Core analysis

Keywords d rec methods, indirect methods, rock properties, coring, core barrel, standard core analysis, special core analysis, slabbed core, sidewall samples, direct indications, microfossils, sonde, logging unit, invasion, mudcake, formation pressure measurement, fluid sampling, measurement while drilling, formation evaluation while drilling. 

In addition to a geological evaluation on a macroscopio and microscopic scale, plugs (small cylinders 2 cm diameter and 5 cm long) are cut from the slabbed core, usually at about 30 cm intervals. Core analysis is carried out on these samples. 

Special core analysis will include measurements of ... 

The main cost factor ot coring is usually the rig time spent on the total operation and the follow up investigations in the laboratory. Core analysis is complex and may involve different laboratories. It may therefore take months before final results are available. As a result of the relatively high costs and a long lead time of core evaluations the technique is only used in selected intervals in a number of wells drilled. 

The evenly distributed price points ensure result analysis maps based on a standard grid. Core analysis of simulation results considers profit and utilization of the value chain as illustrated in fig. 106. 

Continuous core analysis Continuous core analysis with ultraviolet light (natural fluorescence)... 

Long, P, Phase II Core Handling and Core Analysis—IR Imaging of Cores, ChevronTexaco JIP Workshop, Winchester, CO, September 30-October 1 (2003). 

Kleinberg, R.L., New Techniques in Sediment Core Analysis, Geological Society of London, Special Publication (Rothwell, R.G, ed.), 267, 179 (2006). 

Application of core drilling and core analysis to the recovery of oil. Intern. Petroleum Tech., 8 157-167. 

A. J. Lucas, G. K. Pierens, M. Peyron, T. A. Carpenter, L. D. Hall, R. C. Stewart, D. W. Phelps, and G. F. Potter, Quantitative porosity mapping of reservoir rock cores by physically slice selected NMR, in P. F. Worthington and C. Chardaire-Riviere, (Eds.), Advances in Core Evaluation III Reservoir Management, Reviewed Proceedings of the Society of Core Analysts Third European Core Analysis Symposium, France, September 14—16, 1992, Gordon and Breach Science Publishers, Reading, UK, 1993, pp. 3-24. 

Values of m and N are often available from electric log and core analysis, data. If this is so, a value for the water influx W may be calculated as shown in the following example. 

Armstrong DE, Swackhamer DL. 1983. PCB accumulation in southern Lake Michigan sediments Evaluation from core analysis. In Mackay D, et al., eds. Physical behavior of PCBs in the Great Lakes. Ann Arbor, MI Ann Arbor Science Press, 229-244. 

One of the key problems in describing the distribution of cement is the cost (in terms of time and money) of acquiring the data. Petrographic data are usually collected at a far lower density than core analysis data (if at all), are harder to quality-control and are highly operator-dependent. In this paper we describe a way to assess carbonate cement distribution in sandstones using petrophysical logs (hereafter known as wireline logs). We use this method to... 

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). 

Fig. 2. Core description and petrographic data. Grain size is shown as a continuous log. The petrographic data are represented by bars at the appropriate depths, with mineralogy represented (see key). Core analysis data are also displayed on this diagram. There are 99 porosity and permeability datum points.

Core analysis data are displayed as continuous logs in Fig. 2. Porosity varies from > 0 to 19%. Permeability varies from <0.1 mD to > 5000 mD. Porosity and permeability are highest where the rocks are most coarse grained. However, again the correlation is not perfect the tops of the sandbodies tend to have low porosity and permeability values relative to the middle and lower portions of sandbodies (Fig. 2). Consequently, grain size and facies variations cannot be used in isolation to understand or predict variations in reservoir quality. 

Core analysis data are also plotted on a conventional log-linear diagram (Fig. 4). There is considerable scatter in the data and a wide range of permeabilities for a given porosity. This probably means that there is more than one control on porosity, and thus permeability, evolution. 

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.

The results of these calculations are shown in Fig. 8. Inspection of Figs 2 and 8 shows that the wireline-derived permeability curve corresponds well with the core analysis data. 

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

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.

Core analysis data show that dolomite cement has a more detrimental effect upon permeability than quartz cement. Permeability has thus been calculated from the wireline porosity data using... 

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