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Study on forward and inversion modeling of array laterolog logging in a horizontal/highly deviated well

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Electric feld synthesis was carried out using the multi-feld superposition method according to the working principle of the array laterolog electrode system. The feld distribution of each subfeld was simulated with the 3D finite element method, and the laterolog response of the array was obtained using the linear superposition principle of electric feld. The detection depth and thin layer response at diferent angles of the array laterolog were analyzed. The forward response calculation shows that the radial detection depth of the array laterolog is smaller than the deep laterolog detection depth. When the inclination angle of the well is less than 15°, the logging response of the array laterolog is less afected by the well inclination, and the well inclination correction need not be performed. The logging response values of highly deviated wells with inclination angles exceeding 60° and horizontal wells are quite diferent from those of vertical wells; thus, well deviation correction must be performed. To improve the stability of array laterolog logging inversion using the accurate forward response, a Newton–singular value decomposition method based on particle swarm optimization is proposed to realize inversion of array laterolog logging, and the stability and reliability of logging inversion are greatly improved. Thus, application of the theoretical model and actual data processing and analysis show that the proposed method can efectively and accurately eliminate the infuence of a complex logging environment and obtain real formation parameters.
Czasopismo
Rocznik
Strony
1307--1318
Opis fizyczny
Bibliogr. 28 poz.
Twórcy
autor
  • College of Energy Resources, Chengdu University of Technology, Chengdu 610059, People’s Republic of China
autor
  • China Radio Wave Research Institute, Xinxiang 453003, Henan, People’s Republic of China
autor
  • CNOOC (China) Co., Ltd. Zhanjiang Branch, Zhanjiang 524000, Guangdong, People’s Republic of China
autor
  • Institute of Sedimentary Geology, Chengdu University of Technology, Chengdu 610059, People’s Republic of China
Bibliografia
  • 1. Abordán A, Szabó NP (2018) Particle swarm optimization assisted factor analysis for shale volume estimation in groundwater formations. Geosci Eng 6(9):85–95
  • 2. Avdeev DB (2005) Three-dimensional electromagnetic modelling and inversion from theory to application. Surv Geophys 26(6):767–799
  • 3. Biswas A, Dasgupta S, Das S, Abraham A (2007) Synergy of PSO and bacterial foraging optimization—a comparative study on numerical benchmarks. Adv Soft Comput 44:255–263
  • 4. Chauhan P, Deep K, Pant M (2013) Novel inertia weight strategies for particle swarm optimization. Memet Comput 5(3):229–251
  • 5. Chen H, Deng S, Li Z, Fan Y (2007) The PSO (particle swarm optimization) method for dual-lateral log inversion. Geophys Geochem Explor 31(Supp):29–31
  • 6. Clavier C (1991) The challenge of logging horizontal wells. Log Analyst 32(2):63–84
  • 7. Datta-Gupta A, Lake LW, Pope GA (1995) Characterizing heterogeneous permeable media with spatial statistics and tracer data using sequential simulated annealing. Math Geol 27(6):763–787
  • 8. Davydycheva S, Druskin V, Habashy T (2003) An efficient finite-difference scheme for electromagnetic logging in 3D anisotropic inhomogeneous media. Geophysics 68(5):1525–1536
  • 9. Deng S, Li G, Fan Y, Zhang X, Dai S (2005) Preprocessing method of dual laterolog data in the low-resistivity reservoir. Well Logging Technol 29(3):220–222
  • 10. Deng S, Li L, Li Z, He X, Fan Y (2015) Numerical simulation of high-resolution azimuthal resistivity laterolog response in fractured reservoirs. Pet Sci 12(2):252–263
  • 11. Ding Z, Yang C, Tao H, Deng G, Chen G, Ma E (2002) Physical restriction on model selection of neural network in dual-lateral log inversion. Prog Geophys 17(2):331–336
  • 12. Li D (1980) Finite element method in the application of the electrical logging. Petroleum industry press, Beijing, pp 72–129
  • 13. Li S (1998) Inverting fracture porosity and dip of limestone fractured reservoir using 3-D FEM. Well Log Technol 22(6):412–415
  • 14. Li S, Xiao C, Wang H, Zhang G (1996) Mathematical model of dual laterolog response to fracture and quantitative interpretation of fracture porosity. Acta Geophys Sinica 39(6):845–852
  • 15. Li Z, Fan Y, Deng S, Ji X (2010) Inversion of array laterolog by improved difference evolution. J Jilin Univ Earth Sci Edit 40(5):1199–1204
  • 16. Liu Z, Hu Q, Zhang J (1994) Calculating intrusion by the finite element method under the condition of dual laterolog tool response. Pet Instrum 8(3):149–152
  • 17. Liu F, Li S, Zhang G (1997) Computation of borehole correction curves of dual laterolog tool by integral equation method. Acta Geophys Sinica 40(6):857–866
  • 18. Mohammadi M, Montazeri M, Abasi S (2017) Bacterial graphical user interface oriented by particle swarm optimization strategy for optimization of multiple type DFACTS for power quality enhancement in distribution system. J Cent South Univ 24(3):569–588
  • 19. Sewell P, Noroozi S, Vinney J, Amali R, Andrews S (2010) Improvements in the accuracy of an inverse problem engine’s output for the prediction of below-knee prosthetic socket interfacial loads. Eng Appl Artif Intell 23(6):1000–1011
  • 20. Sibbit AM, Faivre O (1985) The dual laterolog response in fractured rocks[C]. In: SPWLA 26th annual logging symposium, Dallas, Texas, 17–20
  • 21. Smits J, Dubourg I, Luling M (1998) Improved resistivity interpretation utilizing a new array laterolog tool and associated inversion processing. SPE 49328:831–842
  • 22. Tan Y, Wang J (2005) Calculate the geophysical inverse problems using genetic algorithm. Chin J Eng Math 22(3):427–434
  • 23. Tan M, Gao J, Wang X, Zhang S (2011) Numerical simulation of the dual laterolog for carbonate cave reservoirs and response characteristics. Appl Geophys 8(1):79–85
  • 24. Zhang G (1996) Electrical logging. University of Petroleum Press, Dongying
  • 25. Zhang L, Tang Y, Hua C, Guan X (2015) A new particle swarm optimization algorithm with adaptive inertia weight based on Bayesian techniques. Appl Soft Comput 28:138–149
  • 26. Zhu D, Deng S, Fan Y, Wang X (2005) Numerical simulation of dual laterolog response in highly deviated wells. Well Log Technol 29(3):208–211
  • 27. Zhu P, Lin C, Li Z, Zhao W, Zhang H (2015) Numerical simulation of array laterolog response in horizontal and highly deviated wells. J Jilin Univ 45(6):1862–1869
  • 28. Ziari I, Jalilian A (2012) Optimal placement and sizing of multiple aplcs using a modified discrete PSO. Int J Electr Power Energy Syst 43(1):630–639
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fede2e62-2b52-4fe2-aabb-ea2f0422bda7
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