Abstract
Abstract
This proposed paper aims to evaluate the impact of poor logging data on the prediction of accurate mud weight and to assess the impact of Uni-Axial Compressive Strength (UCS) for weak to moderate and moderate to strong formations with fracture and minimum mud/stability pressure gradients. Six approximate correlations are developed as a function of UCS to predict the fracture and stability pressure gradients for the stated range of formation.
This study employed MATLAB code for the analysis of logging data to identify instabilities in the offset well and estimate the rock's mechanical properties through numerical simulation. By incorporating data from nearby wells, the logging data were rectified, facilitating the recalculation of optimal mud weights using a geomechanical earth model. The case study focused on three UCS correlations suitable for weak to moderate and moderate to strong formations. Scatter plots of fracture and stability pressure gradients against UCS obtained from MATLAB simulation were generated and plotted, which were then combined to derive approximate correlations for each correlation through regression analysis for the prediction of minimum and maximum mud weights (referred to as stability and fracture pressure gradient) as functions of UCS within the considered formation range.
Inaccurate logging data, especially caused by hole enlargements or breakout for offset wells can lead to erroneous estimations of recommended mud weights for drilling plans which can pose serious technical, safety and financial risks in drilling operations. The proposed approach of corrections to the offset well's data has been observed to provide more reliable and safer recommended mud weights. About the UCS exanimation, the first correlation is a function of static Young’s modulus, the second is a function of P-velocity, and the third is a function of dynamic Young’s modulus and dynamic Poisson’s ratio. The first and second correlations have shown the representation of moderate to very strong formations which agrees with the formation of the case study while the third correlation has produced values of UCS which are not representative of the well as it demonstrates the behavior of weak formations. Regarding the relationship between UCS and mud weights, it was found that as UCS increases, the fracture pressure gradient increases while the stability pressure gradient decreases for all three correlations.
The workflow presented in this paper can improve the estimation of optimal mud weights for new wells before drilling, potentially reducing uncertainties and the associated risks of wellbore instability. The approximate correlations for various formation types, also detailed in this paper can potentially serve as approximate as well as valuable engineering tools that enhance the estimation of optimal mud weights without the need for in-situ stress data and other mechanical properties of the formation.