PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
  • Sesja wygasła!
Tytuł artykułu

Cooperative fuzzy-guided focused inversion for unstructured mesh modeling of potential feld geophysics, a case study for imaging an oil trapping structure

Autorzy
Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This work illustrates the application of a fuzzy-guided focused technique for cooperative 2D modeling of magnetic and gravity data on common geological sources responsible for anomalous observation, whereby a well-known fuzzy c-means clustering tool is inserted in the center of the inversion mechanism to search different clusters of geophysical properties which are magnetic susceptibility and density contrast within several zones. An unstructured meshing is performed with triangular cells which captures the accurate borders of a rugged topography area and any complex-shaped sought sources. The efficiency of the proposed cooperative inversion algorithm is examined along 2D profiles with simulation of several synthetic sources by which the retrieved geophysical properties indicate sharp edges, correct depth and shape pattern of the sought sources. Imposing a model stabilizer, a depth weighting function and petrophysics constraints of physical models within the clustering inversion, greatly promotes the performance of the constructed models over the outputs of running individually each data set. Of note is that a conjugate gradient solver is utilized here with a preconditioner to estimate approximately sought physical properties from an objective function with two constituents that are a model and a misfit norm. Ground-based gravity and magnetic observations over a plausible oil-trapping structure are investigated at the Kif region, situated in Iraq. Cooperative inversion output can pave the way for imaging of a fault feature which has been filled by a thick sequence of sediments, presenting a configuration of a graben-horst structure. The main notable output of this work proves the existence of an oil-trapping structure responsible for a distinct potential field geophysics anomaly.
Czasopismo
Rocznik
Strony
2077--2098
Opis fizyczny
Bibliogr. 111 poz.
Twórcy
autor
  • Petroleum Exploration and Geophysics Lab (PEGLUT), College of Engineering, School of Mining Engineering, University of Tehran, Tehran, Iran
Bibliografia
  • 1. Abedi M (2020) A focused and constrained 2D inversion of potential field geophysical data through Delaunay triangulation, a case study for iron-bearing targeting at the Shavaz deposit in Iran. Phys Earth Planet Inter. https://doi.org/10.1016/j.pepi.2020.106604
  • 2. Abedi M, Gholami A, Norouzi GH (2014) 3D inversion of magnetic data seeking sharp boundaries: a case study for a porphyry copper deposit from now Chun in Central Iran. Near Surf Geophys 2:657–666
  • 3. Al-Ameri TK, Pitman J, Naser EN, Zumberge J, Al-Haydari HA (2010) Programed oil generation of the Zubair formation, southern Iraq oil fields: results from Petromod software modeling and geochemical analysis. Arab J Geosci. https://doi.org/10.1007/s12517-010-0160-z
  • 4. Al-Banna A (1992) Gravity lineaments, fault trends and depth of the basement rocks in Western Desert. Iraqi J Sci 33:63–79
  • 5. Al-Farhan M, Oskooi B, Ardestani VE, Abedi M, Al-Khalidy A (2019) Magnetic and gravity signatures of the Kifl oil field in Iraq. J Petrol Sci Eng 183:106397
  • 6. Al-Kubaisi MS, Al-Jarah OB, Abdul-Jabbar AA (2014) Neotectonics of Al-Thirthar, Al-Habbaniya, Al-Razzazah depressions, central Iraq, by using remote sensing data. Iraqi J Sci 55(2B):790–801
