A hybrid GIS-assisted framework to integrate Dempster–Shafer theory of evidence and fuzzy sets in risk analysis: an application in hydrocarbon exploration

References

• Agterberg FP. 2011. A modified weights-of-evidence method for regional mineral resource estimation. Nat Resour Res. 20(2):95–101.
   Google Scholar
• Althuwaynee OF, Pradhan B, Park HJ, Lee JH. 2014. A novel ensemble bivariate statistical evidential belief function with knowledge based analytical hierarchy process and multivariate statistical logistic regression for landslide susceptibility mapping. Catena. 114:21–36.
   Web of Science ®Google Scholar
• Amiri MA, Karimi M, Alimohammadi A. 2015. Hydrocarbon resource potential mapping using the evidential belief functions and GIS, Ahvaz/Khuzestan province, southwest Iran. Arab J Geosci. 8:3929–3941.
   Web of Science ®Google Scholar
• Armas L. 2012. Weight of evidence method for landslide susceptibility mapping, Romania. J Nat Hazard. 60:937–950.
   Web of Science ®Google Scholar
• Baudrit C, Couso I, Dubois D. 2007. Joint propagation of probability and possibility in risk analysis: towards a formal framework. Int J Approx Reason. 45(1):82–105.
   Web of Science ®Google Scholar
• Biswajeet P, Saro L, Manfred FB. 2009. Use of geospatial data and fuzzy algebraic operators to landslide-hazard mapping. Appl Geomat. 1:3–15.
   Google Scholar
• Bonham-Carter G. 1994. Geographic information systems for geoscientists: modelling with GIS. Oxford: Pergamon Press.
   Google Scholar
• Bordenave M. 2014. Petroleum systems and distribution of the oil and gas fields in the Iranian part of the Tethyan region. In AAPG Special Volumes, Memoir 106: Petroleum Systems of the Tethyan Region. American Association of Petroleum Geologists; p. 505–540.
   Google Scholar
• Burrough PA, McDonnell R. 2015. Principles of geographical information systems. 3rd ed. Oxford: Oxford University Press.
   Google Scholar
• Carranza EJM. 2009. Controls on mineral deposit occurrence inferred from analysis of their spatial pattern and spatial association with geological features. Ore Geol Rev. 35(3-4):383–400.
   Web of Science ®Google Scholar
• Carranza EJM. 2015. Data-driven evidential belief modeling of mineral potential using few prospects and evidence with missing values. Nat Resour Res. 24(3):291–304.
   Web of Science ®Google Scholar
• Carranza EJM, Hale M. 2003. Evidential belief functions for data-driven geologically constrained mapping of gold potential, Baguio district, Philippines. Ore Geol Rev. 22(1-2):117–132.
   Web of Science ®Google Scholar
• Carranza EJM, Van Ruitenbeek F, Hecker C, Van der Meijde M, Van der Meer F. 2008. Knowledge-guided data-driven evidential belief modelling of mineral prospectivity in Cabo de Gata, SE Spain. Int J Appl Earth Observ Geoinform. 10(3):374–387.
   Web of Science ®Google Scholar
• Chen W, Pourghasemi HR, Zhao ZH. 2017. A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial nueral network model for landslide susceptibility mapping. J Geocarto Int. 32(4):367–385.
   Web of Science ®Google Scholar
• Dempster AP. 1967. Upper and lower probabilities induced by a multivalued mapping. Ann Math Statist. 38(2):325–339.
   Google Scholar
• Egenhofer MJ, Franzosa RD. 1991. Point-Set Topological Spatial Relations. Int J Geogr Inf Syst. 5(2):161–174.
   Google Scholar
• Ford A, Miller JM, Mol AG. 2016. A comparative analysis of weights of evidence, evidential belief functions, and fuzzy logic for mineral potential mapping using incomplete data at the scale of investigation. Nat Resour Res. 25(1):19–33.
   Web of Science ®Google Scholar
• Hong H, Naghibi SA, Dashtpagerdi MM, Pourghasemi HR, Chen W. 2017a. A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China. Arab J Geosci. 10:167.
   Web of Science ®Google Scholar
• Hong H, Ilia I, Tsangaratos P, Chen W, Xu C. 2017b. A hybrid fuzzy weight of evidence method in landslide susceptibility analysis on the Wuyuan area, China. J Geomorphol. 290:1–16.
   Google Scholar
• Jamshidi P, Sharifloo A, Pahl C, Arabnejad H, Metzger A, Estrada G. 2016. Fuzzy self-learning controllers for elasticity management in dynamic cloud architectures, IEEE, 2016 12th International ACM SIGSOFT Conference on Quality of Software Architectures.
   Google Scholar
• Kiureghian A, Ditlevsen O. 2009. Aleatory or epistemic? Does it matter? Struct Saf. 31(2):105–112.
   Web of Science ®Google Scholar
• Leturmy P, Robin C. 2010. Tectonic and stratigraphic evolution of Zagros and Makran during the Mesozoic-Cenozoic: introduction. Geol Soc Lond Spec Publ. 330(1):1–4.
   Google Scholar
• Lusty PAJ, Scheib C, Gunn AG, Walker ASD. 2012. Reconnaissance-scale prospectivity analysis for gold mineralization in the southern Uplands-Down-Longford Terrane, Northern Ireland. Nat Resour Res. 21(3):359–382.
