Document Type : Research Paper

Authors

• James Sunday Abe ¹
• Kenneth Okosun ²

¹ Ph.D., Department of Applied Geophysics, Federal University of Technology, Akure, Nigeria

² B. Tech., Department of Applied Geophysics, Federal University of Technology, Akure, Nigeria

Abstract

Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (S_w) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.



 



Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (S_w) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.



 [KO1]Sentence has been rephrased.




 [M.N.2]This verb does not make sense in this context and has made the sentence unclear.




 [KO3]Sentence has been rephrased



 

Highlights

• Seismic, check-shot, and well logs data are analyzed for the reservoir characterization and modeling of “KO” Field in Niger Delta.
• Interpretation of the well logs is matched to the seismic lines to ensure that there is a good correlation between them.
• Three different seismic attributes are used to identify high amplitude regions and to perform a comprehensive structural interpretation of the field.
• A geological model representing the structural, stratigraphic, lithological, petrophysical features of the reservoir is constructed and evaluated.

Keywords

• Reservoir Characterization
• Seismic Attributes
• 3D Static Modeling

20.1001.1.23452412.2020.9.4.1.9

Main Subjects

• Petroleum Engineering