Porosity depth plots

Figure 8.32. Porosity-depth plots of (A) shallow-marine carbonates and (B) deep-sea oozes. (After Scholle and Halley, 1985.)...

Fig. 9. Porosity/depth plot for the Hibernia Oilfield. Geothermal gradient from Suie (personal communication). Sandstone diagenetic-maturity classification after Schmidt McDonald (1979a).

Log SI can be plotted versus time for each modeled layer, or it can be plotted against present-day depth. When log SI is positive, the mineral is oversaturated and will precipitate when log SI is negative, the mineral is undersaturated and will dissolve. Moreover, comparing log SI vs. present-day depth plots with porosity/depth plots allows the predicted mineral stabilities (potential porosity anomalies) to be tested directly. In this manner, a model of the evolution of porosity in a targeted clastic reservoir system can be accurately evaluated. 

The microsol scale technique is used to weigh a shale sample out of and in water, thus giving weight and volume. The results are plotted versus depth. Low shale densities (high porosity filled with water) indicate overpressured zone. A demonstration example is shown in Figure 4-336. 

Figure Al. a) Porosity distribution for a ID melt column (solid curve) assuming constant melt flux (see Spiegelman and Elliott 1993). Average porosity is shown as the dashed line, b) Emichment factors (a) calculated from the analytical solution (solid curves) and approximate analytical solution (dotted curves) for °Th and Ra. c) Emichment factors (a) calculated from the numerical solution of Spiegelman and Elliott (1993) for °Th and Ra. In these plots, depth (z) is non-dimensionalized. See text for explanation.

The small spheres are fluid molecules, and the large spheres are immobile silica particles. The top visualizations are for a disordered material and the bottom visualizations are for an ordered material of the same porosity. The visualizations on the left are for the saturated vapor state, and those on the right are for the corresponding saturated liquid state, (b) Simulated adsorption and desorption isotherms for Lennard-Jones methane in a silica xerogel at reduced temperature kT/Sfi = 0.7. The reduced adsorbate density p = pa is plotted vs the relative pressure X/Xo for methane silica/methane methane well depth ratios ejf/Sff = 1- (open circles) and 1.8 (filled circles) [44]. (Reproduced with permission from S. Ramalingam,... 

Sonic transit time, neutron density and density log data for the cored interval are presented as functions of depth in Fig. 5. The same data are cross-plotted in Fig. 6 with the positions of the three minerals added. Equations (l)-(4) can be solved for porosity plus three solid-grain components. The logs have been converted into fractional porosity and the fractional quantities of quartz, dolomite and shale. The rock was thus assumed to consist of three minerals quartz (all silica minerals and feldspar), dolomite (all carbonate minerals) and shale (all clay minerals). Each group of minerals has approximately uniform responses to the three wireline logging tools. Petrographic analysis shows that the quartz/feldspar ratio is greater than about three (Table 3), suggesting that the assumption about the quartz component is... 

Fig. 12.4 Effects of the depth resolution in pore water concentration profiles on calculating the rates of diffusive transport. Three samples drawn from surface sediments are shown to possess different resolutions (intervals 0.5 cm - dots, 1.0 cm diamonds, 2.0 cm - squares). All values are sufficient to plot the idealized concentration profile within the hounds of analytical error, yet very different flux rates are calculated in dependence on the depth resolution values. In the demonstrated example, the smallest sample distance indicates the highest diffusion (2.98 mmol cmA f ). As soon as the vertical distance between single values increases, or, when the sediment segments under study grows in thickness, the calculated export across the sediment-water boundary diminishes (2.34-t.64mmol cm yr ). In our example, this error which is due to the coarse depth resolution can be reduced by applying a mathematical Fit-function. A truncation of 0.05 cm yields a flux rate of 2.84 mmol cm yr. (The indicated values were calculated under the assumption of the presented porosity profile according to Pick s first law of diffusion - see Chapter 3. A diffusion coefficient of 1 cmA f was assumed. Adaptation to the resolution interval of 2.0 cm was accomplished by using a simple exponential equation).

Fig. 3. shows the axial voidage distribution in the packing with 3 different stiffness coefficients (spring constants). Each dot represents the simulation result of one slice. Fig. 4. plots the bed depth for the reassembled slices. Fig. 5. and 6. present the corresponding results for case 2, which has a slightly denser initial packing porosity. 

Fig. 16. Plot of porosity versus depth for the Latrobe Sandstone. + represents porosity values detected by the authors, while o represents porosity values obtained by Bodard et al. (1984), The area between the two curves, representing porosity loss due to compaction versus depth for a sandstone containing 50% quartz left-hand curve) and a sandstone containing 75% quartz right-hand curve), contains the base porosity values due to compaction predicted by Pittman and Larese (1991). The two horizontal lines outline positive anomalies, while the data points left of the base porosity area are negative anomalies...

Veeken (2007) notes that the RPT plot is area or basin dependent and velocity-porosity trends are calculated for the expected lithologies and various depth of burial (compaction). A distinction needs to be made between silici-clastic and carbonate systems . 

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