   Google Scholar
• Magoon LB, Dow WG. 1994. The petroleum system: from source to trap. Memoir 60. Houston: American Association of Hydrocarbon Geologists, p. 1–25.
   Google Scholar
• Motamedi H, Sherkati S, Sepehr M. 2012. Structural style variation and its impact on hydrocarbon traps in central Fars, southern Zagros folded belt, Iran. J Struct Geol. 37:124–133.
   Web of Science ®Google Scholar
• Mousavi SR. 2012. Dempster-Shafer Theory and modified rules to determine uncertainty in mineral prospection, PhD Thesis. TU Clausthal Institute.
   Google Scholar
• Nikravesh M. 2005. DSS and information systems in enterprise: evolutionary computing-based optimization multi aggregator fuzzy decision trees, IEEE International conference on Man and cybernetics.
   Google Scholar
• Nykanen V, Groves DI, Ojala VJ, Eilu P, Gardoll SJ. 2008. Reconnaissance-scale conceptual fuzzy-logic prospectivity modelling for iron oxide copper-gold deposits in the northern Fennoscandian Shield, Finland. Aust J Earth Sci. 55:25–38.
   Web of Science ®Google Scholar
• Park NW. 2011. Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis. J Environ Earth Sci. 62(2):367–376.
   Web of Science ®Google Scholar
• Piryaei A, Reijmer JJG, Borgomano J, van Buchem FSP. 2011. Late cretaceous tectonic and sedimentary evolution of the Bandar Abbas area, Fars region, southern Iran. J Pet Geol. 34:157–180.
   Web of Science ®Google Scholar
• Remondo J, González A, De Terán JRD, Cendrero A, Fabbri A, Chung C-JF. 2004. Validation of landslide susceptibility maps: example and applications from a case study in Northern Spain. Nat Hazards. 30(3):437–449.
   Web of Science ®Google Scholar
• Rose PR. 2000. Risk analysis and management of petroleum exploration ventures. AAPG methods in exploration series, No.12. American Association of Petroleum Geologists ISBN: 978-1-58861-444-5.
   Google Scholar
• Royal Dutch Shell. 2014. Play based exploration. A guide for AAPG’s Imperial Barrel Award Participation. Rijswijk: Royal Dutch Shell.
   Google Scholar
• Seraj S, Delavar MR. 2018a. An extended GIS-based Dempster-Shafer theory for play-based hydrocarbon exploration risk analysis under spatial uncertainty conditions, case study: Zagros Sedimentary Basin, Iran. Georisk. 13:131–144.
   Google Scholar
• Seraj S, Delavar MR. 2018b. Play-based hydrocarbon exploration under spatial uncertainty using evidential theory, ISPRS annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-4, ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change”, Delft, The Netherlands,
   Google Scholar
• Shafer G. 1976. A mathematical theory of evidence, 1. Princeton: Princeton University Press
   Google Scholar
• Shokouh Saljoughi B, Hezarkhani A. 2018. A comparative analysis of artificial neural network (ANN), wavelet neural network (WNN), and support vector machine (SVM) data-driven models to mineral potential mapping for copper mineralizations in the Shahr-e-Babak region, Kerman, Iran. Appl Geomat. 10(3):229–256.
   Web of Science ®Google Scholar
• Su X, Mahadevan S, Han W, Deng Y. 2016. Combining dependent bodies of evidence. Appl Intell. 44(3):634–644.
   Web of Science ®Google Scholar
• Tangestani MH. 2009. A comparative study of Dempster–Shafer and fuzzy models for landslide susceptibility mapping using a GIS: an experience from Zagros Mountains, SW Iran. J Asian Earth Sci. 35(1):66–73.
   Web of Science ®Google Scholar
• Tavakoli-Shirazi S, Frizon de Lamotte D, Wrobel-Daveau J-C, Ringenbach J-C. 2013. Pre-Permian uplift and diffuse extensional deformation in the High Zagros Belt (Iran), integration in the geodynamic evolution of the Arabian plate. Arab J Geosci. 6(7):2329–2342.
   Web of Science ®Google Scholar
• Tien Bui D, Pradhan B, Lofman O, Revhaug I, Dick OB. 2012. Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): a comparative assessment of the efficacy of evidential belief functions and fuzzy logic models. Catena. 96:28–40.
   Web of Science ®Google Scholar
• Tobler W. 1970. A computer movie simulating urban growth in the Detroit Region. Econ Geol. 4:234–240.
   Google Scholar
• Tsoukalas LH, Uhrig RE. 1997. Fuzzy and neural approaches in engineering. New York: Wiley.
   Google Scholar
• Xiong Y, Zuo R. 2018. GIS-based rare events logistic regression for mineral prospectivity mapping. Comput Geosci. 111:18–25.
   Web of Science ®Google Scholar
• Zadeh LA. 1965. Fuzzy sets. Inf Control J. 8(3):338–353.
   Google Scholar
• Zhou D, Tang Y, Jiang W. 2016. A modified model of failure mode and effects analysis based on generalized evidence theory. Math Probl Eng. 2016.
   Web of Science ®Google Scholar
• Ziyong Z, Hangyu Y, Xiaodan G. 2018. Fuzzy fusion of geological and geophysical data for mapping hydrocarbon potential based on GIS. Pet Geosci. 24(1):131–141.
   Web of Science ®Google Scholar