Drilling Data Based Approach for Equivalent Circulation Density Prediction While Drilling

Abstract

The current research presents a machine learning application toward predicting the equivalent circulating density (ECD) in real-time while drilling operations. Maintaining high accuracy in estimating equivalent circulating density (ECD) is crucial due to the potential well control issues that can arise from inaccurate ECD values. Inaccurate ECD can lead to problems such as fluid losses, formation fracturing, kicks, and blowouts. Therefore, precise ECD estimation plays a vital role in preventing these issues and ensuring the safety and stability of drilling operations. The fourth industrial revolution provided high technology-based solutions to serve the oil and gas industry and machine learning is considered one of the best tools in research and development. The developed model within this study utilized the drilling hydraulic data in terms of initial mud weight, mud pumping standpipe pressure, and pumping rate to be fed to the random forest model to predict the ECD with good accuracy. A data set of 5,140 data points was used through a comprehensive data analytics workflow to enhance data quality that greatly impacted the model accuracy. The obtained results showed the outperformance of the developed model to predict ECD with a correlation coefficient (R) of 0.99 between the actual and predicted ECD data with a low mean square error of 0.04. The developed model will add more to the drilling automation process toward safe and efficient operations through providing high accurate ECD values while drilling.

INTRODUCTION

The drilling operations are considered the most critical among the other operations in the oil and gas due to safety precautions and well control issues that impact the personnel's life and the operations’ high cost. Monitoring the drilling operations with many sensors along the surface beside downhole sensors will help control the operations. Equivalent circulating density (ECD) is considered one of the parameters during drilling operations and should be given special care while drilling narrow window zones where there is not a wide gap between the pore and formation fracture pressures. ECD represents the hydrostatic pressure of the drilling mud and the annular friction pressure losses while circulating the wells (Haciislamoglu, 1994). Inaccurate estimation of ECD may lead to many well control issues as ECD might increase and cause mud losses or even fracturing the drilled formations, while low ECD value below the drilled zone pore pressure may result in a kick and flow from the drilled formations. Hence, many well control problems will be encountered with inappropriate ECD estimation. Many factors affect ECD such as hole geometry, pressure losses profile, drilling mud rheological characteristics especially mud weight and viscosity, well pressures and temperature profiles, and hole cleaning (Hemphill and Ravi, 2011; Zhang et al. 2013; Abdelgawad et al. 2019).