This study aims to correlate the response of pressure transient test to permeability distribution type. For this purpose, correlated permeability distributions in x-y direction are generated using fractional Brownian motion (fBm) as it has been shown in literature that permeability in carbonate reservoirs exhibits an fBm type distribution horizontally. 2-D fBm permeability distributions created using mid point displacement method are employed as data to a black oil simulator. The intermittence exponent, H or fractal dimension of the distribution, D, as defined by D ¼ 2)H, characterizes the distribution type. All permeability distributions are normalized to represent the same arithmetic mean (20, 100, and 500 mD) and uniform variance so that only their fractal dimension that underlies the smoothness of the distribution distinguishes them. Many different realizations of permeability distributions are generated based on the random number seeds used and pressure transient (drawdown) tests are simulated using a black oil simulator package (ECLIPSE 100). Pressure transient analysis is performed using PanSystem package. As a base case and for the comparison purpose, the same procedure is repeated for the totally homogeneous case (the same permeability for all grids) and a random (normally distributed) permeability distribution with the same mean and uniform variance. The effects of permeability distribution type on the pressure response are clarified. A strong impact of heterogeneity is observed as an increase in skin effect with increasing fractal dimension of permeability distribution. This additional (or pseudo) skin effect due to heterogeneity is correlated to the fractal dimension of the permeability distribution. As a further step, the procedure is repeated for different flow rates applied during the drawdown test. The correlation between the fractal dimension of permeability distribution and additional skin is improved by incorporating the rate into it. The methodology followed can be used in the assessment of reservoir heterogeneity quantitatively using pressure transient response.
Many tools conventionally used in formation evaluation can provide an estimation of reservoir heterogeneity type and degree. Based on this information representative reservoir model can be built through which reservoir pressure and production behavior can be accurately estimated. The estimation of reservoir heterogeneity through reservoir responses, however, is still a challenging task. Well test analyses provide important information about the interwell permeability distribution of a reservoir. This study aims to correlate the response of pressure transient test to permeability distribution type. For this purpose, correlated permeability distributions in x-y direction are generated using fractional Brownian motion (fBm) as it has been shown in literature that permeability exhibits an fBm type distribution horizontally. 2-D fBm permeability distributions created using mid point displacement method are employed as data to a black oil simulator. Intermittence exponent, H or fractal dimension of the distribution, D, as defined by D=2-H, characterizes the distribution type. All permeability distributions are normalized to represent the same arithmetic mean (20, 100, and 500 mD) and uniform variance so that only their fractal dimension that underlies the smoothness of the distribution distinguishes them. Many different realizations of permeability distributions are generated based on the random number seeds used and pressure transient (drawdown) tests are simulated using a black oil simulator package (ECLIPSE 100). Pressure transient analysis is performed using PanSystem package. As a base case and for the comparison purpose, the same procedure is repeated for totally homogeneous case and random (normally distributed) permeability distribution with the same mean and uniform variance. The effects of permeability distribution type on the pressure response are clarified. A strong impact of heterogeneity is observed as an increase in skin effect with increasing fractal dimension of permeability distribution. This additional (or pseudo) skin effect due to heterogeneity is correlated to the fractal dimension of the permeability distribution. As a further step, the procedure is repeated for different flow rates applied during the drawdown test.The correlation between the fractal dimension of permeability distribution and additional skin is improved by incorporating the rate into it. The methodology followed can be used in the assessment of reservoir heterogeneity quantitatively using pressure transient response. Introduction Permeability heterogeneity is one of the most important reservoir parameters to be identified for the performance estimation and further field development in reservoir engineering. Vertical permeability distribution can be assessed by conventional tools, namely well logs and drilling data. Description of horizontal heterogeneity is more challenging. The heterogeneity of the permeability field can be defined using available tools and the production performance can be estimated based on this data. Inversely, one can use the production data1–7 or pressure change in time8–22 to describe the permeability heterogeneity. This would be a desirable application but still a challenging task as a unique solution to the problem cannot easily be obtained.
The active government gas exploration programme in Oman has recently added another sizeable gas-condensate discovery that was drilled and tested by Central-C-1. Destined to unlock the first CA sandstone gas-condensate field, the well results indicated a very prolific reservoir. In the process of data gathering, a number of challenging aspects were identified and assessed. Residual gas saturation is the most interesting and potentially high impacting aspect. This paper addresses variations on the gas saturation profile as calculated from the petrophysical logs, the identification from the special core analysis measurement of high residual gas saturation rocks, and all relevant findings inferred from the production testing and the static pressure gradient measurement. Despite cautioned applicability of the SCAL measurement results to reservoir conditions, a potential evidence for part of the CA reservoir accommodating high residual gas saturation was recorded. Number of scenarios were modelled to assess the impact of high residual gas saturation in relation with other reservoir uncertainties normally associated with exploration reserve bookings. These scenarios ultimately studied the impact of the residual gas saturation uncertainty on the development economics of the field. This paper explains why major economic measures, such as gas and the condensate recovery efficiencies, well placements and aquifer influx were seen sensitive to this uncertainty. For a comprehensive evaluation of its impact, a relationship between rock properties distribution and residual gas saturation was invisaged as a comprehensive evaluation method. In a deeper concept this translates into a relationship between the interpreted original depositional model and the adopted charge model. This interesting relationship was evaluated in the simulator using a special saturation-porosity dependence that was primarily based on the SCAL measurements. This paper details the analytical and the numerical approach used to evaluate the impact of the uncertainty in residual gas saturation. It highlights how this uncertainty features within the appraisal data gathering targets and within the surveillance strategy of this field. Introduction Central-C-1 well was drilled in 2000 that resulted in discovering a sizable gas-condensate field. The well was successfully production tested. However, high residual gas saturation was interpreted in some of the penetrated reservoir zones. This posed a challenge to model particularly with good production test results. Reservoir simulation was used to assess impact of such high values on recovery efficiencies.
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