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Porosity wireline-derived data

Fig. 8. Combination diagram of grain size data (derived from core description, Fig. 2) and mineral proportions, porosity and permeability (derived from wireline log analysis). There is excellent correlation between quartz proportion and reservoir quality. The correlation of these with grain size is complex. The tops of some sandbodies have a high dolomite content and correspondingly poor reservoir quality (e.g. 2470-2471 m). Sandbodies are numbered for reference to Fig. 9. Core analysis porosity and permeability data (dashed and faint) have been added to the diagram for comparison with the wireline-derived data. Fig. 8. Combination diagram of grain size data (derived from core description, Fig. 2) and mineral proportions, porosity and permeability (derived from wireline log analysis). There is excellent correlation between quartz proportion and reservoir quality. The correlation of these with grain size is complex. The tops of some sandbodies have a high dolomite content and correspondingly poor reservoir quality (e.g. 2470-2471 m). Sandbodies are numbered for reference to Fig. 9. Core analysis porosity and permeability data (dashed and faint) have been added to the diagram for comparison with the wireline-derived data.
Fig. 7. Data quality assurance. (A) comparison of wireline-derived porosity and core analysis-derived porosity. There is a good correlation between the two data sets. The intercept on the x axis shows that the wireline porosity data are overestimating porosity by about 0.024. (B) Comparison of petrographically defined quartz and wireline-derived quartz—the correlation is good and is approximately 1 1 with a zero intercept. (C) Comparison of petrographically defined dolomite and wireline-derived dolomite—the correlation is good and has an approximately 1 1 slope with a zero intercept. Fig. 7. Data quality assurance. (A) comparison of wireline-derived porosity and core analysis-derived porosity. There is a good correlation between the two data sets. The intercept on the x axis shows that the wireline porosity data are overestimating porosity by about 0.024. (B) Comparison of petrographically defined quartz and wireline-derived quartz—the correlation is good and is approximately 1 1 with a zero intercept. (C) Comparison of petrographically defined dolomite and wireline-derived dolomite—the correlation is good and has an approximately 1 1 slope with a zero intercept.
Porosity and permeability core analysis data for the sampled well were made available to the authors by Elf (99 data points from the interval under investigation). Core porosity data have an uncertainty of less than 0.5%, which arises from the variable amount of stress relaxation following withdrawal of the core from the subsurface. Analytical errors are insignificant. Sonic transit time, neutron density, density and other wireline data recorded at 5 cm intervals by petrophysical logging methods were also made available by Elf These data were used to derive porosity and mineral proportions using methods outlined by Doveton (1994) and Hearst Nelson (1985). [Pg.165]

Wireline log analysis has been used to define porosity and mineralogy (with three components quartz, dolomite and shale), and these data have been used to derive permeability. They will be used subsequently to assess dolomite cement distribution within the reservoir. [Pg.168]

The derivation of porosity, mineralogy and permeability from wireline data has distinct advantages over core analysis data and petrographic analysis. Most importantly, wireline mineralogical... [Pg.171]


See other pages where Porosity wireline-derived data is mentioned: [Pg.163]    [Pg.170]    [Pg.170]   


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Derivative data

Wireline

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