Appraisal of Potential Hydrocarbon Zones in Masila Oil Field, Yemen

  • Mohammed Sultan AlshayefEmail author
  • Akram Javed
  • Arafat Mohammed Bin Mohammed


Hydrocarbons serve the prime energy source of the world and the backbone to industrial development. Hydrocarbon potential is explored here using the spatial multi-criteria decision-making method. In order to demarcate the hydrocarbon potential zones within Masila oil field, Yemen, various thematic layers of multi-criteria factors affecting the hydrocarbons such as basement depth map (BDM), gravity anomaly map (GAM), magnetic anomaly map (MAM), subsurface faults system map (SFSM), upper syn-rift isopach map (USRIM), post-rift isopach map (PRIM), and lower syn-rift isopach map (LSRIM) were generated using the information extracted from both the geophysical and wells data available for the oil field. Geographical information system (GIS) techniques were used to generate various thematic maps that were subsequently converted to raster format and reclassified into various classes on the basis of their relative importance and the opinion of relevant experts. These thematic maps and their feature classes were assigned weights (eigenvalues) and rank by using the analytic hierarchy process (AHP) and following the theories of multi-criteria analysis (MCA). Furthermore, these maps were superimposed using the weighted linear combination (WLC) model on the GIS platform. The results of the integration of the thematic maps were classified into three classes representing the three hydrocarbon potential zones, namely, high potential zone (39.8%), moderate potential zone (49.1%), and low potential zone (11.1%). The cross plots of occurrence of the hydrocarbon reservoir, existing oil fields, and well locations were inferred for validation. The validation results revealed a good prospect for hydrocarbon potential in the study area. The novel quantitative approach used in the present study is capable of providing comprehensive results and assessment of hydrocarbons in the Masila oil field and other areas as well.


Multi-criteria analysis Analytic hierarchy process GIS integration Potential hydrocarbon zones Masila oil field, Yemen 



The authors are thankful to the editors of the Journal of Geovisualization and spatial analysis for their valuable comments and suggestions on this paper. The authors are grateful the anonymous reviewers for their critical and constructive comments which improve the contents significantly. The authors also acknowledge the Geological Survey and Mineral Sources Board, Yemen, for providing geological data and for Petroleum Exploration and Production Authority, Yemen, for providing the geophysical data. Thanks to Dr. Nabil Al-Areeq, Thamar University, Yemen, for providing seismic data.

Compliance with Ethical Standards

The manuscript complied with ethical standards.

Conflict of Interest

The authors declare that they no conflict of interest.

Ethical Approval

The manuscript agreed to research ethics.