  • 7. Al-Sayyab A (1989) Geology of petroleum. University of Baghdad Press, Baghdad: 472
  • 8. Aster RC, Borchers B, Thurber C (2003) Parameter estimation and inverse problems. Academic Press, New York, NY
  • 9. Bank RE (1990) PLTMG: A software package for solving elliptic partial differential equations, User’s Guide 6.0. Society for Industrial and Applied Mathematics, Philadelphia, PA
  • 10. Bellen RC, Van Dunnington HV, Wetzel R, Morton DM (1959) Lexique stratigraphquie international. Asie, Fasicule 10a Iraq. Centre National de la Recherche Scientifique, Paris, III: pp 333
  • 11. Beltrão JF, Silva JBC, Costa JC (1991) Robust polynomial fitting method for regional gravity estimation. Geophysics 56(1):80–89
  • 12. Bertete-Aguirre H, Cherkaev E, Oristaglio M (2002) Non-smooth gravity problem with total variation penalization functional. Geophys J Int 149:499–507
  • 13. Bezdek JC (1981) Pattern recognition with fuzzy objective function algorithms. Plenum Press
  • 14. Biswas A (2017) Inversion of source parameters from magnetic anomalies for mineral/ore deposits exploration using global optimization technique and analysis of uncertainty. Nat Resour Res 27:77–107
  • 15. Biswas A (2020) Interpretation of gravity anomaly over 2D vertical and horizontal thin sheet with finite length and width. Acta Geophys. https://doi.org/10.1007/s11600-020-00464-7
  • 16. Blakely RJ (1995) Potential theory in gravity and magnetic applications. Cambridge University Press
  • 17. Botev Z, Grotowski J, Kroese D (2010) Kernel density estimation via diffusion. Ann Stat 38:2916–2957
  • 18. Buday T (1980) The regional geology of Iraq, stratigraphy and palaeogeography. State Organization for Minerals, Baghdad, Iraq, p 455
  • 19. Calcagno P, Chilès JP, Courrioux G, Guillen A (2008) Geological modelling from field data and geological knowledge: part I. Modelling method coupling 3D potential-field interpolation and geological rules. Phys Earth Planet Inter 171:147–157
  • 20. Carter-McAuslan A, Lelièvre PG, Farquharson CG (2015) A study of fuzzy c-means coupling for joint inversion, using seismic tomography and gravity data test scenarios. Geophysics 80(1):W1–W15
  • 21. Cella F, Fedi M (2012) Inversion of potential field data using the structural index as weighting function rate decay. Geophys Prospect 60(2):313–336
  • 22. Cockett R, Kang S, Heagy LJ, Pidlisecky A, Oldenburg DW (2015) SimPEG: an open source framework for simulation and gradient based parameter estimation in geophysical applications. Comput Geosci 85:142–154
  • 23. Cuma M, Wilson GA, Zhdanov M (2012) Large-scale 3D inversion of potential field data. Geophys Prospect 60(6):1186–2119
  • 24. Darijani M, Farquharson CG, Lelievre P (2020) Clustering and constrained inversion of seismic refraction and gravity data for overburden stripping: application to uranium exploration in the Athabasca Basin, Canada. Geophysics 85(4):B133–B146
  • 25. Demirci İ, Erdoğan E, Candansayar ME (2012) Two-dimensional inversion of direct current resistivity data incorporating topography by using finite difference techniques with triangle cells: investigation of Kera fault zone in western Crete. Geophysics 77(1):E67–E75
  • 26. Duda RO, Hart PE, Stork DG (2000) Pattern classification, 2nd ed. Interscience, Wiley
  • 27. Essa KhS, Elhussein M (2019) Magnetic interpretation utilizing a new inverse algorithm for assessing the parameters of buried inclined dike-like geological structure. Acta Geophys 67:533–544
  • 28. Essa KhS, Géraud Y (2020) Parameters estimation from the gravity anomaly caused by the two-dimensional horizontal thin sheet applying the global particle swarm algorithm. J Petrol Sci Eng 193:107421
