Improvements in the Selection Criteria for the Representative Special Core Analysis Samples
- Shameem Siddiqui (Texas Tech U.) | Taha M. Okasha (Saudi Aramco) | James J. Funk (Saudi Aramco) | Ahmad M. Al-Harbi (Saudi Aramco)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- December 2006
- Document Type
- Journal Paper
- 647 - 653
- 2006. Society of Petroleum Engineers
- 5.6.2 Core Analysis, 5.6.1 Open hole/cased hole log analysis, 5.1.1 Exploration, Development, Structural Geology, 5.1.3 Sedimentology, 5.5 Reservoir Simulation, 1.6.9 Coring, Fishing, 5.8.7 Carbonate Reservoir, 5.1 Reservoir Characterisation, 4.3.4 Scale, 4.6 Natural Gas, 5.5.2 Core Analysis
- 3 in the last 30 days
- 1,281 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 12.00|
|SPE Non-Member Price:||USD 35.00|
The data generated from special-core-analysis (SCAL) tests have a significant impact on the development of reservoir engineering models. This paper describes some of the criteria and tests required for the selection of representative samples for use in SCAL tests. The proposed technique ensures that high-quality core plugs are chosen to represent appropriate flow compartments or facies within the reservoir. Visual inspection and, sometimes, computerized tomography (CT) images are the main tools used for assessing and selecting the core plugs for SCAL studies. Although it is possible to measure the brine permeability (kb ), there is no direct method for determining the porosity (f) of SCAL plugs without compromising their wettability. Other selection methods involve using the conventional-core-analysis data (k and f) on "sister plugs?? as a general indicator of the properties of the SCAL samples.
A selective technique ideally suited for preserved or "native-state?? samples has been developed to identify reservoir intervals with similar porosity/permeability relationships. It uses a combination of wireline log, gamma scan, quantitative CT, and preserved-state brine-permeability data. The technique uses these data to calculate appropriate depth-shifted reservoir-quality index (RQI) and flow-zone indicator (FZI) data, which are then used to select representative plug samples from each reservoir compartment. As an example application, approximately 400 SCAL plugs from an Upper Jurassic carbonate reservoir in the Middle East were tested using the selection criteria. This paper describes the step-by-step procedure to select representative plugs and criteria for combining the plugs for meaningful SCAL tests.
The main goal of coring is to retrieve core samples from a well to get the maximum amount of information about the reservoir. Core samples collected provide important petrophysical, petrographic, paleontological, sedimentological, and diagenetic information. From a petrophysical point of view, the whole-core and plug samples typically undergo the following tests: CT scan, gamma scan, conventional tests, SCAL tests, rock mechanics, and other special tests. The data are combined to get information on heterogeneity, depth shift between core and log data, whole-core and plug porosity and permeability, porosity/permeability relationship, fluid content (Dean-Stark), RQI, FZI, wettability, relative permeability, capillary pressure, stress/strain relationship, and compressibility. The petrophysical data generated in this way play important roles in reservoir characterization and modeling, log calibration, reservoir simulation, and overall field production and development planning.
Among all the petrophysical tests, the SCAL tests (which include wettability, capillary pressure, and relative permeability determination) are critical and time-consuming. A reservoir-condition relative permeability test can sometimes run for several months when mimicking the actual flow mechanisms taking place in the field. Therefore, it is very important to design these tests properly and, in particular, to select the samples that ensure meaningful results. In short, the samples must be "representative samples,?? which can capture the overall variability within the reservoir in a more scientific way. Unfortunately, the most important aspect of all SCAL procedures, the sample selection, is one of those least discussed. According to Corbett et al. (2001), API's RP40 (Recommended Practices for Core Analysis) makes very little reference to sampling; similarly, textbooks on petrophysics do not have sections on sampling. The Corbett et al. paper reviewed the statistical, petrophysical, and geological issues for sampling and proposed a series of considerations. This has led to the development of a method (Mohammed and Corbett 2002) using hydraulic units in a relatively simple clastic reservoir.