  1. Al-Adamat R (2008) GIS as a decision support system for siting water harvesting ponds in the Basalt Aquifer/NE Jordan. J Environ Assess Policy Manag 10:189–206. CrossRefGoogle Scholar
  2. Al-Adamat R, Diabat A, Shatnawi G (2010) Combining GIS with multi-criteria decision making for siting water harvesting ponds in Northern Jordan. J Arid Environ 74(11):1471–1477. CrossRefGoogle Scholar
  3. Al-Areeq NM (2008) Sediment logical evaluation and petroleum system in the central part of Sayun-Masila basin, Republic of Yemen. Thesis Ph.D., Assiut University-EgyptGoogle Scholar
  4. Albaroot M, Ahmed AHM, Al-Areeq N, Sultan M (2016) Tectonostratigraphy of Yemen and geological evaluation: a new prospective. Int J New Technol 2(2):19–33Google Scholar
  5. Al-Shabeeb AR (2016) The use of AHP within GIS in selecting potential sites for water harvesting sites in the Azraq- Jordan. J Geogr Inf Syst 8:73–88. CrossRefGoogle Scholar
  6. Anane M, Kallali H, Jellali S, Ouessar M (2008) Ranking suitable sites for Soil Aquifer Treatment in Jerba Island (Tunisia) using remote sensing, GIS and AHP-multicriteria decision analysis. Int J Water 4:121–135. CrossRefGoogle Scholar
  7. As-Saruri MA, Sorkhabi R, Baraba R (2010) Sedimentary basins of Yemen: their tectonic development and lithostratigraphic cover. Arab J Geosci 3(3):515–520. CrossRefGoogle Scholar
  8. Beydoun ZR (1964) The structure and stratigraphy of the Eastern Aden protonate and Dhufar. In: Overseas Geology and mineral resources supplement series. HMSO, LondonGoogle Scholar
  9. Beydoun ZR (1991) Arabian plate hydrocarbon geology and potential: a plate tectonic approach. American Association of Petroleum Geologists, Tulsa. CrossRefGoogle Scholar
  10. Beydoun ZR, As-Saruri ML, Baraba RS (1996) Sedimentry basins of the republic of Yemen: their structural evaluation and geological characteristics. Rev Inst Francais Pétrole 15:763–775CrossRefGoogle Scholar
  11. Beydoun ZR, Alsaruri LA, El-nakhal H, Al-Ganad EN, Baraba SS, Nani OA, Al-Aawah M (1998) International lexicon of stratigraphy-geological of Yemen. Int Union Geol Sci 3(34):48–229Google Scholar
  12. Bin Mohammed AM (2017) Integration based GIS weighted linear combination (WLC) model for delineation hydrocarbon potential zones in Ayad Area (Yemen) using analytic hierarchy process (AHP) technique. Int J Geoinformatics Geol Sci 4(2):23–31. CrossRefGoogle Scholar
  13. Carver SJ (1991) Integrating multi-criteria evaluation with geographical information systems. Int J Geogr Inf Syst 5(3):321–339. CrossRefGoogle Scholar
  14. Das S (2019) Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas basin, India. Remote Sens Appl 14:60–74. CrossRefGoogle Scholar
  15. El-Awar FA, Makke MK, Mohtar R (2000) A hydro-spatial hierarchical method for siting water harvesting reservoirs in dry areas. Appl Eng Agric 16(4):395–404. CrossRefGoogle Scholar
  16. Elsheikh RFA, Ouerghi S, Elhag AR (2015) Flood risk map based on GIS, and multi criteria techniques (case study Terengganu Malaysia). J Geogr Inf Syst 7(4):348–357. CrossRefGoogle Scholar
  17. Feizizadeh B, Blaschke T (2013) GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin. Iran Nat Hazards 65(2):2105–2128. CrossRefGoogle Scholar
  18. Haitham FMS, Nani ASO (1990) The Gulf of Aden rift, in hydrocarbon potential of the Arabian sector. J Pet Geol 13(2):211–220. CrossRefGoogle Scholar
  19. Hajkowicz S, Higgins A (2008) A comparison of multiple criteria analysis techniques for water resource management. Eur J Oper Res 184(1):255–265. CrossRefGoogle Scholar
  20. Hazarika N, Barman D, Das AK, Sarma AK, Borah SB (2016) Assessing and mapping flood hazard, vulnerability and risk in the upper Brahmaputra River valley using stakeholders’ knowledge and multicriteria evaluation (MCE). J Flood Risk Manag.
  21. Hopkins LD (1977) Methods for generating land suitability maps: a comparative evaluation. J Am Inst Plann 34(4):19–29. CrossRefGoogle Scholar
  22. Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications. Springer-Verlag, BerlinCrossRefGoogle Scholar
  23. Jamali IA, Mörtberg U, Olofsson B, Shafique M (2014) A spatial multi-criteria analysis approach for locating suitable sites for construction of subsurface dams in Northern Pakistan. Water Resour Manag 28(14):5157–5174. CrossRefGoogle Scholar
  24. Jankowski P, Andrienko N, Andrienko G (2001) Map-centered exploratory approach to multiple criteria spatial decision making. Int J Geogr Inf Sci 15(2):101–127. CrossRefGoogle Scholar
  25. Kihoro J, Bosco NJ, Murage H (2013) Suitability analysis for rice growing sites using a multicriteria evaluation and GIS approach in great Mwea region, Kenya. Springer Open J.
  26. Krishnamurthy J, Kumar NV, Jayaraman V, Manivel M (1996) An approach to demarcate ground water potential zones through remote sensing and a geographical information system. Int J Remote Sens 17(10):1867–1884. CrossRefGoogle Scholar
  27. Linda A, Oluwatola A, Opeyemi TA (2015) Land suitability analysis for maize production in Egbeda local government area of Oyo state using GIS techniques. Int J Environ Ecol Eng 9(3):294–299Google Scholar
  28. Madrucci V, Taioli F, de Araújo CC (2008) Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, Sao Paulo State Brazil. J Hydrol 357(3-4):153–173. CrossRefGoogle Scholar
  29. Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New YorkGoogle Scholar
  30. Massam BH (1988) Multi-criteria decision making (MCDM) techniques in planning. Prog Plan 30(1):1–84. CrossRefGoogle Scholar
  31. Mills SJ (1992) Oil discoveries in the Hadramaut: how Canadian Oxy scored in Yemen. Oil Gas J 9:49–52Google Scholar
  32. Musungu K, Motala S, Smit J (2012) Using multi-criteria evaluation and GIS for flood risk analysis in informal settlements of Cape Town: the case of Graveyard Pond. S Afr J Geomatics 1(1):92–108Google Scholar
  33. Paul SK (1990) People democratic republic of Yemen, a future oil province. Geol Soc Lond Spec Publ 50:329–339. CrossRefGoogle Scholar
  34. PEPA (2004) Petroleum exploration& production authority. unpublished reports, YemenGoogle Scholar
  35. Rolland A, Rangarajan R (2013) Runoff estimation and potential recharge site delineation using analytic hierarchy process. Geocarto Int 28(2):159–170. CrossRefGoogle Scholar
  36. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281. CrossRefGoogle Scholar
  37. Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resources allocation. McGraw-Hill, New YorkGoogle Scholar
  38. Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26. CrossRefGoogle Scholar
  39. Saaty TL (2008) Decision making with the analytic hierarchy process. Int J Serv Sci 1(1):83–98Google Scholar
  40. Sahin O, Mohamed S, Warnken J, Rahman A (2013) Assessment of sea-level rise adaption options: multiple-criteria decision making approach involving stakeholders. Struct Surv 31(4):283–300CrossRefGoogle Scholar
  41. Shivaprasad Sharma SV, Roy PS, Chakravarthi V, Srinivasa Rao G (2017) Flood risk assessment using multi-criteria analysis: a case study from Kopili river basin Assam, India. Geomatics Nat Hazards Risk 9(1):79–93. CrossRefGoogle Scholar
  42. Sircar A (2004) Hydrocarbon production from fractured basement formations. Curr Sci 87(25):147–151Google Scholar
  43. Store R, Kangas J (2001) Integrating spatial multicriteria evaluation and expert knowledge for GIS-based habitat suitability modeling. Landsc Urban Plan 55(2):79–93. CrossRefGoogle Scholar
  44. Tomlin CD (1990) Geographical information systems and cartographic modeling. Prentice-Hall, Englewood CliffsGoogle Scholar
  45. Yalcin A (2008) GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): comparisons of results and confirmations. Catena. 72(1):1–12. CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of GeologyAligarh Muslim UniversityAligarhIndia
  2. 2.Department of Oil and GasUniversity of AdenShabwahYemen

Personalised recommendations