  • 29. Fadhel MS, Al-Rahim AM (2019a) A new tectono sedimentary framework of the Jurassic succession in the Merjan oil field, Central Iraq. J Pet Explor Prod Technol 9:2591–2603
  • 30. Fadhel MS, Al-Rahim AM (2019b) 3D seismic model of faulting systems of a Jurassic-Cretaceous sedimentary packages in Merjan_West Kifl oil fields-Central Iraq. Heliyon 5:e02507
  • 31. Farquharson CG (2008) Constructing piecewise-constant models in multidimensional minimum-structure inversions. Geophysics 73:K1–K9
  • 32. Farquharson CG, Ash M, Miller H (2008) Geologically constrained gravity inversion for the Voisey’s Bay ovoid deposit. Lead Edge 27:64–69
  • 33. Fouad SFA (2010) Tectonic and structural evolution of the Mesopotamia foredeep, Iraq. Iraqi Bull Geol Min 6:41–53
  • 34. Fullagar PK, Hughes NA, Paine J (2000) Drilling-constrained 3D gravity interpretation. Explor Geophys 31(2):17–23
  • 35. Gallardo LA, Meju MA (2004) Joint two-dimensional DC resistivity and seismic travel time inversion with cross-gradients constraints. J Geophys Res Solid Earth 109(B3):1–11
  • 36. Gallardo LA, Meju MA (2007) Joint two-dimensional crossgradient imaging of magnetotelluric and seismic travel-time data for structural and lithological classification. Geophys J Int 169:1261–1272
  • 37. Galley CG, Lelièvre PG, Farquharson CG (2020) Geophysical inversion for 3D contact surface geometry. Geophysics 85:K27–K45
  • 38. Galley C, Lelievre P, Haroon A, Graber S, Jamieson JW, Szitkar F, Yeo I, Farquharson C, Petersen S, Evans R (2021) Magnetic and gravity surface geometry inverse modelling of the TAG active mound. Earth Space Sci Open Archive. https://doi.org/10.1002/essoar.10506959.1
  • 39. Gholami A, Siahkoohi HR (2009) Simultaneous constraining of model and data smoothness for regularization of geophysical inverse problems. Geophys J Int 176:151–163
  • 40. Guillen A, Calcagno Ph, Courrioux G, Joly A, Ledru P (2008) Geological modelling from field data and geological knowledge Part II. Modelling validation using gravity and magnetic data inversion. Phys Earth Planet Inter 171:158–169
  • 41. Gundogdu NY, Candansayar E (2018) Three-dimensional regularized inversion of DC resistivity data with different stabilizing functionals. Geophysics 83(6):E399–E407
  • 42. Harris B, Pethick A, Schaa R, Cuong LVA (2018) Cooperative inversion: a review. ASEG Ext Abstr 2018:1–3. https://doi.org/10.1071/ASEG2018abM1_1F
  • 43. Hathaway RJ, Bezdek JC (2001) Fuzzy c-means clustering of incomplete data. IEEE Trans Syst Man Cybern B Cybern 31:735–744
  • 44. Hathaway RJ, Bezdek C, Hu Y (2000) Generalized fuzzy c-means clustering strategies using Lp norm distances. IEEE Transact Fuzzy Syst 8(5):576–582
  • 45. Hijab BR, Aldabbas MA (2000) Tectonic evolution of Iraq. Iraqi Geol. J. 32, 26–47. Iraqi Geological Survey and Mine Research Company, 1990. Internal Report of Kifl Oil Field. pp 38
  • 46. Hinze WJ, Frese RRBv, Saad AH (2012) Gravity and magnetic exploration: principles, practices, and applications. Cambridge University Press, p 515
  • 47. Huang XY, Deng JZ, Chen X (2019) Magnetotelluric extremum boundary inversion based on different stabilizers and its application in a high radioactive waste repository site selection. Appl Geophys 16:367–377
  • 48. Jahandari H, Farquharson CG (2015) Finite-volume modelling of geophysical electromagnetic data on unstructured grids using potentials. Geophys J Int 202(3):1859–1876
