Rock mechanics utilizes empirical formulas which are based on studies of certain environments. The shortcoming of such criteria is having estimations of rock physical properties with high uncertainty and not field/formation specific. The objective of this paper is to apply a core-log integration to convert dynamic mechanical properties captured from formation evaluation logs and calibrate them with core static data to generate a continuous profile of data with low uncertainty and generate correlations applicable to the specific physical environment.

To obtain proper rock mechanical correlations, building a mechanical earth model (MEM) calibrated with core data and stimulation data is essential. Multiple wells drilled in a certain sandstone field with rock mechanical physical tests are analyzed. Multi-arm caliber data is also put in use to establish knowledge about in-situ stress directions. The procedure starts with gathering and filtering acoustic slowness & shear, formation pressure, density, and oriented multi-arm caliper logs. Next, calibration of dynamic to core static mechanical data collected in the lab is established. The geomechanical analysis includes an understanding of the state of stresses in a chosen reservoir along with rock elastic and failure properties. The complied data is then integrated using different workflows to develop Mechanical Earth Model (MEM). The intended rock mechanics correlations include elastic constants (Young's Modulus and Poisson's ratio), and rock failure parameters. Once Mechanical Earth Model (MEM) is established, dynamic logging data and core static data are correlated to produce key rock mechanics elements that are field and formation specific. The correlations include Young's Modulus, Poisson's Ratio, Unconfined Compressive Strength (UCS) correlation, and Friction Angle (FANG) correlation. A range of each rock mechanic element is also highlighted for the specific environment showcasing the limits expected for collapse and fracture. Ultimately, stress profile is generated with low uncertainty highlighting magnitudes of maximum and minimum horizontal stresses along with the given interval.

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