ABSTRACT
Tracking the rheological properties of the drilling fluid is a key factor for the success of the drilling operation. The conventional tests that are usually be conducted by the mud engineers have limited resolution of the rheological data. The main objective of the paper is to relate the most frequent mud measurements as mud weight (MWT) and Marsh funnel viscosity (MFV) to the less frequent mud rheological measurements as plastic viscosity (PV), yield point (YP), behavior index (n), and apparent viscosity (AV). Artificial intelligence (AI) is the best tool for modeling such a large number of recorded heuristic data from which the artificial neural networks (ANN) was chosen to be the optimization method. In addition, the study developed empirical correlations for determining the mud rheological properties. 369 real field measurements were used to build the ANN model which were collected from 56 different wells during drilling operations of different sections with different sizes. The results showed a correlation coefficient (R) that exceeded 0.9 between measured and predicted values and with an average absolute percentage error (AAPE) below 8%. The correlations may track on real-time the rheological properties for all-oil mud that allows better control for the drilling operation problems.
During the drilling operations, drilling fluids are mainly used to provide many functions. The primary function of the drilling fluid is to control the formation pressure of the drilled zone (Knox and Jiang, 2005). In addition, the drilling fluid is used to lubricate the drill bit, carry the drilled cuttings, and format a filter cake to support the hole and other functions. From an economic point of view, the drilling fluids cost share 25–40 % of the total well drilling cost (Chilingarian et al., 1983). Therefore, designing and monitoring the drilling fluids parameters are very critical for drilling operations. Bad mud design or non-precise monitoring for the drilling fluid will cause drilling problems, and therefore, will add an extra cost to the drilling expenditures (Jenkins and Crockford, 1975; Okoro et al., 2018). Consequently, monitoring the drilling fluid on real-time will help to complete the drilling operation with a successful technical and economic program. The all-oil mud is a type of oil-based drilling fluids (OBM) and it is mainly composed of oil as a continuous phase with no water (Amani et al., 2012). The other type of OBM is the invert emulsion mud which is containing an amount of water and this is the major difference between the two types. The all-oil mud is a mud system composed of oil with a low level of dispersed additives. The field application of the all-oil system showed successful case studies with better mud rheology and hole cleaning than the invert emulsion mud system. All-oil muds are used to drill difficult wells, such as long sections of high angle and high-pressure high-temperature (HPHT) wells. The application of the all-oil system provides a higher penetration rate, excellent lubrication properties, thermal stability, improves hole cleaning, and reduces the bit wear significantly (Fraser, 1992).
