Reservoir Characterization by Seismic Attributes With Vp & Vs Measurement of core samples (a "Rock Physics" study)

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1 Page 1 of 8 Reservoir Characterization by Seismic Attributes With Vp & Vs Measurement of core samples (a "Rock Physics" study) Saeed Amiri Besheli, S. Saleh Hendi, and Jaafar Vali Geophysics Department, RIPI-NIOC ABSTRACT Seismic reflection methods have been extensively used for the detailed delineation of the subsurface structure for the exploration of hydrocarbon. Recently, the so-called "seismic inversion" technique has been applied not only to an enhancement of the resolution but also to a characterization of the reservoir. In this technique, well data is treated as "hard data", which is fixed throughout the numerical calculation. On the other hand, seismic data is used as "soft data", which is treated as less reliable compared to the well data. Nevertheless, since there are some errors in the well data due to factors such as a large caving of a borehole, a suitable verification is required, especially for the portion of complicated reservoir. Quantitative interpretation of sonic logs using calibrated relationships is an important application of the "Rock Physics Model" for well log formation evaluation. "Rock Physics" plays a fundamental role in the development of many new seismic technologies, such as production and development seismology, seismic monitoring of EOR processes, and direct hydrocarbon and porosity detection. "Rock Physics" not only provides the physical and feasibility basis for developing and using seismic technologies in characterizing reservoirs and reservoir processes, but also bridge exploration, production, and management of reservoir through interpreting seismic results. "Rock Physics Model" doesn t apply in Iranian Reservoir Characterization, because this method needs to install an advance system for core velocity measurements in reservoir conditions. In this paper, we demonstrate one case study basis "Rock Physics Model" on a Carbonate oil field that similar to Iranian Reservoir. Introduction During the past 50 years or so, tremendous progress has been made in studying physical properties of rocks and minerals in relation to seismic exploration and earthquake seismology. During this period, many theories have been developed and many experiments have been carried out. Some of these theories and experimental results have played important roles in advancing earth sciences and exploration technologies. In exploration seismology, seismic waves bring out subsurface rock and fluid information

2 Page 2 of 8 in the form of travel time, reflection amplitude, and phase variations. During the early years of exploration seismology, seismic data were interpreted primarily for structures that might trap hydrocarbons. With the advancement of computing power and seismic processing and interpretation techniques, seismic data are now commonly analyzed for determining lithology, porosity, pore fluids, and saturation. "Rock Physics" bridges seismic data and reservoir properties and parameters, it has been instrumental in recent years in the development of technologies such as 4-D seismic reservoir monitoring, seismic lithology discrimination, and direct hydrocarbon detection with "bright-spot" and angledependent reflectivity analyses. Seismic properties are affected in complex ways by many factors, such as pressure, temperature, saturation, fluid type, porosity, pore type, etc. These factors are often interrelated or coupled in a way that many also change when one factor changes. The effect of these changes on seismic data can be either additive or subtractive. As a result, investigation of the effect of varying a single parameter while fixing others becomes imperative in understanding "Rock Physics" applications to seismic interpretations. Because of the vast amount of information in the literature on "Rock Physics", it is impossible to summarize every theory and every experimental finding in this paper. In this paper, we describe a method in which core and log measurements are used to establish a calibrated "Rock Physics Model" for seismic interpretation. The first part reviews several aspects of the relationships between petrophysical, lithologic, and acoustic properties in Carbonate rocks that justify a need for calibration of seismic interpretation. Using a case study on a Carbonate oil reservoir, We demonstrate in the second part how the calibration method is applied to sonic and seismic measurements and used in a reservoir characterization. Elastic Properties of Carbonate Rocks Many studies have shown that in Carbonate rocks, porosity is the rock parameter that has the most impact on velocity. Hence, characterization lateral variations in porosity within a field from seismic velocities or impedance are potentially feasible and represent a major contribution of seismic techniques for reservoir appraisal. However, because velocities in Carbonate rock also depend on other parameters, such as mineralogy, pore shape, and fluid type, the velocity-porosity trend may be too scattered to permit precise determination of porosity from velocity measurements. To gain insight as to how petrophysical and lithologic parameters can affect the velocity-porosity relationship, one can use the following physically based relationship between the elastic modulus of the skeleton frame of a rock and porosity: (1) Where and are the bulk moduli of the skeletal frame and mineral phase of the rock, respectively, is the porosity, and is the compressibility of the pores. Is related to the and and bulk density (ρ) of an isotropic dry rock according to: (2) From equation (1), we note that the bulk modulus varies with porosity,, but that is also depend on the bulk modulus of the mineral phase,, which varies with mineralogy, and the compressibility of the

