Well log data analysis for lithology and fluid identification in Krishna-Godavari Basin, India

Well log data analysis for lithology and fluid identification in Krishna-Godavari Basin, India Well log analysis provides the information on petrophysical properties of reservoir rock and its fluid content. The present study depicts interpretation of well log responses such as gamma ray, resistivity, density and neutron logs from six wells, namely W-1, W-2, W-9, W-12, W-13 and W-14 under the study area of Krishna-Godavari (K-G) basin. The logs have been used primarily for identification of lithology and hydrocarbon-bearing zones. The gamma ray log trend indicates deposition of cleaning upward sediment. Coarsening upward, clayey-silty-sandy bodies have been evidenced from the gamma ray log. Gas-bearing zones are characterised by low gamma ray, high deep resistivity and crossover between neutron and density logs. Total 14 numbers of hydrocarbon-bearing zones are identified from wells W-9, W-12, W-13 and W-14 using conventional log analysis. Crossplotting techniques are adopted for identification of lithology and fluid type using log responses. Crossplots, namely P-impedance vs. S-impedance, P-impedance vs. ratio of P-wave and S-wave velocities (Vp/Vs) and lambda-mu-rho (LMR), have been analysed to discriminate between lithology and fluid types. Vp/Vs vs. P-impedance crossplot is able to detect gas sand, brine sand and shale whereas P-impedance vs. S-impedance crossplot detects shale and sand trends only. LMR technique, i.e. λρ vs. μρ crossplot is able to discriminate gas sand, brine sand, carbonate and shale. The LMR crossplot improves the detectability and sensitivity of fluid types and carbonate lithology over other crossplotting techniques. Petrophysical parameters like volume of shale, effective porosity and water saturation in the hydrocarbon-bearing zones in these wells range from 5 to 37%, from 11 to 36 and from 10 to 50% respectively. The estimated petrophysical parameters and lithology are validated with limited core samples and cutting samples from five wells under the study area. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Arabian Journal of Geosciences Springer Journals

Well log data analysis for lithology and fluid identification in Krishna-Godavari Basin, India

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Saudi Society for Geosciences
Subject
Earth Sciences; Earth Sciences, general
ISSN
1866-7511
eISSN
1866-7538
D.O.I.
10.1007/s12517-018-3587-2
Publisher site
See Article on Publisher Site

Abstract

Well log analysis provides the information on petrophysical properties of reservoir rock and its fluid content. The present study depicts interpretation of well log responses such as gamma ray, resistivity, density and neutron logs from six wells, namely W-1, W-2, W-9, W-12, W-13 and W-14 under the study area of Krishna-Godavari (K-G) basin. The logs have been used primarily for identification of lithology and hydrocarbon-bearing zones. The gamma ray log trend indicates deposition of cleaning upward sediment. Coarsening upward, clayey-silty-sandy bodies have been evidenced from the gamma ray log. Gas-bearing zones are characterised by low gamma ray, high deep resistivity and crossover between neutron and density logs. Total 14 numbers of hydrocarbon-bearing zones are identified from wells W-9, W-12, W-13 and W-14 using conventional log analysis. Crossplotting techniques are adopted for identification of lithology and fluid type using log responses. Crossplots, namely P-impedance vs. S-impedance, P-impedance vs. ratio of P-wave and S-wave velocities (Vp/Vs) and lambda-mu-rho (LMR), have been analysed to discriminate between lithology and fluid types. Vp/Vs vs. P-impedance crossplot is able to detect gas sand, brine sand and shale whereas P-impedance vs. S-impedance crossplot detects shale and sand trends only. LMR technique, i.e. λρ vs. μρ crossplot is able to discriminate gas sand, brine sand, carbonate and shale. The LMR crossplot improves the detectability and sensitivity of fluid types and carbonate lithology over other crossplotting techniques. Petrophysical parameters like volume of shale, effective porosity and water saturation in the hydrocarbon-bearing zones in these wells range from 5 to 37%, from 11 to 36 and from 10 to 50% respectively. The estimated petrophysical parameters and lithology are validated with limited core samples and cutting samples from five wells under the study area.

Journal

Arabian Journal of GeosciencesSpringer Journals

Published: May 15, 2018

References

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