{"title":"3-D Geostatistical Model and Volumetric Estimation of âÂÂDelâ Field, NigerDelta","authors":"Oluwadare Oa, Osunrinde Ot, Abe Sj, Ojo Bt","doi":"10.4172/2381-8719.1000291","DOIUrl":null,"url":null,"abstract":"There is an insatiable thirst for oil and gas consumption and increased production will be made possible only \n through effective reservoir characterization and modeling. A suite of wire-line logs for four wells from ‘DEL’ oil field \n together with 3D seismic data were analyzed for reservoir characterization of the field. Two reservoirs were identified \n using the resistivity log. A synthetic seismogram was generated in order to perform seismic to well tie process as \n well as picking of horizons throughout the section. Time and depth structural maps were generated. Geostatistical \n simulation such as the sequential Gaussian stimulation and sequential indicator stimulation were carried out to provide \n equiprobable representations of the reservoirs, and the distribution of reservoir properties within the geological cells. \n The modeled reservoir properties resulted in an improved description of reservoir distribution and inter connectivity. \n The analysis indicated the presence of hydrocarbon in the reservoirs. There is also a fault assisted closure on the \n structural map which is of interest in exploration. A fluid distribution plot and map of the field were also obtained. The \n modeled properties gave an average porosity of 24%, average water saturation ranging from 12%-24% and moderate \n net-gross. The volumetric calculation of the reservoir gives a STOIIP ranging from 37.53 MMbbl-43.03 MMbbl. The \n result showed high hydrocarbon potential and a reservoir system whose performance is considered satisfactory for \n hydrocarbon production. The resulting models can also be used to predict the future performance of the reservoir.","PeriodicalId":80381,"journal":{"name":"AGSO journal of Australian geology & geophysics","volume":"33 1","pages":"1-10"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AGSO journal of Australian geology & geophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/2381-8719.1000291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
There is an insatiable thirst for oil and gas consumption and increased production will be made possible only
through effective reservoir characterization and modeling. A suite of wire-line logs for four wells from ‘DEL’ oil field
together with 3D seismic data were analyzed for reservoir characterization of the field. Two reservoirs were identified
using the resistivity log. A synthetic seismogram was generated in order to perform seismic to well tie process as
well as picking of horizons throughout the section. Time and depth structural maps were generated. Geostatistical
simulation such as the sequential Gaussian stimulation and sequential indicator stimulation were carried out to provide
equiprobable representations of the reservoirs, and the distribution of reservoir properties within the geological cells.
The modeled reservoir properties resulted in an improved description of reservoir distribution and inter connectivity.
The analysis indicated the presence of hydrocarbon in the reservoirs. There is also a fault assisted closure on the
structural map which is of interest in exploration. A fluid distribution plot and map of the field were also obtained. The
modeled properties gave an average porosity of 24%, average water saturation ranging from 12%-24% and moderate
net-gross. The volumetric calculation of the reservoir gives a STOIIP ranging from 37.53 MMbbl-43.03 MMbbl. The
result showed high hydrocarbon potential and a reservoir system whose performance is considered satisfactory for
hydrocarbon production. The resulting models can also be used to predict the future performance of the reservoir.