Field Validation of Drillpipe Rotation Effects on Equivalent Circulating Density

Abstract

It is important to predict the Equivalent Circulating Density (ECD) of fluids as closely as possible for safe drilling and completion of wells. This is especially true for those challenging wells where the margin between hole collapse and formation fracturing is very narrow. These characteristics of narrow safe drilling windows are commonly seen in extended-reach drilling (ERD) and deepwater wells, and pose significant drilling and cementing challenges. Over recent years, the changes in ECD caused by fluid compressibility, downhole fluid rheology, drillpipe eccentricity, and rate of penetration have been widely studied. In contrast, work on the modeling of drillpipe rotation effects on pressure drop and ECD have received relatively little attention. Early studies have looked at the relationship between circulating pressure drop, especially in slimhole drilling configurations, and at very high drillpipe rotational speeds. More recently the predicted effects of rotation on ECD in concentric and eccentric wellbore geometries have been studied and model improvements have been made. These technical approaches are summarized in this paper. The effect of drillpipe rotational speed on the predicted ECD for different drillstring combinations are presented and discussed. The calculated effects of drillpipe rotation on pressure drop and ECD are compared to actual field measurements using downhole annular pressure gauges. From the results discussed in this paper, the reader can gauge the accuracy of the current calculation methods. The changes in ECD with drillpipe rotation can now be better predicted, something especially important for those wells whose safe drilling window is narrow. Ultimately this reduces drilling and completions risk and helps assure safe and efficient well construction. Introduction Many studies on the effects of drillpipe rotation on annular drilling hydraulics have been performed over the years1,2,3. In these studies, the authors have looked at hydraulic effects in terms of changes in annular pressure drop (?P). They generally concluded that annular pressure initially drops with increasing drillpipe rotation speed, and later increases with increasing drillpipe rotation speed. In slim hole drilling studies4,5,6, it was found that a rotating drillpipe can produce large increases in annular pressure drop when annular clearances are small. Later, with the advent of downhole pressure drilling tools, researchers7,8,9 found that there was indeed a positive link between drillpipe rotation speed and Equivalent Circulating Density (ECD), a term that mathematically combines Equivalent Static Density (ESD) and annular pressure drop converted to density by the following equation: (1) ECD* = *ESD* + *?P/0 .052/TVD Figure 1 and Figure 2 show results from published work8,9 that clearly demonstrate a relationship between drillpipe rotation speed and increasing ECD. Figure 1 shows data for a 12.25-in section, while Figure 2 contains data for 8.75-in and 8.5-in sections. In presenting the data, the authors did not publish a model to account for the measured changes in ECD. Today, researchers now generally agree that there is a positive relationship between drillpipe rotation speed and annular pressure drop / ECD. Until recently there has not been published a comprehensive mathematical model that accurately predicts the effects of drillpipe rotation on annular pressure drop / ECD. Results using a preliminary model10 were published for concentric wellbores, and subsequently results for a more comprehensive model11 were published for eccentric wellbores. Studies of drillpipe rotation effects in circulating invert emulsion drilling fluids were made, and the combined effects on ECD were measured. In these "fingerprinting" exercises performed on a North Sea deviated well, key operational and drilling fluid parameters were recorded and the subsequent ECD measurements were measured and recorded. This body of work represents the most comprehensive set of data from which to study the effects of drillpipe rotation on annular pressure changes. In this paper, the data set from the North Sea experiments is used to validate the mathematical model constructed for drillpipe rotational effects in concentric and eccentric wellbores.

Annular Frictional Pressure Losses During Drilling—Predicting the Effect of Drillstring Rotation

“…The increase was less pronounced when the rotation rate continued to increase further up to 120rpm. Fiveteen years later Hemphill et al [27] reported similar results for a North Sea well. Field data also showing a reduction in annular frictional pressure losses with increased drill string rotation does also exist [31] showing the complexity of the flow problem.…”

“…Unlike the results from the majority of the laboratory studies, most of the field measurements [22][23][24][25][26][27][28][29][30] have shown a significant increase in pressure loss as the pipe rota tion increases. The discrepancy between lab observations and field measurements can be attributed to several factors, such as operat ing with multiple dimension scales, drillpipe wobbling or instabil ity, the irregular geometry of the wellbore, tool joint effect, far too simple fluid systems in the laboratory or a combination of these factors.…”

New approach to evaluate the equivalent circulating density (ECD) using artificial intelligence techniques

“…ANNs are at the leading edge of computational systems used to produce, or at least mimic, intelligent behavior. ANN is capable of resolving paradigms that linear computing cannot process (Andagoya et al 2015;Hemphill et al 2007;Omosebiet al 2012).…”

“…Unlike classical AI techniques which directly emulate rational and logical reasoning, neural networks are able to reproduce the underlying processing mechanisms which give rise to intelligence as an emergent property of complex adaptive systems (Shanmuganathan and Samarasinghe 2016). ANN systems have successfully been developed and deployed to solve capacity planning, pattern recognition, intuitive problem-related aspects, robotics, and business intelligence (Andagoya et al 2015;Hemphill et al 2007).…”

“…To have an accurate prediction using AI techniques, data have to be filtered and analyzed. Filtration process starts with removing all random values that cannot represent the measurements such as negative values, 999 values and null ones (Andagoya et al 2015;Hemphill et al 2007;Omosebiet al 2012). The second process of filtration was based on the use of histogram plot to remove the outliers.…”