Pure and Applied Geophysics Research Papers (original) (raw)

Depositional facies correlation and petrophysical evaluation of Bosso Field was carried out to generate part of the information required for profitable development of the field. Exaggerated reservoir continuity and grouping of genetically... more

Depositional facies correlation and petrophysical evaluation of Bosso Field was carried out to generate part of the information required for profitable development of the field. Exaggerated reservoir continuity and grouping of genetically unrelated reservoirs commonly result from the traditional method of depositional facies correlation that is based on similar lithologies and paleontological events. Wells drilled on the basis of the results from such correlations are sometimes dry, and the asset operator suffers colossal financial loss. The conventional technique of determining porosity correction linearly from gamma ray index yields inaccurate effective porosity values in Tertiary shaly sand reservoirs, and ultimately misleading reserve estimates. The study was performed using Halliburton’s Geographix® DiscoveryTM 5000.0.0.0 software, open-hole geophysical logs acquired from six wells named BO-1, BO-2, BO-4, BO-5, BO-6 and BO-7. Benin Formation was delineated from Agbada Formation on the basis of gamma ray log variation pattern, resistivity values and shale thickness. The top of Agbada Formation was penetrated at 7,878 ft (2,403 m), 7,929ft (2,418 m), 7,845 ft (2,393 m), 7,873 ft (2,401 m), 7,867 ft (2,399 m) and 7,930 ft (2,419 m) in wells BO-2, BO-6, BO-1, BO-5, BO-7 and BO-4 respectively. Akata Formation was penetrated only at BO-1 and BO-6. Marine flooding surfaces were utilised in dividing the Agbada Formation into six parasequences which were correlated across the well logs. The parasequences were all progradational. Three hydrocarbon reservoirs named A, B, C were identified and correlated within the parasequences. Effective porosity was obtained using Larionov formula and hydrocarbon saturations were obtained using the Indonesian method. Permeability was estimated using Timur’s equation. Hydrocarbon volume per unit reservoir volume of each reservoir was obtained as the product of hydrocarbon saturation and reservoir thickness. Sand 6B (Sand B in BO-6) had the highest hydrocarbon saturation values of 0.773. Sand 5B (Sand B in BO-5) had the lowest hydrocarbon saturation of 0.62. Sand 6B yielded the highest permeability (20,686 mD) while lowest permeability value (1,452 mD) was obtained in Sand 5C. Sand 5A (Sand A in BO-5) had the highest hydrocarbon volume per unit reservoir volume of 501.21 while Sand 4C (Sand C in BO-4) had the lowest value of 69.09. The work revealed opportunities for infill well drilling between BO-5 and BO-1, as well as between BO-5 and BO-4 for increased production from Sand C. Opportunities for infill well drilling for increased production from Sands A and B were also revealed between BO-1 and BO-4, and between BO-5 and BO-4.