  • 49. Jahandari H, Ansari SM, Farquharson CG (2017) Comparison between staggered grid finite-volume and edge-based finite-element modelling of geophysical electromagnetic data on unstructured grids. J Appl Geophys 138:185–197
  • 50. Jassim SZ, Goff JC (2006) Geology of Iraq, Czech Republic. 80-7028-287-8, p 341
  • 51. Kieu DT, Kepic A (2020) Seismic-impedance inversion with fuzzy clustering constraints: an example from the Carlin Gold District, Nevada, USA. Geophys Prospect 68:103–128
  • 52. Last BJ, Kubik K (1983) Compact gravity inversion. Geophysics 48:713–721
  • 53. Lelièvre PG, Oldenburg DW (2006) Magnetic forward modeling and inversion for high susceptibility. Geophys J Int 166:76–90
  • 54. Lelièvre PG, Oldenburg DW, Williams N (2009) Integrating geological and geophysical data through advanced constrained inversions. Explor Geophys 40(4):334–341
  • 55. Lelièvre PG, Farquharson CG, Hurich CA (2011) Inversion of first-arrival seismic travel times without rays, implemented on unstructured grids. Geophys J Int 185:749–763
  • 56. Lelièvre PG, Farquharson CG, Hurich CA (2012) Joint inversion of seismic travel times and gravity data on unstructured grids with application to mineral exploration. Geophysics 77(1):K1–K15
  • 57. Lelièvre P, Farquharson C, Bijani R (2015) 3D stochastic geophysical inversion for contact surface geometry. EGU General Assembly, Vienna, pp 12–17
  • 58. Lelièvre PG, Carter-McAuslan AE, Dunham MW, Jones DJ, Nalepa M, Squires CL, Tycholiz CJ, Vallée MA, Farquharson CG (2018) FacetModeller: Software for manual creation, manipulation and analysis of 3D surface-based models. SoftwareX 7:41–46
  • 59. Lelièvre PG (2009) Integrating geologic and geophysical data through advanced constrained inversions. PhD Thesis. University of British Columbia, p 157
  • 60. Li Y, Oldenburg DW (1996) 3D inversion of magnetic data. Geophysics 61:394–408
  • 61. Li Y, Oldenburg DW (1998) 3D inversion of gravity data. Geophysics 63:109–119
  • 62. Li Y, Oldenburg DW (2000) Joint inversion of surface and three-component borehole magnetic data. Geophysics 65:540–552
  • 63. Li Y, Oldenburg DW (2003) Fast inversion of large-scale magnetic data using wavelet transforms and a logarithmic barrier method. Geophys J Int 152:251–265
  • 64. Lines LR, Schultz AK, Treitel S (1988) Cooperative inversion of geophysical data. Geophysics 53:8–20
  • 65. Liu S, Jin S (2020) 3-D Gravity anomaly inversion based on improved guided fuzzy C-means clustering algorithm. Pure Appl Geophys 177:1005–1027
  • 66. Liu S, Hu X, Liu T, Feng J, Gao W, Qiu L (2013) Magnetization vector imaging for borehole magnetic data based on magnitude magnetic anomaly. Geophysics 78:D429–D444
  • 67. Liu S, Hu X, Xi Y, Liu T (2015a) 2D inverse modeling for potential fields on rugged observation surface using constrained Delaunay triangulation. Comput Geosci 76:18–30
  • 68. Liu S, Hu X, Xi Y, Liu T, Xu S (2015b) 2D sequential inversion of total magnitude and total magnetic anomaly data affected by remanent magnetization. Geophysics 80(6):D429–D444
  • 69. Marco Miotti F, Zerilli A, Menezes PTL, Crepaldi JLS, Viana AR (2018) A new petrophysical joint inversion workflow Advancing Reservoir’s Characterization. Chall Interpret 6(3):1–23
  • 70. Meng Z, Li F, Xu X, Huang D, Zhang D (2017) Fast inversion of gravity data using the symmetric successive over-relaxation (SSOR) preconditioned conjugate gradient algorithm. Explor Geophys 48(3):294–304
  • 71. Meng Z, Li F, Xu XC, Zhou W, Hang D (2018) Sparsity constraints using a Laplacian kernel to get geological structures from potential field data. Near Surf Geophys 6:39–52
