Abstract
Tracking the rheological properties of the drilling fluid is a key factor for the success of the drilling operation. The main objective of this paper is to relate the most frequent mud measurements (every 15 to 20 min) as mud weight (MWT) and Marsh funnel viscosity (MFV) to the less frequent mud rheological measurements (twice a day) as plastic viscosity (PV), yield point (YP), behavior index (n), and apparent viscosity (AV) for fully automating the process of retrieving rheological properties. The adaptive neuro-fuzzy inference system (ANFIS) was used to develop new models to determine the mud rheological properties using real field measurements of 741 data points. The data were collected from 99 different wells during drilling operations of 12 ¼ inches section. The ANFIS clustering technique was optimized by using training to a testing ratio of 80% to 20% as 591 data points for training and 150 points, cluster radius value of 0.1, and 200 epochs. The results of the prediction models showed a correlation coefficient (R) that exceeded 0.9 between the actual and predicted values with an average absolute percentage error (AAPE) below 5.7% for the training and testing data sets. ANFIS models will help to track in real-time the rheological properties for invert emulsion mud that allows better control for the drilling operation problems.
Highlights
During the drilling operations, drilling fluids are used to provide many functions
artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machines (SVM) tools were used to estimate the P-wave and S-wave travel times from the well logs data with a low error less than 5% AAPE; the results showed that ANN outperformed the ANFIS
The study predicted the rheological properties such as the plastic viscosity, apparent viscosity, the rheometer readings at 600 and 300 revolution per minute and the flow behavior index for oil-based mud from the mud weight, the Marsh funnel viscosity and solid content and the results showed that the correlation coefficient was higher than 90%
Summary
During the drilling operations, drilling fluids are used to provide many functions. Chemical additives are added to the drilling fluid composition to adjust the fluid rheological and filtration properties in terms of the plastic viscosity (PV), yield point (YP), gel strength, and the filtrate invasion into the formation [4], in addition to the regulation of pH value, density, and water phase activity. The oil-based mud (OBM) is a type of the drilling fluid, and it is mainly composed of oil as a continuous phase with water content ratio less than 5%. The term “invert emulsion” is often used to represent water in oil emulsion in the oil-based mud system having water in its composition as an added component to provide a desired property [5]. The application of the invert emulsion mud is Sensors 2020, 20, 1669; doi:10.3390/s20061669 www.mdpi.com/journal/sensors
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