Porosity prediction of I-field in the Niger delta area using well-log data and seismic attributes

Autor: Makinde, V, Bello, R, Omeike, M.O., Aikhuele, D.O.
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Scientia Africana; Vol 15, No 1 (2016)
ISSN: 1118-1931
Popis: There are many important characteristics of formations within the subsurface that can be used to determine locations of hydrocarbon reservoirs below the earth surface. This work used the Porosity characteristics of formation to determine the locations of hydrocarbon reservoirs of I – field. The study was aimed at interpolating data from few wells using well-log data, geo-statistical analysis and seismic attributes to determine porosity values in order to overcome the problem of multiple well drilling. The study area, I-field, is located between latitudes 4.7950oN and 4.8186oN, longitudes 6.9595oE and 6.9800oE. Variogram analysis and Sequential Gaussian Simulation were used as the geo-statistical techniques for interpolation. From these techniques, multiple models were generated and the best porosity model which revealed the direction of increased porosity within I-field, as well as areas with high and low porosity variation across the field was selected. Seismic attributes were then incorporated with this model to increase the level of certainty and reliability of the prediction. A cross-plot analysis of the gamma ray log and porosity log showed high responses along the depth 2800 m closing contour on a fault plane with average porosity variation of 18 - 28% at the depth 3200m located at the centre of the field. The cross-plot analysis revealed an increase in porosity at areas where sandstones are located (gamma-ray values from 0-55). Porosity prediction showed that locations at depth 2800 m within the I-field are of high porosity of 28% and are therefore viable locations for sitting of wells and prospecting for hydrocarbons; while locations at depth 3200m are of comparatively low porosity of 18%.Keywords: Porosity, Seismic Attributes, Lithology, Well Log, Hydrocarbon
Databáze: OpenAIRE