Determination of the Formation Damage Potential by Simulation
Reservoir exploitation processes frequently cause pressure, temperature and concentration changes, and rock-fluid and fluid-fluid interactions, which often adversely effect the performance of these processes. Prior to any reservoir exploitation applications, extensive laboratory, field and simulation studies should be conducted for assessment of the formation brine and mineral chemistry and the formation damage potential of the reservoir.
Consequently, optimal strategies can be designed to effectively mitigate the adverse effects and improve the oil and gas recovery. Typical examples of such detailed studies have been presented in a series of reports by Demir (1995), Haggerty and Seyler (1997), and Seyler (1998) for characterization of the brine and mineral compositions and the investigation of the formation damage potential in the Mississippian Aux Vases and Cypress formations in the Illinois Basin. Demir (1995) used the chemical data on the formation brines and minerals to interpret the geology, determine the properties (porosity, permeability, water saturation), and estimate the formation damage potential of these reservoirs.
Contents
Formation Minerals and Brines
The stratigraphic dispositions of the Aux Vases and Cypress formations are shown in this article by Leetaru (1990) given by Demir (1995).
Formation Brines
Demir (1995) reports that brine samples were gathered from the oil producing wells in the Aux Vases and Cypress formations. Also, the samples of the brines of the Cypress and Waltersburg formations, which
are used for water flooding in the Aux Vases and Cypress reservoirs, were collected from the separation tanks. Prior to sample collection, chemical
treatments, such as acidizing and corrosion inhibitor applications in the wells, were ceased usually for 24 hours, but at least for 4 hours. The brine
samples were collected using the USGS method, described in this article, and isolated from exposure to the atmosphere to avoid oxidation and
degassing. The samples were identified by the well API numbers and field names, and the pH, Eh resistivity, total dissolved solids (TDS), and laboratory chemical analysis of these samples were determined. The results are summarized in Table 17-1 by Demir (1995). The methods used to analyze the formation brine samples are described according to ISGS (1993).
Formation Heterogeneity
The maps of the areal distributions of the total dissolved solids (TDS) of the Aux Vases and Cypress formation brines are shown in this article
respectively, by Demir (1995). Demir (1995) states that "variations in water chemistry in a given reservoir in the same field can indicate a lack of communication between different pools, or mineralogical heterogeneity within the reservoir." Demir (1995) indicates that the total dissolved solids (TDS) increase by depth. However, the data points are somewhat scattered. This indicates the presence of structural and stratigraphic irregularities in the basin (Demir, 1995).
Inferring Reservoir Properties from Resistivity
versus TDS and Temperature Relationships
The brine resistivities and TDS of formation brines, measured before degassing and oxidation, can be used to estimate water saturations and permeabilities (Demir, 1995). Demir (1995). Based on the linear plot shown in this article, Demir (1995) developed the following empirical relation between the resistivity and the TDS content of the brine samples at 25°C temperature:
In addition, Demir (1995) developed two more empirical relationships. The first equation predicts brine resistivities at temperatures, T(°C), in
the range of 18-60°C, given the brine resistivity at 25°C:
The second equation predicts brine resistivities at temperatures, T(°C), in the range of 18-60°C, given the TDS value in the range of 48,697-148,028 mg/1:
Once the resistivity is known, Demir (1995) explains that water saturation can be estimated by the Archie (1942) equation. Alternatively, Demir (1995) explains that saturation can also be estimated using the data of TDS and apparent water salinity (AWS) determined by the TDT-K Thermal Decay Timelog technique (Schlumberger, 1989, pp. 128-130). Then, the permeability can be estimated by means of the empirical relationships of porosity, permeability, and water saturation according to Schlumberger (1989, pp. 138-139).
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