Effect of Formation Characteristics on Rate of Pentaration Modeling Using Multiple Regression Methods: A Case Study of an Oil Well in Khasib Formation, Buzurgan Oil Field

The reservoir description relies heavily on petrophysical characteristics while drilling operations are governed by geomechanical characteristics. Improving the rate of penetration ROP is one of the key methods to reduce drilling costs. ROP is affected by different interconnected factors, which makes it very difficult to infer the mutual effect of each individual parameter. A robust ROP is required to understand the complexity of the drilling process. Therefore, multiple Regression methods are used to predict ROP and capture the effect of the changes in the drilling parameters and formation characteristics. Well logs were used to determine the rock's physical characteristics and uniaxial compressive strength as well. The goal of this research project is to examine and contrast the effects of petrophysical characteristics on ROP in one well located in the Khasib Formation, Buzurgan oil field, southern Iraq, in which a new ROP model has been created. Multiple Nonlinear Regression was used to simulate the model. The model's estimate was enhanced by precisely including the rock properties. Correlation coefficients that utilize petrophysical properties were found to be 0.85 whereas the operational parameters without using the petrophysical properties were found to be 0.56, according to the simulation findings by using multiple nonlinear regression. Therefore, when determining the employing operational parameters to forecast ROP, this method can be used in pre-planning and post-analysis to reduce drilling costs.