Cross plot Analysis of Rock Properties from Well Log Data for gas detection in Soku Field, Coastal Swamp Depobelt, Niger Delta Basin

  • Austin O
  • Agbasi O
  • Samuel O
  • et al.
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Abstract

The cross plotting of rock properties for fluid and lithology discrimination was carried out in a Niger Delta oil field using well data X-26 from a given oil field in the coastal swamp depobelt. The data used for the analysis consisted of suites of logs, including gamma ray, resistivity, sonic and density logs only. The reservoir of interest Horizon 1, was identified using the available suite of logs on the interval where we have low gamma ray, high resistivity and low acoustic impedance specifically at depths 10,424ft (3177.24m) to 10 724ft (3268m). We first obtained other rock attributes from the available logs before cross plotting. The inverse of the interval transit times of the sonic logs were used to generate the compressional velocities and the S-wave data was generated from Castagna´s relation. Employing rock physics algorithm on Hampson Russell software (HRS), rock attributes including Vp/Vs ratio, Lambda-Rho and Mu-Rho were also extracted from the well data. Cross plotting was carried out and Lambda Rho (λρ) versus MuRho (μρ) crossplots proved to be more robust for lithology identification than Vp versus Vs crossplots, while λρ Versus Poisson impedance was more robust than Vp/Vs versus Acoustic impedance for fluid discrimination, as well as identification of gas sands. The crossplots were consistent with Rock Physics Templates (RPTs). This implies the possibility of further using the technique on data points of inverted sections of various AVO attributes within the field in areas not penetrated by wells within the area covered by the seismic.

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APA

Austin, O. E., Agbasi, O. E., Samuel, O., & Etuk, S. E. (2018). Cross plot Analysis of Rock Properties from Well Log Data for gas detection in Soku Field, Coastal Swamp Depobelt, Niger Delta Basin. Journal of Geoscience, Engineering, Environment, and Technology, 3(4), 180. https://doi.org/10.24273/jgeet.2018.3.4.1318

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