Reconciling Core Derived Permeabilities and Well Test Using A Fracture Network: A Field Case Example
- Mohsen Charfeddine (ADCO) | Maged Al-Deeb (ADCO) | Salem El-Abd (ADCO) | Asnul Bahar (Kelkar and Associates, Inc.) | Harun Ates (Kelkar and Associates, Inc.) | Tono Soeriawinata (Kelkar and Associates, Inc.) | Mohan Kelkar (The Univ. of Tulsa)
- Document ID
- Society of Petroleum Engineers
- Abu Dhabi International Petroleum Exhibition and Conference, 13-16 October, Abu Dhabi, United Arab Emirates
- Publication Date
- Document Type
- Conference Paper
- 2002. Society of Petroleum Engineers
- 5.8.7 Carbonate Reservoir, 4.1.5 Processing Equipment, 4.1.2 Separation and Treating, 5.6.4 Drillstem/Well Testing, 1.6.9 Coring, Fishing, 5.1 Reservoir Characterisation, 5.5.8 History Matching, 3.2.3 Hydraulic Fracturing Design, Implementation and Optimisation, 5.1.2 Faults and Fracture Characterisation, 5.6.1 Open hole/cased hole log analysis, 4.3.4 Scale, 5.1.5 Geologic Modeling, 5.5.3 Scaling Methods
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It is a common observation that well test permeability values do not match with thickness weighted core permeability averages. This is not a surprise because of the differences in the measurement scales where, unlike well test measurements, core samples represent a very small portion of the reservoir around the well bore. In addition, the presence of fractures and/or high permeability channels will further enhance the difference between the two sources of data. Therefore, reservoir descriptions based on core measurements alone cannot honor well test results. They need to be modified properly without violating the underlying geological and geostatistical information.
In this paper, we present a methodology to properly enhance permeability fields that also accounts for fracture distribution in the reservoir. The basic idea is that radial upscaling around a wellbore within a given investigation radius should match the permeability obtained from well tests. The enhancement is caused by two factors: microfractures, which cannot be explicitly represented in the reservoir description, and macro-fractures, which can be interpreted using 3-D seismic data. To account for these two different types of fractures, we calculate two different enhancement factors, one for the base level (microfractures) and one for the higher level (macro-fractures). The base level, after appropriate interpolation, is applied across the entire reservoir, whereas the higher level is applied only to locations where macro-fractures are interpreted from 3-D seismic data.
The technique was successfully applied to a Middle Eastern carbonate reservoir. A significant correlation is observed between the enhancement required to match the well test data and the fracture density (macro-fractures obtained from 3-D seismic data) within a given investigation area. A correlation function is then obtained between the enhancement factor and the fracture density for a given grid block, which in turn is used to apply enhancement to interwell locations. Thus, the resulting permeability field did not only honor the well test results but also the fracture distribution and the underlying geological and geostatistical descriptions. In a later stage, a tensorial approach was used to upscale permeability to account for the anisotropy in permeability distribution. Using this approach, a proper anisotropy of permeability distribution, matching the fracture orientation, has been obtained.
This paper presents one aspect of the fully integrated reservoir characterization and flow simulation study of an oilfield in the Middle East. A comprehensive integrated reservoir characterization was conducted by considering all available data, namely well logs and cores, geological interpretation, seismic (structures and inversion-derived porosity), fracture network, and pressure build up tests. The approach used in the study was a stochastic approach where multiple reservoir descriptions were generated to quantify the uncertainty in the future performance (Ref. 1).
Reservoir properties for each realization were generated using a geostatistical technique that produces properties, i.e., porosity, permeability and water saturation, consistent with the underlying rock type description. The description was based on core and log data. Additionally, porosity, which affects the permeability description, was also constrained to the seismic derived porosity. The permeability distribution generated by this method was referred to as the core-derived permeability in this paper.
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