  • 72. Menke W (1989) Geophysical data analysis: discrete inverse theory. Academic Press, Inc
  • 73. Mollaret C, Wagner FM, Hilbich C, Scapozza C, Hauck C (2020) Petrophysical joint inversion applied to alpine permafrost field sites to image subsurface ice, water, air, and rock contents. Front Earth Sci 8:1–23
  • 74. Mousa A, Mickus K, Al-Rahim A (2017) The thickness of cover sequences in the Western Desert of Iraq from a power spectrum analysis of gravity and magnetic data. J Asian Earth Sci 138:230–245
  • 75. Oldenburg DW, Li Y (1994) Subspace linear inversion methods. Inverse Prob 10:915–935
  • 76. Oldenburg DW, Li Y, Ellis RG (1997) Inversion of geophysical data over a copper gold porphyry deposit: a case history for Mt Milligan. Geophysics 62(5):1419–1431
  • 77. Oldenburg DW, Li Y (2005) Inversion for applied geophysics: a tutorial. In: Butler, DK (Ed.), Near-surface Geophysics: pp 89–150 (SEG)
  • 78. Özyıldırım Ö, Candansayar ME, Demirci İ, Tezkan B (2017) Two-dimensional inversion of magnetotelluric/radiomagnetotelluric data by using unstructured mesh. Geophysics 82(4):E197–E210
  • 79. Paasche H, Tronicke J (2007) Cooperative inversion of 2D geophysical data sets: a zonal approach based on fuzzy c-means cluster analysis. Geophysics 72(3):A35–A39
  • 80. Paasche H, Tronicke J, Holliger K, Green AG, Maurer H (2006) Integration of diverse physical-property models: subsurface zonation and petrophysical parameter estimation based on fuzzy c-means cluster analyses. Geophysics 71(3):H33–H44
  • 81. Paoletti V, Ialongo S, Florio G, Fedi M, Cella F (2013) Self-constrained inversion of potential fields. Geophys J Int 195:854–869
  • 82. Phillips N, Oldenburg DW, Chen J, Li Y, Routh PS (2001) Cost effectiveness of geophysical inversions in mineral exploration: applications at San Nicolas. Lead Edge 20(12):1351–1360
  • 83. Portniaguine O, Zhdanov MS (1999) Focusing geophysical inversion images. Geophysics 64:874–887
  • 84. Portniaguine O, Zhdanov MS (2002) 3D magnetic inversion with data compression and image focusing. Geophysics 67:1532–1541
  • 85. Rao L, Wu X, Guo R, Gao J, Dang B (2020) A comparative study of different stabilizers for retrieving geoelectric structure based on a unified framework. J Appl Geophys 175:104001
  • 86. Ren Z, Tang J, Kalscheuer T, Maurer H (2017) Fast 3-D large-scale gravity and magnetic modeling using unstructured grids and an adaptive multilevel fast multipole method. J Geophys Res Solid Earth 122(1):79–109
  • 87. Rezaie M (2020) A sigmoid stabilizing function for fast sparse 3D inversion of magnetic data. Near Surf Geophys 18(2):149–159
  • 88. Rezaie M, Moradzadeh A, Nejati Kalate A, Aghajani H (2017) Fast 3D focusing inversion of gravity data using reweighted regularized lanczos bidiagonalization method. Pure Appl Geophys 174:359–374
  • 89. Roy KK (2007) Potential theory in applied geophysics. Springer-Verlag, Berlin Heidelberg, New York
  • 90. Schneider J, Bechsta T, Machel HG (2004) Covariance of C- and O-isotopes with magnetic susceptibilities a result of burial diagenesis of sandstones and carbonates: an example from the Lower Devonian La Vid Group, Cantabrian Zone, NW Spain. Int J Earth Sci 93:990–1007
  • 91. Schumacher D (1996) Hydrocarbon-induced alteration of soils and sediments in Hydrocarbon migration and its near surface expression. AAPG Mem 66:71–89
  • 92. Silva FJS, Valéria CF, Barbosa, Silva JBC (2009) 3D gravity inversion through an adaptive-learning procedure. Geophysics 74(3):I9–I21
  • 93. Silva FJS, Valéria CF, Barbosa SJBC (2011) Adaptive learning 3D gravity inversion for salt-body imaging. Geophysics 76(3):I49–I57
