group participation in chasing a single dangerous prey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 1275-1287.
    11. Makowiec, Danuta & Gała¸ska, Rafał & Dudkowska, Aleksandra & Rynkiewicz, Andrzej & Zwierz, Marcin, 2006. "Long-range dependencies in heart rate signals—revisited," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 632-644.
    12. Xavier Brouty & Matthieu Garcin, 2023. "Fractal properties, information theory, and market efficiency," Papers 2306.13371, arXiv.org.
    13. Ho, Ding-Shun & Lee, Chung-Kung & Wang, Cheng-Cai & Chuang, Mang, 2004. "Scaling characteristics in the Taiwan stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 332(C), pages 448-460.
    14. Rossitsa Yalamova, 2012. "Fractal Measures in Market Microstructure Research," Multinational Finance Journal, Multinational Finance Journal, vol. 16(1-2), pages 137-154, March - J.
    15. Li, Muyi & Huang, Yongxiang, 2014. "Hilbert–Huang Transform based multifractal analysis of China stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 222-229.
    16. Rypdal, Martin & Sirnes, Espen & Løvsletten, Ola & Rypdal, Kristoffer, 2013. "Assessing market uncertainty by means of a time-varying intermittency parameter for asset price fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3335-3343.
    17. Stalgorova, Ekaterina & Babadagli, Tayfun, 2014. "Scaling of production data obtained from Random Walk Particle Tracking simulations in highly fractured porous media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 181-192.
    18. Wu, Peng & Muzy, Jean-François & Bacry, Emmanuel, 2022. "From rough to multifractal volatility: The log S-fBM model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    19. Hosseinabadi, S. & Abrinaei, F. & Shirazi, M., 2017. "Statistical and fractal features of nanocrystalline AZO thin films," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 11-22.
    20. Lee, Hojin & Chang, Woojin, 2015. "Multifractal regime detecting method for financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 70(C), pages 117-129.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:392:y:2013:i:20:p:5132-5137. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.