In this paper, some issues related to sample-selection criteria (with special focus on carbonate reservoirs) will be discussed. A large data set of conventional, whole-core, and special-core analyses on a well in an Upper Jurassic carbonate reservoir was used to characterize representative samples for SCAL tests.
|File Size||1 MB||Number of Pages||7|
Amaefule, J.O., Altunbay, M., Tiab, D., Kersey, D.G., and Keelan, D.K. 1993.Enhanced Reservoir Description:Using Core and Log Data To Identify Hydraulic (Flow) Units and PredictPermeability in Uncored Intervals/Wells. Paper SPE 26436 presented at theSPE Annual Technical Conference and Exhibition, Houston, 3-6 October. DOI:10.2118/26436-MS.
Corbett, P., Potter, D., Mohammed, K., and Liu, S. 2001. Forget BetterStatistics—Concentrate on Better Sample Selection. Proc., 6th NordicSymposium of Petrophysics, Trondheim, Norway, 15-16 May.
Craig, F.F. Jr. 1971. The Reservoir Engineering Aspects ofWaterflooding. Monograph Series, SPE, Dallas, 3: 64-66.
Funk, J.J., Siddiqui, S., Al-Sardi, A., and Haque, M.A. 1999. MultiscaleFlow Zone Determinations. SCA paper No. 9959 presented at the Soc. of CoreAnalysts Conference, Golden, Colorado, 2-4 August.
Hunt, P.K., Engler, P., and Bajsarowicz, C. 1988. Computed Tomography as a CoreAnalysis Tool: Applications, Instrument Evaluation, and Image ImprovementTechniques. JPT 40 (9): 1203-1210. SPE-16952-PA. DOI:10.2118/16952-PA.
Jensen, J.L., Lake, L.L., Corbett, P.W.M., and Goggin, D.J. 1997.Statistics for Petroleum Engineers and Geoscientists, 144-166.Upper Saddle River, New Jersey: Prentice Hall.
Mohammed, K. and Corbett, P. 2002. How Many Relative PermeabilityMeasurements Do You Need? A Case Study from a North African Reservoir. SCApaper No. 2002-03 presented at the SCA Symposium, Monterey, California, 23-26September.
Nelson, P.H. 1994. Permeability-Porosity Relationships in Sedimentary Rocks.The Log Analyst 35 (3): 38-62.
Saner, S. and Sahin, A. 1999. Lithological and Zonal Porosity-PermeabilityDistributions in the Arab-D Reservoir, Uthmaniyah Field, Saudi Arabia. AAPGBull. 83 (2): 230-243.
Siddiqui, S. 2001. Application of Computerized Tomography in Core Analysisat Saudi Aramco. Saudi Aramco J. of Technology (Winter 2000-2001)2-14.
Siddiqui, S., Funk, J., and Khamees, A. 2000. Static and DynamicMeasurements of Reservoir Heterogeneities in Carbonate Reservoirs. SCA paperNo. 2000-06 presented at the SCA Symposium, Abu Dhabi, UAE, 18-22 October.
Stiles, W.E. 1949. Use of Permeability Distribution in Water FloodCalculations Trans., AIME 186: 9-13.
Testerman, J.D. 1962. AStatistical Reservoir-Zonation Technique. JPT 14 (8):889-893; Trans., AIME, 225. SPE-286-PA. DOI: 10.2118/286-PA.
Tiab, D. and Donaldson, E.C. 1996. Petrophysics: Theory and Practice ofMeasuring Reservoir Rock and Fluid Transport Properties. Houston: GulfPublishing Co.
Vinegar, H.J. and Wellington, S.J. 1987. Tomographic Imaging of Three-PhaseFlow Experiments. Rev. Sci. Instrum. 58 (1): 96-107. DOI: http://dx.doi.org/10.1063/1.1139522.