3 Page 3 of 8 pores,, which depends mostly on pore shape and aspect ratio. Furthermore, for fluid saturated rocks, the bulk modulus also depends on fluid compressibility and measurement frequency. Hence, precise porosity determination from elastic properties relies on an accurate assessment of the influence of mineralogy, pore shape, and fluid type on elastic properties. Influence of mineralogy The minerals that are commonly found in Carbonate rocks -calcite, dolomite, and aragonite- have a wide range of elastic properties and density. From equation (1), the effect of mineralogy on bulk modulus should correspond to a change in the intercept in the relationship between porosity and the inverse bulk modulus. For calcite and dolomite, the influence of mineralogy on bulk modulus is expected to be negligible, but shear modulus and density are influenced to greater extent by calcite-dolomite content. Consequently, compressional and shear velocities (Vp & Vs) and impedance (Ip & Is) are related to density and elastic moduli through the following equations and should be sensitive to mineralogy because shear modulus (G) and bulk density (ρ) depend on mineral content: (3), (4) (5), (6) Hence, in the process of estimating porosity from velocity or impedance measurement, information about the mineralogy is essential. Influence of pore shape The effect of pore compliance and shape on the elastic properties of rocks has been investigated from both theoretical and experimental standpoints. A self-consistent technique illustrates, for a given velocity, porosity can vary depending on pore shape. Such influence of pore shape on velocity can also be observed qualitatively in core data, for this data set, it is clear that the presence of vuggy porosity strongly influences the velocity-porosity behavior of P- and S-waves. Influence of fluid type In addition to mineralogy and pore type, saturation also influences velocity measurements and hence can affect the velocity-porosity trend. Note that ultrasonic frequency measurements and Gassmann s predictions can be considered as upper and lower boundaries, respectively, for estimating the influence of fluid type on elastic properties or seismic and well-log applications. Case Study: A Carbonate Oil Field This case study on a Tertiary carbonate oil field illustrates a method that uses combined information

4 Page 4 of 8 acquired at core, log, and seismic scales to characterize petrophysical properties from seismic measurements. This oil field under consideration has estimated reservoir of 110 million tones of oil. The main problem confronting development of this filed is the need to characterize reservoir limits and internal reservoir properties more accurately. Information from wells indicates a large variability of porosity, oil saturation, and reservoir thickness across the field. Therefore, this case study examines in detail the influence of this parameters on velocity and impedance in an attempt to determine the possible contribution of seismic measurements to the reservoir model revision. From Core to Log to Seismic To calibrate the seismic attributes, a three-step method based on core and log measurements was developed (Fig. 1.). First," Rock Physics Model" was derived using core measurements, which related Vp & Vs and Impedances to rock properties (porosity & fluid type) and to measurement conditions (frequency & stress). Second, a comparison of core, log, and a seismic measurement was performed to check that the "Rock Physics Model" could be applied with confidence to well log and seismic interpretation. Third, the "Rock Physics Model" was used for quantitative interpretation of sonic and seismic data. If this step is completed successfully and if data quality permits, seismic attributes can be interpreted in quantitative reservoir parameters.

5 Page 5 of 8 Fig.1. Graph of relationships of Core, Log, and Seismic data, showing interpretation of seismic attributes. Core Measurement Result Core measurements included Vp & Vs, porosity, and gas permeability as a function of stress mineral density, and a quantitative petrographic description for each plug. Using these measurements, we were able to establish a "Rock Physics Model" for the influence of porosity, pore shape, mineralogy, saturation, and measurement frequency. To quantify of total porosity, pore shape, and mineralogy on Vp & Vs, constrained the empirical fitting of elastic moduli data using equation (1), in which elastic moduli were computed from velocity and density measurements. The two pore types identified in thin section analysis (Intraparticle & Interparticle) have a distinctly different influence on elastic properties. As total porosity increases, the Intra. Porosity also generally increases. Mineralogy had little impact on the quality of the regression fit between the elastic moduli and the porosity because of the predominance of calcite in this samples. To investigate the influence of fluid type on elastic properties, measurements of Vp & Vs were taken under stress on dry and fully brine-saturated samples at ultrasonic frequencies. Vs measurements are nearly unaffected by fluid type, as predicted by Gassmann s equation. Vp s are greater by about 10% in brine-saturated rocks than in dry rocks. To investigate the influence of frequency, for dry samples no significant discrepancies were found between measurements at sonic and ultrasonic frequencies, suggesting that dispersion is negligible. In contrast, ultrasonic velocities in brinesaturated samples higher than sonic velocities. "Rock Physics Model" describes the influence of porosity, pore shape, mineralogy, fluid type, and measurement frequency on velocity and impedance. Core to Log Seismic Comparison An example of a core-log comparison is shown in Fig.2. In this figure, Vp measured on dry cores at atmospheric pressure ( ) was corrected for stress ( ), saturation ( ), and frequency using the "Rock Physics Model". Furthermore, to allow direct comparison between cores and well log measurements, core data were brought to the scale of resolution of sonic measurements ( ) using an up-scaling procedure. To compare log and seismic measurements, the classic method of comparing synthetic seismograms and seismic traces was used. In this procedure, impedances measured from log data are sampled every 4 ms in the time domain, then converted to reflectivity s (derivatives of impedance), and finally are convolved with seismic traces (Fig.3). In this calibration step, in which we compared core with log data and log with seismic data, no systematic discrepancies were observed between measurements obtained at various scales. This is encouraging for subsequent use of the ""Rock Physics Model" at sonic and seismic scales. Sonic Log Interpretation The "Rock Physics Model" was used in this case study to estimate porosity from sonic measurements on a multiwell basis. Results in Fig. 4. Show good agreement between sonic porosity and core porosity on a multiwell basis. These results confirm (1) the predictive value of "Rock Physics Model" at the sonic scale and (2) the small impact of saturation, mineralogy, and pore shape on porosity determination from velocity measurements. Finally, this study shows that sonic measurements, once properly calibrated, can

