**2.3 Estimating rock properties from CMSE**

 The next step is to leverage the estimation of CMSE and UCS to build a real-time wellbore geomechanical model. The CMSE is directly used as a proxy for UCS by finding a linear correlation of the CMSE to the average UCS values in the zone of interest. Velocity in rocks primarily depends on three factors namely porosity/ effective pressure, saturating fluids and lithology/rock minerals. When focusing primarily on the lateral section, it is reasonable to assume that saturating fluids are fairly homogenous. Thus, the two contributing factors to acoustic and shear velocity become lithology and porosity/effective pressure which are used to estimate these velocities and the rock mechanical properties. For example, the Young's Modulus (YM) can be derived from UCS using multiple available correlations based on different lithologies. Knowing the YM could lead to using other correlations to estimate the Poisson's ratio (PR), Shear Modulus (G), Porosity (PHI), Fracture Index (FI), and rock brittleness (STRBRT). Majidi et al. [7] showed how the MSE could also be used to derive pore pressure. Using frictional faulting theory, with

### **Figure 1.**

*Comparison of CMSE (blue) derived from surface drilling data vs. downhole MSE (orange) measured downhole. Notice the difference of the CMSE values from the MSE derived from surface drilling data without correction (gray).* 

*Surface Drilling Data for Constrained Hydraulic Fracturing and Fast Reservoir Simulation… DOI: http://dx.doi.org/10.5772/intechopen.84759* 

#### **Figure 2.**

*(A) Using the commonly found surface drilling data to estimate the (B) pore pressure and stresses and (C) key geomechanical logs, porosity and natural fractures along any wellbore.* 

the UCS and the pore pressure, in-situ stresses can also be estimated. **Figure 2(A)**  illustrates the common input surface drilling data and the resulting outputs that include stresses in **Figure 2(B)** and rock properties in **Figure 2(C)**. Using these key rock properties as inputs, multiple other properties combining both rock properties and stresses can be derived and used in completion optimization.
