1887
  1. Home
  2. Conferences
  3. Conference Proceedings
  4. Fifth EAGE Conference on Petroleum Geostatistics
  5. Conference paper

Abstract

Summary

In this study, a new approach was introduced to enhance the accuracy of Total Organic Carbon (TOC) prediction. The modification involved the application of Simulated Annealing (SA), an optimization technique inspired by physical annealing processes, to the non-linear estimation method known as Icl-BS. The Icl-BS technique, initially proposed by Bibor and Szabo in 2016, aimed to establish a linear regression relationship between TOC content and parameter Δd, computed using the Clay Indicator Method (Icl) developed by Zhao et al. in 2016.

The modified method referred to as Icl-BS-SA, demonstrated remarkable improvements over traditional approaches. Comparisons were made against the conventional linear regression-based Icl method and the nonlinear regression-based Icl-BS technique using the Levenberg-Marquardt (LM) algorithm. The results indicated that the Icl-BS-SA method outperformed these approaches in terms of both accuracy and parameter estimation.

By incorporating the SA technique, the Icl-BS-SA method achieved significantly enhanced outcomes, showcased through reduced relative data distance and Root Mean Square Error (RMSE). This innovative approach holds promise for advancing TOC prediction accuracy, making it a noteworthy contribution to the field.

© EAGE Publications BV
Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.202335010
2023-11-27
2025-04-26

  • From This Site

    /content/papers/10.3997/2214-4609.202335010
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Bibor, I., and Szabó, N. P., 2016. Unconventional shale characterization using improved well logging methods.Geosciences and Engineering.5. 32–50.
     [Google Scholar]
  2. Henderson, D., Jacobson, S., Johnson, A., 2006. The Theory and Practice of Simulated Annealing, in: Handbook of Metaheuristics. pp. 287–319. https://doi.org/10.1007/0-306-48056-5_10
     [Google Scholar]
  3. Mao, Z.-Q., 2001. The Physical Dependence and The Correlation Characteristics Of Density And Neutron Logs.Petrophysics42
     [Google Scholar]
  4. Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E., 1953. Equation of State Calculations by Fast Computing Machines.J. Chem. Phys.21, 1087–1092. https://doi.org/10.1063/1.1699114
     [Google Scholar]
  5. Norwegian Petroleum Directorate (2023, July 1st). FactPages: Wellbore.
     [Google Scholar]
  6. Passey, Q. R., Bohacs, K., Esch, W. L., Klimentidis, R., Sinha, S. (2010). Geologic and Petrophysical Characterization of Unconventional Shale Gas Reservoirs.International Oil and Gas Conference and Exhibition, 8–10 June, Beijing, China.
     [Google Scholar]
  7. Passey, Q.R., Creaney, S. and Kulla, J.B. (1990) A Practical Model for Organic Richness from Porosity and Resistivity Logs.AAPG Bulletin, 74, 1777–1794. https://doi.org/10.1306/0C9B25C9-1710-11D7-8645000102C1865D
     [Google Scholar]
  8. Passey, Q.R., Creaney, S., Kulla, J.B., Moretti, F., and Stroud, J.D. (1990). A Practical Model for Organic Richness from Porosity and Resistivity Logs.
     [Google Scholar]
  9. Schmoker, J. W. (1979). Determination of Organic Content of Appalachian Devonian Shales from Formation-Density Logs: AAPG Bulletin, 63(9), pp. 1504–1509.
     [Google Scholar]
  10. Szabó, N. P., Dobróka, M. (2020). Interval inversion as innovative well log interpretation tool for evaluating organic-rich shale formations.Journal of Petroleum Science and Engi-neering, Vol. 186.
     [Google Scholar]
  11. Szabó, N.P., Remeczki, F., Jobbik, A., Kiss, K., Dobróka, M., 2022. Interval inversion based well log analysis assisted by petrophysical laboratory measurements for evaluating tight gas formations in Derecske through, Pannonian basin, east Hungary.Journal of Petroleum Science and Engineering208, 109607. https://doi.org/10.1016/j.petrol.2021.109607
     [Google Scholar]
  12. Zee Ma, Y. (2016). Chapter 1—Unconventional Resources from Exploration to Produc-tion. In Y. Z.Ma, S. A.Holditch (Eds.), Unconventional Oil and Gas Resources Hand-book (pp. 3–52). Gulf Professional Publishing.
     [Google Scholar]
  13. Zhao, P., Mao, Z., Huang, Z., Zhang, C., 2016. A new method for estimating total organic carbon content from well logs.AAPG Bulletin100, 1311–1327. https://doi.org/10.1306/02221615104
     [Google Scholar]
/content/papers/10.3997/2214-4609.202335010
Loading
Improving Toc Estimation Accuracy Using Simulated Annealing Algorithm: a Data Science Approach
Conference Proceedings 2023, 1 (2023); https://doi.org/10.3997/2214-4609.202335010
/content/papers/10.3997/2214-4609.202335010
/content/papers/10.3997/2214-4609.202335010
Loading

Data & Media loading...

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error