  • 94. Singh A (2020) Triangular grid-based fuzzy cross-update inversion of gravity data: case studies from mineral exploration. Nat Resour Res 29:459–471
  • 95. Singh A, Biswas A (2016) Application of global particle swarm optimization for inversion of residual gravity anomalies over geological bodies with idealized geometries. Nat Resour Res 25(3):297–314
  • 96. Singh A, Sharma SP (2018) Identification of different geologic units using fuzzy constrained resistivity tomography. J Appl Geophys 148:127–138
  • 97. Singh A, Mishra PK, Sharma SP (2019) 2D cooperative inversion of direct current resistivity and gravity data: a case study of uranium bearing target rock. Geophys Prospect 67:696–708
  • 98. Sissakian VK, Mohammed BS (2007) Geology of Iraqi western desert. Iraqi Bull Geol Min Spec: Issue 51–124
  • 99. Sun J, Li Y (2014) Adaptive Lp inversion for simultaneous recovery of both blocky and smooth features in a geophysical model. Geophys J Int 197(2):882–899
  • 100. Sun J, Li Y (2015) Multidomain petrophysically constrained inversion and geology differentiation using guided fuzzy c-means clustering. Geophysics 80(4):ID1–ID18
  • 101. Thurston JB, Brows RJ (1992) The filtering characteristics of least-squares polynomial approximation for regional/residual separation. Can J Explor Geophys 28(2):71–80
  • 102. Vatankhah S, Ardestani VE, Renaut RA (2014) Automatic estimation of the regularization parameter in 2D focusing gravity inversion: application of the method to the Safo manganese mine in the northwest of Iran. J Geophys Eng 11:1–11
  • 103. Vatankhah S, Liu S, Renaut RA, Hu X, Hogue JD, Gharloghi M (2020) An efficient alternating algorithm for the Lp-norm cross-gradient joint inversion of gravity and magnetic data using the 2-D fast fourier transform. IEEE Trans Geosci Remote Sens. https://doi.org/10.1109/TGRS.2020.3033043
  • 104. Ward WOC, Wilkinson PB, Chambers JE, Oxby LS, Bai L (2014) Distribution-based fuzzy clustering of electrical resistivity tomography images for interface detection. Geophys J Int 197:310–321
  • 105. Xiang Y, Yu P, Zhang L, Feng S, Utada H (2017) Regularized magnetotelluric inversion based on a minimum support gradient stabilizing functional. Earth Planets Space 69:158
  • 106. Xu Z, Zou G, Wei Q, Tian J, Yuan H (2021) Focusing joint inversion of gravity and magnetic data using a clustering stabilizer in a space of weighted parameters. Geophys J Int 224:1344–1359
  • 107. Yari M, Nabi-Bidhendi M, Ghanati R, Shomali ZH (2021) Hidden layer imaging using joint inversion of P-wave travel-time and electrical resistivity data. Near Surf Geophys 19:297–313
  • 108. Zeeh S, Walter U, Kuhlemann J, Herlec U, Keppens E, Bechstadt T (1997) Carbonate cements as a tool for fluid flow reconstruction a study in parts of the eastern Alps (Austria, Germany, and Slovenia). In: Montanez, I.P., Gregg, J.M., Shelton, K.L. (Eds.), Basin-wide diagenetic patterns: integrated petrologic, geochemical, and hydrologic considerations. SEPM Spec. Publ. 57, pp 167–181
  • 109. Zhang SY, Pan YL (2004) Principle of applied geophysics. China University of Geosciences Press, Wuhan
  • 110. Zhao CJ, Yu P, Zhang LL (2016) A new stabilizing functional to enhance the sharp boundary in potential field regularized inversion. J Appl Geophys 135:356–366
  • 111. Zhdanov MS (2002) Geophysical inverse theory and regularization problems. Elsevier, Amsterdam
Uwagi
PL
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-494f922d-8a16-47bb-af6a-a74e18a18708
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.