6 Page 6 of 8 be used quantitatively for porosity estimation. Fig. 2. Logs of sonic data (solid lines) overprinted with upscale core measurements (dots) showing a comparison of the two data sets. Fig. 3. Comparison between seismic trace (bottom) and synthetic

7 Page 7 of 8 seismogram derived from log data. Fig. 4. Comparison of porosity values calculated using sonic logs (solid lines) with values measured on cores (dots) from three different wells. Seismic Inversion Well data were used to establish a layered initial impedance model. This was done by blocking the impedance logs and extrapolating laterally along interpreted seismic horizons. The acoustic impedance in this initial model range from 11 to 13 km/s g/ in reservoir zone, in the inversion results, a greater variability of impedance is seen from 9 to 13 km/s g/. This suggests that there are stronger variations in porosity than estimated from the initial model, especially in the central zone of the reservoir. Interpretation of Seismic Impedance From the inversion results, two seismic attributes can be accessed: the average impedance and the total traveltime in the reservoir. These attributes are used to estimate porosity and reservoir thickness according the following procedure. Porosity is calculated directly from the relationship between

8 Page 8 of 8 impedance and porosity from the "Rock Physics Model". Traveltimes are used to compute the reservoir thickness, knowing the average velocity in the formation. The average velocity is calculated from impedance at each trace using the relationship between velocity and impedance from "Rock Physics Model". The relationship between impedance and porosity was applied to the inverted seismic impedance to generate a profile of porosity. To obtain results comparable to the reservoir model dimensions, porosity and thickness profiles were averaged over 10 and 40 traces corresponding to 120 And 500 m, respectively. Similarly, using the information contained in impedance and traveltime, a total reservoir thickness profile was obtained. For comparison, the average reservoir porosity values measured were superposed at the wells. The seismically derived properties are coherent at well sites with log observations. In particular, seismic inversion successfully predicts porosity and reservoir thickness at the blind well locations. These results provide confidence in estimating porosity and pay zone away from the well using seismic measurements, with the exception of the zone of poor-quality seismic data. The seismically derived properties were compared with the pervious reservoir model, which was based on well interpolation. There is an overall agreement between the initial reservoir model and the seismic results in the pay zone. Conclusions The validity of the method strongly relies on three factors: 1. Accurate relationships between seismic attributes and rock properties that can be assessed from a detailed laboratory study. 2. Coherency among data acquired at core, log, and seismic scales. 3. Good-quality seismic data, interpretation, and seismic processing and inversion techniques. NIOC-RIPI should install a system for core velocity measurements (Rock Physics Lab), has extensively measured the velocity of elastic waves propagating through core samples in the reservoir conditions to make "Rock Physics Model". That plays very important role in the Iranian reservoir characterization. References 1. Ibrahim Palaz, and Kurt J. Marfurt, 1996, Carbonate Seismology, Society of Exploration Geophysicists. 2. Zhijing Wang, 2001, Fundamental of seismic Rock Physics, Geophysics, Vol. 66,no Amos Nur, and Zhijing Wang, 1989, Seismic and Acoustic Velocities in Reservoir Rocks Volume 1: Experimental Studies, Society of Exploration Geophysicists. 4. Zhijing Wang, and Amos Nur, 1992, Seismic and Acoustic Velocities in Reservoir Rocks Volume 2: Theoretical and Model Studies, Society of Exploration Geophysicists. 5. Zhijing Wang, and Amos Nur, 2000, Seismic & Acoustic Velocities in Reservoir Rocks Volume 3: Recent Developments, Society of Exploration Geophysicists.