Abstract

Abstract This paper presents an innovative log-based method of determining pore volume compressibility as a function of pore pressure depletion. The approach considers changes in reservoir stress associated with pore pressure change (stress path) and incorporates constraints that ensure deformations are within elastic bounds. The approach incorporates the effect of stress anisotropy by using elastic moduli derived from stress-strain curves under simulated triaxial loading conditions. The triaxial condition pore volume compressibility was then converted to that of unaxial strain equivalent, which best describes the existing reservoir characteristics. The proposed methodology is particularly useful for predicting pressure-dependent pore volume compressibility where core specimens are either not available or in situations where laboratory measurements are prohibitively laborious and time consuming. For input, the method requires bulk modulus, compressive strength and other mechanical properties that characterize an elastic material, preferably predicted using a log-based mechanical property algorithm in order to generate a foot-by-foot profile of pore volume compressibility. A continuous profile of uniaxial strain pore volume compressibility with depth from log provides quick assessments of pore volume compressibility variations across the reservoir intervals. It is also useful and cost-effective for constraining pore volume compressibility of all the reservoirs penetrated by the well (and logged) but with only limited core data available for calibrations. The example shallow oil well data illustrates that pore volume compressibility decreases with decreasing pore pressure (or increase effective stress). An inverse pore volume compressibility to strength relationship was also observed. It was also observed that pore volume compressibility decreases with increasing porosity until the effective porosity reaches a critical minimum value. At porosity higher than the critical value, the pore volume compressibility increases with increasing porosity. This may suggest that reservoirs with a porosity less than the critical value are more likely to be under pressure drive, while reservoirs with porosity higher than the critical value are more likely to be under compaction drive.

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